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Reconfigured folder structure

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Added Evaluation, Preprocessing, Training, Transformation folders.
Preprocessing is just a rework of the folder for the new structure of the old preprocessing folder.

Training and Transformation are the old project file broken up into two parts and restructured.

Evaluation is for evaluating the predictive power of the model.
This commit is contained in:
nmelone
2018-09-24 20:48:07 -05:00
parent 953507a22a
commit 7b30c71b53
27 changed files with 4547 additions and 4751 deletions
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532
Project Final/.ipynb_checkpoints/Project-checkpoint.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Project Notebook\n",
"This is the full and complete notebook that takes in the data from NOAA and processes it into frames to be used in the PredNet architecture and produce a resulting prediction."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import os\n",
"from tqdm import tqdm"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#Getting a list of files in raw data folder\n",
"filenames = os.listdir('D:/Nico/Desktop/processed_data')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"header_wanted = [\n",
" 'HOURLYVISIBILITY',\n",
" 'HOURLYDRYBULBTEMPC',\n",
" 'HOURLYWETBULBTEMPC',\n",
" 'HOURLYDewPointTempC',\n",
" 'HOURLYRelativeHumidity',\n",
" 'HOURLYWindSpeed',\n",
" 'HOURLYWindGustSpeed',\n",
" 'HOURLYStationPressure',\n",
" 'HOURLYPressureTendency',\n",
" 'HOURLYPressureChange',\n",
" 'HOURLYSeaLevelPressure',\n",
" 'HOURLYPrecip',\n",
" 'HOURLYAltimeterSetting']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"usecols = ['DATE','STATION'] + header_wanted"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#Loading all files into a pandas Dataframe\n",
"tqdm.pandas()\n",
"df = pd.concat([pd.read_csv('D:/Nico/Desktop/processed_data/{}'.format(x), usecols=usecols, low_memory=False) for x in tqdm(filenames)])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"At this point all the data has been loaded into a single dataframe and any data changes have been made. The next step is to break the data up by WBAN and place in a 2D array at the appropriate grid cell. "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"stations = pd.read_csv(\"../Playground/stations_unique.csv\", usecols = ['STATION_ID', 'LON_SCALED', 'LAT_SCALED'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"height = 20\n",
"width = 40"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mask = [([0] * width) for i in range(height)]\n",
"\n",
"wban_loc = dict(zip(stations.STATION_ID,zip(stations.LON_SCALED,stations.LAT_SCALED)))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"grid = [([pd.DataFrame()] * width) for i in range(height)]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for key, value in tqdm(wban_loc.items()):\n",
" mask[value[1]][value[0]] = 1\n",
" grid[value[1]][value[0]] = df.loc[df.STATION == key]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.imshow(mask)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#TODO Handle different sized data some stacks too short\n",
"def create_frames(data,height, width, depth):\n",
" days = []\n",
" frames = []\n",
" for i in tqdm(range(depth)):\n",
" frame = np.zeros((height,width,12))\n",
" for y in range(height):\n",
" for x in range(width):\n",
" if(not data[y][x].empty):\n",
" frame[y][x] = data[y][x].iloc[[i],1:13].values.flatten()\n",
" if((i+1)%24 != 0):\n",
" frames.append(frame)\n",
" else:\n",
" frames.append(frame)\n",
" days.append(frames)\n",
" frames = []\n",
" return days"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def average_grid_fill(mask,data, height, width):\n",
" \n",
" for i in range(height):\n",
" for j in range(width):\n",
" if(mask[i][j] != 1):\n",
" neighbors = get_neighbors(j,i,data)\n",
" data[i][j] = np.mean(neighbors)\n",
" \n",
" return data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def get_neighbors(x,y,g):\n",
" neighbors = []\n",
" for i in [y-1,y,y+1]:\n",
" for j in [x-1,x,x+1]:\n",
" if(i >= 0 and j >= 0):\n",
" if(i != y or j != x ):\n",
" try:\n",
" neighbors.append(g[i][j])\n",
" except:\n",
" pass\n",
" return neighbors"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def store_sequence(frames):\n",
" import hickle as hkl\n",
" source_list = []\n",
" \n",
" for days in range(len(frames)):\n",
" for day in range(len(frames[days])):\n",
" source_list += '{}'.format(days)\n",
" \n",
" hkl.dump(frames, './data/train/x_train.hkl')\n",
" hkl.dump(source_list, './data/train/x_sources.hkl')\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Splits is a dictionary holding train, test, val\n",
"the values for train, test, and val are lists of tuples holding category and folder name\n",
"in the end each image gets a source associated with it\n",
"there is only one data and one source hickle dump for each of train test and val"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"frames = create_frames(grid, height, width,504)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#TODO use loop to average each frame\n",
"for x in tqdm(range(len(frames))):\n",
" for y in range(len(frames[0])):\n",
" frames[x][y] = average_grid_fill(mask, frames[x][y], height, width )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"store_sequence(frames)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"np_frames = np.array(frames)\n",
"np_frames.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"store_sequence(np_frames)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"At this point I have processed the data and made it into discrete frames of data and it is time to run it through the PredNet architecture for training."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
]
}
],
"source": [
"np.random.seed(123)\n",
"from six.moves import cPickle\n",
"\n",
"from keras import backend as K\n",
"from keras.models import Model\n",
"from keras.layers import Input, Dense, Flatten\n",
"from keras.layers import LSTM\n",
"from keras.layers import TimeDistributed\n",
"from keras.callbacks import LearningRateScheduler, ModelCheckpoint\n",
"from keras.optimizers import Adam\n",
"\n",
"from prednet import PredNet\n",
"from data_utils import SequenceGenerator"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"WEIGHTS_DIR = './weights/'\n",
"DATA_DIR = './data/'"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"save_model = True # if weights will be saved\n",
"weights_file = os.path.join(WEIGHTS_DIR, 'prednet_weather_weights.hdf5') # where weights will be saved\n",
"json_file = os.path.join(WEIGHTS_DIR, 'prednet_weather_model.json')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# Data files\n",
"#TODO: Use the files from NOAA and process them into proper frames\n",
"train_file = os.path.join(DATA_DIR,'train/', 'x_train.hkl')\n",
"train_sources = os.path.join(DATA_DIR, 'train/', 'x_sources.hkl')\n",
"#val_file = os.path.join(DATA_DIR, 'X_val.hkl')\n",
"#val_sources = os.path.join(DATA_DIR, 'sources_val.hkl')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# Training parameters\n",
"nb_epoch = 1\n",
"batch_size = 4\n",
"samples_per_epoch = 500\n",
"N_seq_val = 100 # number of sequences to use for validation"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Model parameters\n",
"n_channels, im_height, im_width = (12, 20, 40)\n",
"input_shape = (n_channels, im_height, im_width) if K.image_data_format() == 'channels_first' else (im_height, im_width, n_channels)\n",
"stack_sizes = (n_channels, 48, 96)\n",
"R_stack_sizes = stack_sizes\n",
"A_filt_sizes = (3, 3)\n",
"Ahat_filt_sizes = (3, 3, 3)\n",
"R_filt_sizes = (3, 3, 3)\n",
"layer_loss_weights = np.array([1., 0., 0.]) # weighting for each layer in final loss; \"L_0\" model: [1, 0, 0, 0], \"L_all\": [1, 0.1, 0.1, 0.1]\n",
"layer_loss_weights = np.expand_dims(layer_loss_weights, 1)\n",
"nt = 24 # number of timesteps used for sequences in training\n",
"time_loss_weights = 1./ (nt - 1) * np.ones((nt,1)) # equally weight all timesteps except the first\n",
"time_loss_weights[0] = 0"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"prednet = PredNet(stack_sizes, R_stack_sizes,\n",
" A_filt_sizes, Ahat_filt_sizes, R_filt_sizes,\n",
" output_mode='error', return_sequences=True)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"inputs = Input(shape=(nt,) + input_shape)\n",
"errors = prednet(inputs) # errors will be (batch_size, nt, nb_layers)\n",
"errors_by_time = TimeDistributed(Dense(1, trainable=False), weights=[layer_loss_weights, np.zeros(1)], trainable=False)(errors) # calculate weighted error by layer\n",
"errors_by_time = Flatten()(errors_by_time) # will be (batch_size, nt)\n",
"final_errors = Dense(1, weights=[time_loss_weights, np.zeros(1)], trainable=False)(errors_by_time) # weight errors by time\n",
"model = Model(inputs=inputs, outputs=final_errors)\n",
"model.compile(loss='mean_absolute_error', optimizer='adam')"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"_________________________________________________________________\n",
"Layer (type) Output Shape Param # \n",
"=================================================================\n",
"input_1 (InputLayer) (None, 24, 20, 40, 12) 0 \n",
"_________________________________________________________________\n",
"pred_net_1 (PredNet) (None, 24, 3) 1645548 \n",
"_________________________________________________________________\n",
"time_distributed_1 (TimeDist (None, 24, 1) 4 \n",
"_________________________________________________________________\n",
"flatten_1 (Flatten) (None, 24) 0 \n",
"_________________________________________________________________\n",
"dense_2 (Dense) (None, 1) 25 \n",
"=================================================================\n",
"Total params: 1,645,577\n",
"Trainable params: 1,645,548\n",
"Non-trainable params: 29\n",
"_________________________________________________________________\n"
]
}
],
"source": [
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"truth = []\n",
"for i in range(20):\n",
" truth.append(np.random.randint(255,size=(1)))\n",
"output = np.array(truth)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"train_generator = SequenceGenerator(train_file, train_sources, nt, batch_size=batch_size, shuffle=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"lr_schedule = lambda epoch: 0.001 if epoch < 75 else 0.0001 # start with lr of 0.001 and then drop to 0.0001 after 75 epochs\n",
"callbacks = [LearningRateScheduler(lr_schedule)]\n",
"#history = model.fit(np_frames, output ,batch_size, nb_epoch, callbacks=callbacks)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/1\n"
]
}
],
"source": [
"history = model.fit_generator(train_generator, samples_per_epoch / batch_size, nb_epoch, callbacks=callbacks)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

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Project Final/Evaluation/Evalutation.ipynb Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
]
}
],
"source": [
"import os\n",
"import numpy as np\n",
"from six.moves import cPickle\n",
"import matplotlib\n",
"matplotlib.use('Agg')\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.gridspec as gridspec\n",
"%matplotlib inline\n",
"from keras import backend as K\n",
"from keras.models import Model, model_from_json\n",
"from keras.layers import Input, Dense, Flatten\n",
"\n",
"from prednet import PredNet\n",
"from data_utils import SequenceGenerator\n",
"\n",
"from tqdm import tqdm"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"n_plot = 40\n",
"batch_size = 10\n",
"nt = 24"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"WEIGHTS_DIR = '../Training/weights/'\n",
"DATA_DIR = '../data/'\n",
"RESULTS_SAVE_DIR = './weather_results/'"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"weights_file = os.path.join(WEIGHTS_DIR, 'prednet_weather_weights.hdf5')\n",
"json_file = os.path.join(WEIGHTS_DIR, 'prednet_weather_model.json')\n",
"test_file = os.path.join(DATA_DIR, 'x_test.hkl')\n",
"test_sources = os.path.join(DATA_DIR, 'sources_test.hkl')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# Load trained model\n",
"f = open(json_file, 'r')\n",
"json_string = f.read()\n",
"f.close()\n",
"train_model = model_from_json(json_string, custom_objects = {'PredNet': PredNet})\n",
"train_model.load_weights(weights_file)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# Create testing model (to output predictions)\n",
"layer_config = train_model.layers[1].get_config()\n",
"layer_config['output_mode'] = 'prediction'\n",
"data_format = layer_config['data_format'] if 'data_format' in layer_config else layer_config['dim_ordering']\n",
"test_prednet = PredNet(weights=train_model.layers[1].get_weights(), **layer_config)\n",
"input_shape = list(train_model.layers[0].batch_input_shape[1:])\n",
"input_shape[0] = nt\n",
"inputs = Input(shape=tuple(input_shape))\n",
"predictions = test_prednet(inputs)\n",
"test_model = Model(inputs=inputs, outputs=predictions)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"test_generator = SequenceGenerator(test_file, test_sources, nt, sequence_start_mode='unique', data_format=data_format)\n",
"X_test = test_generator.create_all()\n",
"X_hat = test_model.predict(X_test, batch_size)\n",
"if data_format == 'channels_first':\n",
" X_test = np.transpose(X_test, (0, 1, 3, 4, 2))\n",
" X_hat = np.transpose(X_hat, (0, 1, 3, 4, 2))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Compare MSE of PredNet predictions vs. using last frame. Write results to prediction_scores.txt\n",
"mse_model = np.nanmean( (X_test[:, 1:] - X_hat[:, 1:])**2 ) # look at all timesteps except the first\n",
"mse_prev = np.nanmean( (X_test[:, :-1] - X_test[:, 1:])**2 )\n",
"if not os.path.exists(RESULTS_SAVE_DIR): os.mkdir(RESULTS_SAVE_DIR)\n",
"f = open(RESULTS_SAVE_DIR + 'prediction_scores.txt', 'w')\n",
"f.write(\"Model MSE: %f\\n\" % mse_model)\n",
"f.write(\"Previous Frame MSE: %f\" % mse_prev)\n",
"f.close()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Model MSE:\t 14.119876861572266\n",
"Prev Frame MSE:\t 0.02834348939359188\n"
]
}
],
"source": [
"print(\"Model MSE:\\t {}\\nPrev Frame MSE:\\t {}\".format(mse_model,mse_prev))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
" 63%|███████████████████████████████████████████████████▉ | 19/30 [09:38<05:35, 30.47s/it]"
]
}
],
"source": [
"# Plot some predictions\n",
"aspect_ratio = float(X_hat.shape[3]) / X_hat.shape[2]\n",
"plt.figure(figsize = (nt, 7*2*aspect_ratio))\n",
"gs = gridspec.GridSpec(2*7, nt)\n",
"gs.update(wspace=0., hspace=0.2)\n",
"plot_save_dir = os.path.join(RESULTS_SAVE_DIR, 'prediction_plots/')\n",
"if not os.path.exists(plot_save_dir): os.mkdir(plot_save_dir)\n",
"plot_idx = np.random.permutation(X_test.shape[0])[:n_plot]\n",
"for i in tqdm(plot_idx):\n",
" for t in range(nt):\n",
" for c in range(7):\n",
" plt.subplot(gs[t + c*2*nt])\n",
" plt.imshow(X_test[i,t,:,:,c], interpolation='none')\n",
" plt.tick_params(axis='both', which='both', bottom='off', top='off', left='off', right='off', labelbottom='off', labelleft='off')\n",
" if t==0: plt.ylabel('Actual', fontsize=10)\n",
"\n",
" plt.subplot(gs[t + (c*2+1)*nt])\n",
" plt.imshow(X_hat[i,t,:,:,c], interpolation='none')\n",
" plt.tick_params(axis='both', which='both', bottom='off', top='off', left='off', right='off', labelbottom='off', labelleft='off')\n",
" if t==0: plt.ylabel('Predicted', fontsize=10)\n",
"\n",
" plt.savefig(plot_save_dir + 'plot_' + str(i) + '.png')\n",
" plt.clf()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fig=plt.figure(figsize=(15,10))\n",
"columns = 3\n",
"rows = 4\n",
"for i in range(1,columns+rows +1):\n",
" fig.add_subplot(rows,columns,i)\n",
" plt.imshow(X_test[0,0,:,:,i-1],X_hat[0,0,:,:,i-1])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"X_hat[0][0][0][0][2]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

4
Project Final/data_utils.py → Project Final/Evaluation/data_utils.py
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@@ -45,7 +45,9 @@ class SequenceGenerator(Iterator):
def next(self):
with self.lock:
index_array, current_index, current_batch_size = next(self.index_generator)
index_array = next(self.index_generator)
current_index = index_array[0]
current_batch_size = len(index_array)
batch_x = np.zeros((current_batch_size, self.nt) + self.im_shape, np.float32)
for i, idx in enumerate(index_array):
idx = self.possible_starts[idx]

0
Project Final/keras_utils.py → Project Final/Evaluation/keras_utils.py
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0
Project Final/prednet.py → Project Final/Evaluation/prednet.py
View File

2106
Project Final/Preprocessing/preprocess_data.ipynb Normal file
View File

File diff suppressed because it is too large Load Diff

407
Project Final/Preprocessing/stations_unique.csv Normal file
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@@ -0,0 +1,407 @@
,index,STATION_ID,STATION,BEGIN_DATE,END_DATE,STATE,COUNTRY,LATITUDE,LONGITUDE,ELEVATION,LAT_SCALED,LON_SCALED,TUPLES
0,0,WBAN:00184,"ABBEVILLE CHRIS CRUSTA MEMORIAL AIRPORT, LA US",2013-12-31,2018-08-18,Louisiana,United States,29.976000000000006,-92.084,15.2,16,22,"(22, 16)"
2,3,WBAN:14929,"ABERDEEN REGIONAL AIRPORT, SD US",1964-06-30,2018-08-18,South Dakota,United States,45.4433,-98.413,395.3,3,18,"(18, 3)"
4,5,WBAN:13962,"ABILENE REGIONAL AIRPORT, TX US",1946-07-31,2018-08-18,Texas,United States,32.4105,-99.6822,545.6,14,17,"(17, 14)"
10,11,WBAN:94975,"AINSWORTH MUNICIPAL AIRPORT, NE US",2005-12-31,2018-08-18,Nebraska,United States,42.57694,-100.00056,787.6,5,17,"(17, 5)"
13,16,WBAN:14813,"AKRON FULTON INTERNATIONAL AIRPORT, OH US",1998-12-31,2018-08-18,Ohio,United States,41.0375,-81.46417,318.2,7,30,"(30, 7)"
15,18,WBAN:53864,"ALABASTER SHELBY CO AIRPORT, AL US",2001-12-31,2018-08-18,Alabama,United States,33.178329999999995,-86.78166999999998,172.20000000000005,14,26,"(26, 14)"
17,21,WBAN:23061,"ALAMOSA SAN LUIS VALLEY REGIONAL AIRPORT, CO US",1956-12-31,2018-08-18,Colorado,United States,37.4389,-105.8613,2296.1,10,13,"(13, 10)"
22,26,WBAN:54921,"ALBION MUNICIPAL AIRPORT, NE US",2005-12-31,2018-08-18,Nebraska,United States,41.73,-98.05444,548.3000000000002,6,18,"(18, 6)"
26,30,WBAN:00258,"ALEXANDER MUNICIPAL AIRPORT, NM US",2014-07-30,2018-08-18,New Mexico,United States,34.645,-106.834,1583.1,12,12,"(12, 12)"
33,38,WBAN:24044,"ALLIANCE MUNICIPAL AIRPORT ASOS, NE US",2005-12-31,2018-08-18,Nebraska,United States,42.05730000000001,-102.8017,1197.6,6,15,"(15, 6)"
37,42,WBAN:03049,"ALPINE CASPARIS MUNICIPAL AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,30.38333,-103.68333,1375.6,16,14,"(14, 16)"
40,45,WBAN:94299,"ALTURAS MUNICIPAL AIRPORT, CA US",2005-12-31,2018-08-18,California,United States,41.49139,-120.56444,1333.5,6,2,"(2, 6)"
42,47,WBAN:53933,"ALVA REGIONAL AIRPORT, OK US",2005-12-31,2018-08-18,Oklahoma,United States,36.77306,-98.66972,449.3,10,18,"(18, 10)"
43,49,WBAN:23047,"AMARILLO AIRPORT, TX US",1943-02-28,2018-08-18,Texas,United States,35.2295,-101.7042,1098.5,12,16,"(16, 12)"
50,56,WBAN:63811,"ANDREWS MURPHY AIRPORT, NC US",2005-12-31,2018-08-18,North Carolina,United States,35.195,-83.86528,516.9,12,28,"(28, 12)"
51,57,WBAN:00137,"ANGEL FIRE AIRPORT, NM US",2013-12-31,2018-08-18,New Mexico,United States,36.422,-105.29,2554.2000000000007,11,13,"(13, 11)"
58,64,WBAN:04864,"ANTIGO LANGLADE CO AIRPORT, WI US",2005-12-31,2018-08-18,Wisconsin,United States,45.15417,-89.11055999999998,463.9,3,24,"(24, 3)"
59,65,WBAN:12832,"APALACHICOLA AIRPORT, FL US",1944-12-31,2018-08-18,Florida,United States,29.73333,-85.03332999999998,5.8,17,27,"(27, 17)"
82,91,WBAN:93730,"ATLANTIC CITY INTERNATIONAL AIRPORT, NJ US",1946-12-31,2018-08-18,New Jersey,United States,39.452020000000005,-74.56698999999998,18.3,8,35,"(35, 8)"
84,94,WBAN:53932,"ATOKA MUNICIPAL AIRPORT, OK US",2005-12-31,2018-08-18,Oklahoma,United States,34.39833,-96.14806,179.8,12,19,"(19, 12)"
91,102,WBAN:14605,"AUGUSTA STATE AIRPORT, ME US",1972-12-31,2018-08-18,Maine,United States,44.3155,-69.7972,107.0,4,38,"(38, 4)"
94,105,WBAN:94281,"AURORA STATE AIRPORT, OR US",2005-12-31,2018-08-18,Oregon,United States,45.24861,-122.76861000000001,59.7,3,1,"(1, 3)"
102,114,WBAN:54817,"BAD AXE HURON CO MEMORIAL AIRPORT, MI US",2005-12-31,2018-08-18,Michigan,United States,43.78028,-82.98555999999998,233.5,4,29,"(29, 4)"
104,116,WBAN:53138,"BAKER 5 W, NV US",2004-05-08,2018-08-17,Nevada,United States,39.0118,-114.209,2016.9,8,7,"(7, 8)"
105,117,WBAN:24130,"BAKER CITY AIRPORT, OR US",1956-12-31,2018-08-18,Oregon,United States,44.8428,-117.8086,1024.4,3,4,"(4, 3)"
107,119,WBAN:23155,"BAKERSFIELD AIRPORT, CA US",1941-09-30,2018-08-18,California,United States,35.43440000000001,-119.0542,149.0,12,3,"(3, 12)"
111,124,WBAN:14606,"BANGOR INTERNATIONAL AIRPORT, ME US",1956-12-31,2018-08-18,Maine,United States,44.7978,-68.8185,45.1,3,39,"(39, 3)"
112,125,WBAN:14616,"BAR HARBOR AIRPORT, ME US",2005-12-31,2018-08-18,Maine,United States,44.45,-68.36667,26.8,4,39,"(39, 4)"
113,126,WBAN:54833,"BARABOO WISCONSIN DELLS AIRPORT, WI US",2005-12-31,2018-08-18,Wisconsin,United States,43.52194,-89.77360999999998,297.5,5,24,"(24, 5)"
124,137,WBAN:24119,"BATTTLE MOUNTAIN 4 SE, NV US",1972-12-31,2018-08-18,Nevada,United States,40.6118,-116.8917,1373.1,7,5,"(5, 7)"
129,142,WBAN:00282,"BEACH AIRPORT, ND US",2014-08-18,2018-08-18,North Dakota,United States,46.925,-103.98200000000001,840.0,2,14,"(14, 2)"
131,144,WBAN:94947,"BEATRICE MUNICIPAL AIRPORT, NE US",2005-12-31,2018-08-18,Nebraska,United States,40.301390000000005,-96.75389,403.6,7,19,"(19, 7)"
140,155,WBAN:00127,"BEEVILLE MUNICIPAL AIRPORT, TX US",2013-12-31,2018-08-18,Texas,United States,28.35,-97.71700000000001,82.3,18,18,"(18, 18)"
148,163,WBAN:00224,"BEND MUNICIPAL AIRPORT, OR US",2012-12-31,2018-08-18,Oregon,United States,44.095,-121.2,1055.2,4,2,"(2, 4)"
149,165,WBAN:54781,"BENNINGTON MORSE STATE AIRPORT, VT US",2005-12-31,2018-08-18,Vermont,United States,42.89139,-73.24694000000001,251.8,5,36,"(36, 5)"
163,179,WBAN:03044,"BIG SPRING MCMAHON WRINKLE AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,32.2125,-101.52139,784.3000000000002,14,16,"(16, 14)"
164,180,WBAN:24033,"BILLINGS INTERNATIONAL AIRPORT, MT US",1935-04-30,2018-08-18,Montana,United States,45.8069,-108.5422,1091.5,3,11,"(11, 3)"
166,182,WBAN:04725,"BINGHAMTON GREATER AP, NY US",1956-12-31,2018-08-18,New York,United States,42.2068,-75.98,486.2,6,34,"(34, 6)"
168,185,WBAN:23157,"BISHOP AIRPORT, CA US",1943-01-15,2018-08-18,California,United States,37.3711,-118.35799999999999,1250.3,10,4,"(4, 10)"
169,186,WBAN:24011,"BISMARCK MUNICIPAL AIRPORT, ND US",1936-06-30,2018-08-18,North Dakota,United States,46.7825,-100.7572,503.2,2,16,"(16, 2)"
171,188,WBAN:00286,"BLACK RIVER FALLS AREA AIRPORT, WI US",2013-12-31,2018-08-17,Wisconsin,United States,44.25100000000001,-90.855,255.1,4,23,"(23, 4)"
172,189,WBAN:53881,"BLACKSBURG VIRGINIA TECH AIRPORT, VA US",2005-12-31,2018-08-18,Virginia,United States,37.2075,-80.40778,649.8000000000002,10,31,"(31, 10)"
175,195,WBAN:03036,"BLANDING MUNICIPAL AIRPORT, UT US",2014-07-23,2018-08-18,Utah,United States,37.58278,-109.48306000000001,1787.7,10,10,"(10, 10)"
176,196,WBAN:94793,"BLOCK ISLAND STATE AIRPORT, RI US",1989-12-31,2018-08-18,Rhode Island,United States,41.16806,-71.57777999999998,32.0,7,37,"(37, 7)"
179,199,WBAN:23225,"BLUE CANYON AIRPORT, CA US",1956-12-31,2018-08-18,California,United States,39.2774,-120.7102,1608.1,8,2,"(2, 8)"
181,201,WBAN:03859,"BLUEFIELD MERCER CO AIRPORT, WV US",1999-12-31,2018-08-18,West Virginia,United States,37.2978,-81.20366,870.5,10,30,"(30, 10)"
182,203,WBAN:23158,"BLYTHE ASOS, CA US",1942-06-12,2018-08-18,California,United States,33.6186,-114.7142,120.4,13,6,"(6, 13)"
185,207,WBAN:00263,"BOERNE STAGE FIELD AIRPORT, TX US",2014-07-30,2018-08-18,Texas,United States,29.724,-98.695,422.1,17,18,"(18, 17)"
186,208,WBAN:24131,"BOISE AIR TERMINAL, ID US",1930-12-31,2018-08-18,Idaho,United States,43.5666,-116.2405,857.7,5,5,"(5, 5)"
187,209,WBAN:63871,"BONIFAY TRI CO AIRPORT, FL US",2006-08-31,2018-08-18,Florida,United States,30.84583,-85.60139000000001,25.9,16,27,"(27, 16)"
193,215,WBAN:14739,"BOSTON, MA US",1943-11-20,2018-08-18,Massachusetts,United States,42.36060000000001,-71.00970000000002,3.7,6,37,"(37, 6)"
196,219,WBAN:00310,"BOUNDARY CO AIRPORT, ID US",2013-12-31,2018-08-18,Idaho,United States,48.726000000000006,-116.295,711.1,0,5,"(5, 0)"
198,223,WBAN:93808,"BOWLING GREEN WARREN CO AIRPORT, KY US",1972-12-31,2018-08-18,Kentucky,United States,36.9647,-86.4238,160.9,10,26,"(26, 10)"
199,224,WBAN:00353,"BOYSEN THERMOPOL, WY US",2012-12-31,2018-08-18,Wyoming,United States,43.467,-108.389,2225.0,5,11,"(11, 5)"
200,225,WBAN:24132,"BOZEMAN GALLATIN FIELD AIRPORT, MT US",1972-12-31,2018-08-18,Montana,United States,45.788,-111.1608,1349.3,3,9,"(9, 3)"
205,230,WBAN:00451,"BRANSON WEST MUNICIPAL EMERSON FIELD AIRPORT, MO US",2014-07-30,2018-08-18,Missouri,United States,36.6985,-93.4022,411.2,10,21,"(21, 10)"
207,232,WBAN:00435,BRAZOS 451 OILP,2013-07-16,2018-08-18,,,28.5,-95.716,34.1,18,20,"(20, 18)"
211,237,WBAN:00433,"BRIDGEPORT SONORA JUNCTION, CA US",2013-01-09,2018-08-18,California,United States,38.3557,-119.51899999999999,2057.1,9,3,"(3, 9)"
213,239,WBAN:24180,"BRIGHAM CITY AIRPORT, UT US",2014-07-23,2018-08-18,Utah,United States,41.55222,-112.06222,1288.1,6,8,"(8, 6)"
215,241,WBAN:94946,"BROKEN BOW MUNICIPAL AIRPORT, NE US",2005-12-31,2018-08-18,Nebraska,United States,41.43333,-99.63333,771.1,6,17,"(17, 6)"
218,245,WBAN:94902,"BROOKINGS, SD US",2005-12-31,2018-08-18,South Dakota,United States,44.3,-96.8,502.3,4,19,"(19, 4)"
222,250,WBAN:03721,"BRUNSWICK CO AIRPORT, NC US",2005-12-31,2018-08-18,North Carolina,United States,33.92917,-78.07472,7.6,13,32,"(32, 13)"
225,254,WBAN:23159,"BRYCE CANYON AIRPORT, UT US",1956-12-31,2018-08-18,Utah,United States,37.70639,-112.14556,2312.2000000000007,10,8,"(8, 10)"
228,259,WBAN:94037,"BUFFALO ASOS, SD US",1998-12-31,2018-08-18,South Dakota,United States,45.604440000000004,-103.54639,915.6,3,14,"(14, 3)"
229,260,WBAN:94054,"BUFFALO JOHNSON CO AIRPORT, WY US",2005-12-31,2018-08-18,Wyoming,United States,44.38139,-106.72111000000001,1513.9,4,12,"(12, 4)"
232,263,WBAN:03068,"BULLSEYE AUXILIARY AIRFIELD USAFA, CO US",2006-04-30,2018-08-18,Colorado,United States,38.76667,-104.3,1837.9,9,14,"(14, 9)"
238,269,WBAN:04866,"BURLINGTON MUNICIPAL AIRPORT, WI US",2005-12-31,2018-08-18,Wisconsin,United States,42.69,-88.30360999999998,237.4,5,25,"(25, 5)"
239,270,WBAN:94282,"BURLINGTON SKAGIT REGIONAL BAYVIEW AIRPORT, WA US",2005-12-31,2018-08-18,Washington,United States,48.46667,-122.41667,42.7,0,1,"(1, 0)"
240,271,WBAN:14742,"BURLINGTON WEATHER SERVICE OFFICE AIRPORT, VT US",1947-12-31,2018-08-18,Vermont,United States,44.4683,-73.1499,100.6,4,36,"(36, 4)"
246,277,WBAN:14817,"CADILLAC WEXFORD CO AIRPORT, MI US",1990-07-23,2018-08-18,Michigan,United States,44.28333,-85.41667,397.8,4,27,"(27, 4)"
250,281,WBAN:54743,"CALDWELL ESSEX CO AIRPORT, NJ US",2005-12-31,2018-08-18,New Jersey,United States,40.87639,-74.28305999999998,52.7,7,35,"(35, 7)"
251,282,WBAN:94195,"CALDWELL INDUSTRIAL AIRPORT, ID US",2005-12-31,2018-08-18,Idaho,United States,43.65,-116.63333,740.4,4,5,"(5, 4)"
254,285,WBAN:12986,"CALHOUN CO AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,28.65417,-96.68139000000001,9.1,17,19,"(19, 17)"
255,287,WBAN:23136,"CAMARILLO AIRPORT, CA US",1956-12-31,2018-08-18,California,United States,34.21667,-119.08333,23.5,13,3,"(3, 13)"
265,300,WBAN:54923,"CANBY MYERS FIELD AIRPORT, MN US",2006-10-17,2018-08-18,Minnesota,United States,44.729440000000004,-96.26611,363.6,3,19,"(19, 3)"
266,301,WBAN:00285,"CANDO MUNICIPAL AIRPORT, ND US",2013-12-31,2018-08-18,North Dakota,United States,48.48,-99.236,450.2,0,17,"(17, 0)"
269,305,WBAN:93729,"CAPE HATTERAS BILLY MITCHELL FIELD, NC US",1957-02-28,2018-08-18,North Carolina,United States,35.23260000000001,-75.6219,3.4,12,34,"(34, 12)"
270,306,WBAN:93810,"CARBONDALE SOUTHERN ILLINOIS AIRPORT, IL US",2005-12-31,2018-08-18,Illinois,United States,37.779720000000005,-89.24972,123.7,10,24,"(24, 10)"
273,309,WBAN:03177,"CARLSBAD MCCLELLAN PALOMAR AIRPORT, CA US",2005-12-31,2018-08-18,California,United States,33.12806,-117.27944,100.0,14,4,"(4, 14)"
280,317,WBAN:03914,"CASA GRANDE MUNICIPAL AIRPORT, AZ US",2005-12-31,2018-08-18,Arizona,United States,32.95,-111.76666999999999,445.6,14,8,"(8, 14)"
281,319,WBAN:24089,"CASPER NATRONA CO AIRPORT, WY US",1939-12-31,2018-08-18,Wyoming,United States,42.89779,-106.47371000000001,1620.9,5,12,"(12, 5)"
284,322,WBAN:00465,"CATTARAUGUS CO OLEAN AIRPORT, NY US",2012-12-31,2018-08-18,New York,United States,42.24122,-78.37136,651.1,6,32,"(32, 6)"
285,323,WBAN:00283,"CAVALIER MUNICIPAL AIRPORT, ND US",2013-12-31,2018-08-18,North Dakota,United States,48.784,-97.632,272.2,0,18,"(18, 0)"
290,330,WBAN:53887,"CENTRALIA MUNICIPAL AIRPORT, IL US",2005-12-31,2018-08-18,Illinois,United States,38.514720000000004,-89.09194000000001,162.8,9,24,"(24, 9)"
291,332,WBAN:24017,"CHADRON MUNICIPAL AIRPORT, NE US",1972-12-31,2018-08-18,Nebraska,United States,42.8374,-103.0981,1004.0,5,15,"(15, 5)"
292,333,WBAN:04114,"CHALLIS AIRPORT, ID US",2001-08-31,2018-08-18,Idaho,United States,44.52278,-114.215,1534.1,4,7,"(7, 4)"
293,335,WBAN:94943,"CHAMBERLAIN MUNICIPAL AIRPORT, SD US",2005-12-31,2018-08-18,South Dakota,United States,43.76667,-99.31833,519.1,4,17,"(17, 4)"
300,344,WBAN:13880,"CHARLESTON INTL. AIRPORT, SC US",1944-12-31,2018-08-18,South Carolina,United States,32.899429999999995,-80.04075,12.2,14,31,"(31, 14)"
301,345,WBAN:13866,"CHARLESTON YEAGER AIRPORT, WV US",1956-12-31,2018-08-18,West Virginia,United States,38.3794,-81.59,277.40000000000003,9,30,"(30, 9)"
317,364,WBAN:00143,"CHEYENNE CO MUNICIPAL AIRPORT, KS US",2012-12-31,2018-08-18,Kansas,United States,39.766999999999996,-101.8,1040.3,8,15,"(15, 8)"
327,374,WBAN:93203,"CHICO ARMY FLYING SCHOOL, CA US",2005-12-31,2018-08-18,California,United States,39.8,-121.85,82.9,8,1,"(1, 8)"
330,377,WBAN:13301,"CHILLICOTHE 22 ENE, MO US",2005-06-10,2018-08-16,Missouri,United States,39.86680000000001,-93.147,253.9,8,22,"(22, 8)"
331,378,WBAN:53916,"CHILLICOTHE AGRI SCIENCE CENTER, MO US",2005-12-31,2018-08-18,Missouri,United States,39.82333,-93.57917,234.4,8,21,"(21, 8)"
332,379,WBAN:93104,"CHINA LAKE NAF, CA US",1956-12-31,2018-08-18,California,United States,35.6875,-117.6931,679.7,11,4,"(4, 11)"
345,395,WBAN:94605,"CLAYTON LAKE RAMOS, ME US",2005-12-31,2018-08-18,Maine,United States,46.61667,-69.53332999999999,304.8,2,38,"(38, 2)"
346,396,WBAN:23051,"CLAYTON MUNICIPAL AIR PARK, NM US",1956-12-31,2018-08-18,New Mexico,United States,36.4486,-103.1539,1511.8,11,14,"(14, 11)"
348,398,WBAN:92828,"CLEARWATER AIR PARK, FL US",2018-06-30,2018-08-18,Florida,United States,27.977214,-82.759057,21.6,18,29,"(29, 18)"
354,404,WBAN:14820,"CLEVELAND HOPKINS INTERNATIONAL AIRPORT, OH US",1956-12-31,2018-08-18,Ohio,United States,41.4057,-81.852,238.0,6,30,"(30, 6)"
357,407,WBAN:03027,"CLINES CORNERS, NM US",2005-12-31,2018-08-18,New Mexico,United States,35.00278,-105.66278,2159.8,12,13,"(13, 12)"
358,408,WBAN:00222,"CLINTON MEMORIAL AIRPORT, MO US",2013-12-31,2018-08-18,Missouri,United States,38.35,-93.68299999999999,251.2,9,21,"(21, 9)"
365,417,WBAN:23008,"CLOVIS CANNON AFB, NM US",1943-01-24,2018-08-18,New Mexico,United States,34.38333,-103.31667,1309.1,13,14,"(14, 13)"
368,420,WBAN:12867,"COCOA BEACH PATRICK AFB, FL US",1945-02-28,2018-08-18,Florida,United States,28.23333,-80.60000000000002,2.4,18,30,"(30, 18)"
369,421,WBAN:24045,"CODY MUNICIPAL AIRPORT, WY US",2005-12-31,2018-08-18,Wyoming,United States,44.51667,-109.01666999999999,1552.0,4,10,"(10, 4)"
370,422,WBAN:24136,"COEUR D ALENE AIR TERMINAL, ID US",2005-12-31,2018-08-18,Idaho,United States,47.76667,-116.81667,703.2,1,5,"(5, 1)"
374,426,WBAN:00276,"COLEMAN MUNICIPAL AIRPORT, TX US",2012-12-31,2018-08-18,Texas,United States,31.840999999999998,-99.404,517.2,15,17,"(17, 15)"
377,429,WBAN:53129,"COLORADO CITY MUNICIPAL AIRPORT, AZ US",2014-02-26,2018-08-18,Arizona,United States,36.959720000000004,-113.01388999999999,1485.6,10,7,"(7, 10)"
380,433,WBAN:00206,"COLUMBIA AIRPORT, CA US",2013-12-31,2018-08-18,California,United States,38.033,-120.417,646.2,9,2,"(2, 9)"
383,436,WBAN:03945,"COLUMBIA REGIONAL AIRPORT, MO US",1969-10-31,2018-08-18,Missouri,United States,38.8169,-92.2183,272.2,9,22,"(22, 9)"
385,438,WBAN:13803,"COLUMBUS BAKALAR MUNICIPAL AIRPORT, IN US",1956-12-31,2018-08-18,Indiana,United States,39.26667,-85.9,199.9,8,27,"(27, 8)"
389,442,WBAN:13812,"COLUMBUS RICKENBACKER, OH US",1942-07-31,2018-08-18,Ohio,United States,39.81667,-82.93333,226.8,8,29,"(29, 8)"
395,448,WBAN:13984,"CONCORDIA ASOS, KS US",1962-05-31,2018-08-18,Kansas,United States,39.5514,-97.6508,447.8,8,18,"(18, 8)"
397,451,WBAN:94057,"CONVERSE CO AIRPORT ASOS, WY US",2005-12-31,2018-08-18,Wyoming,United States,42.79611,-105.38028,1504.5,5,13,"(13, 5)"
400,455,WBAN:00327,"COOPERSTOWN MUNICIPAL AIRPORT, ND US",2015-09-25,2018-08-18,North Dakota,United States,47.423,-98.106,434.0,1,18,"(18, 1)"
401,456,WBAN:04141,"COOS BAY 8 SW, OR US",2008-08-18,2018-08-16,Oregon,United States,43.2718,-124.3186,3.7,5,0,"(0, 5)"
403,458,WBAN:00234,"CORNING MUNICIPAL AIRPORT, AR US",2014-07-31,2018-08-18,Arkansas,United States,36.4,-90.65,89.0,11,23,"(23, 11)"
412,468,WBAN:04908,"COUNCIL BLUFFS MUNICIPAL AIRPORT, IA US",2005-12-31,2018-08-18,Iowa,United States,41.259440000000005,-95.75972,381.9,7,20,"(20, 7)"
414,475,WBAN:94977,"CRANE LAKE, MN US",2005-12-31,2018-08-18,Minnesota,United States,48.26667,-92.48333000000001,341.1,0,22,"(22, 0)"
415,476,WBAN:24286,"CRESCENT CITY MCNAMARA AIRPORT, CA US",1972-12-31,2018-08-18,California,United States,41.78028,-124.23666999999999,17.1,6,0,"(0, 6)"
416,477,WBAN:04915,"CRESTON MUNICIPAL AIRPORT, IA US",2005-12-31,2018-08-18,Iowa,United States,41.007220000000004,-94.36306,394.4,7,21,"(21, 7)"
419,480,WBAN:03073,"CROCKETT HOUSTON CO AIRPORT, TX US",2013-12-31,2018-08-18,Texas,United States,31.30694,-95.40389,106.1,15,20,"(20, 15)"
421,482,WBAN:00287,"CROSBY MUNICIPAL AIRPORT, ND US",2012-12-31,2018-08-18,North Dakota,United States,48.928999999999995,-103.297,594.1,0,14,"(14, 0)"
423,485,WBAN:03847,"CROSSVILLE MEMORIAL AIRPORT, TN US",1972-12-31,2018-08-18,Tennessee,United States,35.95090000000001,-85.0813,569.1,11,27,"(27, 11)"
425,489,WBAN:63839,"CULLMAN FOLSOM FIELD AIRPORT, AL US",2005-12-31,2018-08-17,Alabama,United States,34.26889,-86.85833000000001,293.5,13,26,"(26, 13)"
427,491,WBAN:93798,"CULPEPER REGIONAL AIRPORT, VA US",2005-12-31,2018-08-18,Virginia,United States,38.52667,-77.85861,96.3,9,32,"(32, 9)"
428,492,WBAN:00316,"CUMBERLAND MUNICIPAL AIRPORT, WI US",2013-12-31,2018-08-18,Wisconsin,United States,45.506,-91.981,378.3,3,22,"(22, 3)"
432,496,WBAN:94032,"CUSTER CO AIRPORT, SD US",2005-12-31,2018-08-18,South Dakota,United States,43.73306,-103.61139,1690.1,4,14,"(14, 4)"
433,497,WBAN:24137,"CUT BANK AIRPORT, MT US",1942-11-30,2018-08-18,Montana,United States,48.6033,-112.3752,1169.8,0,8,"(8, 0)"
434,498,WBAN:23161,"DAGGETT AIRPORT, CA US",1948-12-31,2018-08-18,California,United States,34.8536,-116.7858,584.3000000000002,12,5,"(5, 12)"
441,506,WBAN:24219,"DALLESPORT AIRPORT, WA US",1956-12-31,2018-08-18,Oregon,United States,45.6194,-121.1661,71.60000000000002,3,2,"(2, 3)"
443,508,WBAN:54734,"DANBURY MUNICIPAL AIRPORT, CT US",2005-12-31,2018-08-18,Connecticut,United States,41.371390000000005,-73.48277999999998,139.3,6,35,"(35, 6)"
444,509,WBAN:94704,"DANSVILLE MUNICIPAL AIRPORT, NY US",1972-12-31,2018-08-18,New York,United States,42.57083,-77.71333,208.8,5,32,"(32, 5)"
449,514,WBAN:04223,"DARRINGTON 21 NNE, WA US",2003-04-02,2018-08-16,Washington,United States,48.5405,-121.446,124.1,0,2,"(2, 0)"
452,517,WBAN:23109,"DAVIS MONTHAN AFB, AZ US",1941-07-16,2018-08-18,Arizona,United States,32.16667,-110.88333,824.2,14,9,"(9, 14)"
459,524,WBAN:04871,"DE KALB TAYLOR MUNICIPAL AIRPORT, IL US",2005-12-31,2018-08-18,Illinois,United States,41.931670000000004,-88.70805999999997,278.90000000000003,6,25,"(25, 6)"
460,525,WBAN:53925,"DE QUEEN SEVIER CO AIRPORT, AR US",2003-12-31,2018-08-18,Arkansas,United States,34.05,-94.40083,108.2,13,21,"(21, 13)"
462,527,WBAN:03976,"DE RIDDER BEAUREGARD PARISH AIRPORT, LA US",2005-12-31,2018-08-18,Louisiana,United States,30.83333,-93.33333,62.2,16,21,"(21, 16)"
464,529,WBAN:53964,"DECATUR MUNICIPAL AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,33.254439999999995,-97.58056,319.1,13,18,"(18, 13)"
466,531,WBAN:04916,"DECORAH MUNICIPAL AIRPORT, IA US",2005-12-31,2018-08-18,Iowa,United States,43.27528,-91.73917,352.7,5,23,"(23, 5)"
470,535,WBAN:22001,"DEL RIO LAUGHLIN AFB, TX US",1943-02-16,2018-08-18,Texas,United States,29.366670000000003,-100.78333,329.8,17,16,"(16, 17)"
472,537,WBAN:00315,"DELAWARE MUNICIPAL JIM MOORE FIELD AIRPORT, OH US",2012-12-31,2018-08-18,Ohio,United States,40.28,-83.11500000000002,288.0,7,29,"(29, 7)"
473,539,WBAN:23162,"DELTA FAA AIRPORT, UT US",2014-08-19,2018-08-18,Utah,United States,39.38333,-112.51666999999999,1450.5,8,8,"(8, 8)"
474,540,WBAN:23078,"DEMING MUNICIPAL AIRPORT, NM US",2005-12-31,2018-08-18,New Mexico,United States,32.26222,-107.72056,1310.9,14,11,"(11, 14)"
475,541,WBAN:00445,"DEMOPOLIS MUNICIPAL AIRPORT, AL US",2014-07-30,2018-08-18,Alabama,United States,32.46383,-87.95405,34.1,14,25,"(25, 14)"
476,542,WBAN:04139,"DENIO 52 WSW, NV US",2008-06-15,2018-08-16,Nevada,United States,41.84840000000001,-119.6357,1981.2,6,3,"(3, 6)"
481,548,WBAN:14933,"DES MOINES INTERNATIONAL AIRPORT, IA US",1956-12-31,2018-08-18,Iowa,United States,41.5338,-93.65299999999999,291.7,6,21,"(21, 6)"
482,549,WBAN:03104,"DESERT RESORTS REGIONAL AIRPORT, CA US",1943-07-11,2018-08-18,California,United States,33.626670000000004,-116.15943999999999,-36.0,13,5,"(5, 13)"
483,550,WBAN:53853,"DESTIN FORT WALTON BEACH AIRPORT, FL US",2005-12-31,2018-08-18,Florida,United States,30.4,-86.47166999999999,6.7,16,26,"(26, 16)"
492,560,WBAN:24138,"DILLON AIRPORT, MT US",1956-12-31,2018-08-18,Montana,United States,45.2575,-112.5544,1585.0,3,8,"(8, 3)"
493,562,WBAN:00444,"DIXON AIRPORT, WY US",2013-12-31,2018-08-18,Wyoming,United States,41.037440000000004,-107.49252,1996.1,7,11,"(11, 7)"
494,563,WBAN:04978,"DODGE CENTER AIRPORT, MN US",2005-12-31,2018-08-18,Minnesota,United States,44.01778,-92.83139,397.8,4,22,"(22, 4)"
495,564,WBAN:13985,"DODGE CITY REGIONAL AIRPORT, KS US",1943-04-18,2018-08-18,Kansas,United States,37.7686,-99.9678,787.0,10,17,"(17, 10)"
497,567,WBAN:93026,"DOUGLAS BISBEE INL AIRPORT, AZ US",1972-12-31,2018-08-18,Arizona,Mexico,31.4583,-109.6061,1251.2,15,10,"(10, 15)"
499,569,WBAN:13707,"DOVER AFB, DE US",1942-11-30,2018-08-18,Delaware,United States,39.13333,-75.46667,8.5,8,34,"(34, 8)"
500,571,WBAN:54786,"DOYLESTOWN AIRPORT, PA US",2005-12-31,2018-08-18,Pennsylvania,United States,40.33,-75.1225,120.1,7,34,"(34, 7)"
502,574,WBAN:54844,"DRUMMOND ISLAND AIRPORT, MI US",2006-08-30,2018-08-18,Michigan,United States,46.007220000000004,-83.74278000000001,202.7,2,28,"(28, 2)"
505,577,WBAN:04787,"DUBOIS JEFFERSON CO AIRPORT, PA US",1972-12-31,2018-08-18,Pennsylvania,United States,41.17833,-78.89889000000001,552.9,7,32,"(32, 7)"
506,578,WBAN:00443,"DUBOIS MUNICIPAL AIRPORT, WY US",2013-05-13,2018-08-18,Wyoming,United States,43.54836,-109.69025,2224.1,5,10,"(10, 5)"
508,580,WBAN:24103,"DUGWAY PROVING GROUNDS, UT US",2006-01-02,2018-08-15,Utah,United States,40.18333,-112.93333,1325.6,7,8,"(8, 7)"
511,584,WBAN:03070,"DUMAS MOORE CO AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,35.858059999999995,-102.01306,1129.3,11,15,"(15, 11)"
512,585,WBAN:14747,"DUNKIRK CHAUTAUQUA CO AIRPORT, NY US",1998-12-31,2018-08-18,New York,United States,42.49333,-79.27221999999998,203.0,5,31,"(31, 5)"
513,586,WBAN:00298,"DUPONT LAPEER AIRPORT, MI US",2012-12-31,2018-08-18,Michigan,United States,43.067,-83.26700000000002,254.2,5,29,"(29, 5)"
517,592,WBAN:03809,"DYERSBURG MUNICIPAL AIRPORT, TN US",1943-04-11,2018-08-18,Tennessee,United States,36.0002,-89.4094,91.4,11,24,"(24, 11)"
518,595,WBAN:23063,"EAGLE CO AIRPORT, CO US",1956-12-31,2018-08-18,Colorado,United States,39.65,-106.91667,1980.3,8,12,"(12, 8)"
519,596,WBAN:00480,"EAGLE RANGE WEATHER SERVICE OFFICE, UT US",2014-07-30,2018-08-16,Utah,United States,41.05,-113.06,1292.0,7,7,"(7, 7)"
522,599,WBAN:00254,EAST CAMERON 278 OIL PLATFORM,2013-12-31,2018-08-18,,,28.433000000000003,-92.883,224.0,18,22,"(22, 18)"
528,606,WBAN:14991,"EAU CLAIRE REGIONAL AIRPORT, WI US",1956-12-31,2018-08-18,Wisconsin,United States,44.8665,-91.4879,269.7,3,23,"(23, 3)"
531,609,WBAN:23114,"EDWARDS AFB, CA US",1941-11-30,2018-08-18,California,United States,34.9,-117.86667,704.4,12,4,"(4, 12)"
532,610,WBAN:93816,"EFFINGHAM CO MEMORIAL AIRPORT, IL US",2005-12-31,2018-08-18,Illinois,United States,39.07028,-88.53332999999998,178.9,8,25,"(25, 8)"
534,612,WBAN:93992,"EL DORADO S AR REGIONAL AIRPORT, AR US",1972-12-31,2018-08-18,Arkansas,United States,33.22083,-92.81417,76.8,14,22,"(22, 14)"
536,614,WBAN:23044,"EL PASO INTERNATIONAL AIRPORT, TX US",1941-03-31,2018-08-18,Texas,United States,31.81111,-106.37583000000001,1194.2,15,12,"(12, 15)"
539,618,WBAN:00182,"ELBOW LAKE MUNICIPAL PRIDE OF THE PRAIRIE AIRPORT, MN US",2014-07-30,2018-08-18,Minnesota,United States,45.986,-95.992,367.3,2,20,"(20, 2)"
541,620,WBAN:13786,"ELIZABETH CITY COAST GUARD AIR STATION, NC US",1948-12-31,2018-08-18,North Carolina,United States,36.26056,-76.175,4.0,11,34,"(34, 11)"
542,621,WBAN:00210,"ELIZABETHTON MUNICIPAL AIRPORT, TN US",2014-07-30,2018-08-18,Tennessee,United States,36.367,-82.167,486.2,11,29,"(29, 11)"
546,625,WBAN:93076,"ELKHART, KS US",2005-12-31,2018-08-18,Kansas,United States,37.0,-101.88333,1105.8,10,15,"(15, 10)"
547,626,WBAN:03733,"ELKINS 21 ENE, WV US",2003-11-16,2018-08-16,West Virginia,United States,39.01300000000001,-79.4743,1033.3,8,31,"(31, 8)"
549,628,WBAN:24121,"ELKO REGIONAL AIRPORT, NV US",1956-12-31,2018-08-18,Nevada,United States,40.8288,-115.7886,1533.1,7,6,"(6, 7)"
550,629,WBAN:24220,"ELLENSBURG BOWERS FIELD, WA US",1988-01-05,2018-08-18,Washington,United States,47.03389,-120.53028,538.3,1,2,"(2, 1)"
551,630,WBAN:24006,"ELLSWORTH AFB, SD US",1939-01-31,2018-08-18,South Dakota,United States,44.15,-103.1,999.1,4,15,"(15, 4)"
552,631,WBAN:14748,"ELMIRA CORNING REGIONAL AIRPORT, NY US",1972-12-31,2018-08-18,New York,United States,42.159440000000004,-76.89193999999998,291.1,6,33,"(33, 6)"
553,632,WBAN:23154,"ELY AIRPORT, NV US",1956-12-31,2018-08-18,Nevada,United States,39.2952,-114.8466,1908.7,8,6,"(6, 8)"
556,635,WBAN:13989,"EMPORIA ASOS, KS US",1972-12-31,2018-08-18,Kansas,United States,38.3291,-96.1946,364.5,9,19,"(19, 9)"
559,638,WBAN:53986,"ENID WOODRING AIRPORT, OK US",2005-12-31,2018-08-18,Oklahoma,United States,36.38333,-97.8,355.7,11,18,"(18, 11)"
560,639,WBAN:24141,"EPHRATA MUNICIPAL AIRPORT, WA US",1941-12-31,2018-08-18,Washington,United States,47.3078,-119.5154,381.6,1,3,"(3, 1)"
564,643,WBAN:94853,"ESCANABA DELTA CO AIRPORT, MI US",2005-12-31,2018-08-18,Michigan,United States,45.73333,-87.08332999999998,181.1,3,26,"(26, 3)"
565,644,WBAN:94971,"ESTHERVILLE MUNICIPAL AIRPORT, IA US",2005-12-31,2018-08-18,Iowa,United States,43.40111,-94.74722,401.4,5,20,"(20, 5)"
567,646,WBAN:00304,EUGENE ISLAND OIL PLATFORM,2012-12-31,2018-08-18,,,28.633000000000006,-91.48299999999999,28.0,18,23,"(23, 18)"
568,647,WBAN:24221,"EUGENE MAHLON SWEET FIELD, OR US",1956-12-31,2018-08-18,Oregon,United States,44.1278,-123.2206,107.6,4,0,"(0, 4)"
570,649,WBAN:03170,"EUREKA AIRPORT, NV US",2005-12-31,2018-08-18,Nevada,United States,39.6013,-116.0055,1809.3,8,5,"(5, 8)"
571,650,WBAN:24213,"EUREKA WEATHER FORECAST OFFICE WOODLEY ISLAND, CA US",2005-12-31,2018-08-17,California,United States,40.8097,-124.1602,6.1000000000000005,7,0,"(0, 7)"
572,651,WBAN:04111,"EVANSTON UINTA CO BURNS FIELD, WY US",1972-12-31,2018-08-18,Wyoming,United States,41.27306,-111.03056000000001,2183.3,7,9,"(9, 7)"
577,656,WBAN:24114,"FAIRCHILD AFB, WA US",1940-03-31,2018-08-18,Washington,United States,47.63333,-117.65,750.1,1,4,"(4, 1)"
578,657,WBAN:00220,"FAIRFIELD CO AIRPORT, SC US",2013-12-31,2018-08-18,South Carolina,United States,34.315000000000005,-81.10900000000002,176.20000000000005,13,30,"(30, 13)"
579,658,WBAN:04925,"FAIRFIELD MUNICIPAL AIRPORT, IA US",2005-12-31,2018-08-18,Iowa,United States,41.05306,-91.97889,243.5,7,22,"(22, 7)"
582,662,WBAN:94056,"FAITH MUNICIPAL AIRPORT, SD US",2005-12-31,2018-08-18,South Dakota,United States,45.031940000000006,-102.01916999999999,786.4,3,15,"(15, 3)"
583,663,WBAN:00270,"FAITH RANCH AIRPORT, TX US",2014-01-06,2018-08-18,Texas,United States,28.209,-100.01899999999999,236.2,18,17,"(17, 18)"
584,665,WBAN:93102,"FALLON NAAS, NV US",1956-12-31,2018-08-18,Nevada,United States,39.41667,-118.71667,1199.1,8,3,"(3, 8)"
585,666,WBAN:94957,"FALLS CITY BRENNER FIELD, NE US",1999-12-31,2018-08-18,Nebraska,United States,40.08028,-95.59194000000001,298.7,8,20,"(20, 8)"
589,670,WBAN:94969,"FARIBAULT MUNICIPAL AIRPORT, MN US",2005-12-31,2018-08-18,Minnesota,United States,44.33333,-93.31667,323.1,4,21,"(21, 4)"
591,672,WBAN:23090,"FARMINGTON FOUR CORNERS REGIONAL AIRPORT, NM US",1956-12-31,2018-08-18,New Mexico,United States,36.74361,-108.22917,1674.9,10,11,"(11, 10)"
592,673,WBAN:93996,"FARMINGTON REGIONAL AIRPORT, MO US",1995-02-09,2018-08-18,Missouri,United States,37.76083,-90.42833,288.6,10,23,"(23, 10)"
593,674,WBAN:03707,"FARMVILLE REGIONAL AIRPORT, VA US",2005-12-31,2018-08-18,Virginia,United States,37.3575,-78.43777999999998,127.1,10,32,"(32, 10)"
598,679,WBAN:53922,"FAYETTEVILLE SPRINGDALE NW AR REGL AIRPORT, AR US",2005-12-31,2018-08-18,Arkansas,United States,36.28333,-94.3,392.3,11,21,"(21, 11)"
599,680,WBAN:13762,"FENTRESS NAVAL AUXILIARY FIELD, VA US",2007-05-31,2018-08-18,Virginia,United States,36.695,-76.13556,4.9,10,34,"(34, 10)"
600,681,WBAN:94966,"FERGUS FALLS AIRPORT, MN US",2005-12-31,2018-08-18,Minnesota,United States,46.28333,-96.15,360.6,2,19,"(19, 2)"
601,682,WBAN:00326,"FERNANDINA BEACH MUNICIPAL AIRPORT, FL US",2013-12-31,2018-08-18,Florida,United States,30.616999999999997,-81.467,5.2,16,30,"(30, 16)"
602,683,WBAN:00237,"FIELD OF DREAMS AIRPORT, MN US",2014-07-30,2018-08-18,Minnesota,United States,46.023,-92.895,311.2,2,22,"(22, 2)"
603,684,WBAN:14825,"FINDLAY AIRPORT, OH US",1972-12-31,2018-08-18,Ohio,United States,41.01361,-83.66861,243.8,7,28,"(28, 7)"
604,685,WBAN:04780,"FITCHBURG MUNICIPAL AIRPORT, MA US",1956-12-31,2018-08-18,Massachusetts,United States,42.55194,-71.75583,106.1,5,37,"(37, 5)"
607,688,WBAN:00485,"FLAGLER CO AIRPORT, FL US",2012-12-31,2018-08-17,Florida,United States,29.46738,-81.20633000000001,10.1,17,30,"(30, 17)"
612,693,WBAN:53889,"FLORA MUNICIPAL AIRPORT, IL US",2005-12-31,2018-08-18,Illinois,United States,38.66472,-88.45277999999998,143.9,9,25,"(25, 9)"
617,698,WBAN:13829,"FORT BENNING LAWSON FIELD, AL US",1939-04-30,2018-08-18,Alabama,United States,32.35,-85.0,70.7,14,27,"(27, 14)"
620,701,WBAN:00449,"FORT BRIDGER AIRPORT, WY US",2013-07-31,2018-08-18,Wyoming,United States,41.39333,-110.40597,2145.5,6,9,"(9, 6)"
621,702,WBAN:13806,"FORT CAMPBELL ARMY AIR FIELD, KY US",1943-07-14,2018-08-18,Kentucky,United States,36.66667,-87.48333000000001,174.70000000000005,11,26,"(26, 11)"
622,703,WBAN:94015,"FORT CARSON BUTTS ARMY AIR FIELD, CO US",1966-09-14,2018-08-18,Colorado,United States,38.67833,-104.75667,1779.4,9,13,"(13, 9)"
624,705,WBAN:94933,"FORT DODGE OZARK AIRLINES, IA US",2005-12-31,2018-08-18,Iowa,United States,42.55,-94.18333,352.3,5,21,"(21, 5)"
628,709,WBAN:03124,"FORT HUACHUCA SIERRA VISTA MUNICIPAL AIRPORT, AZ US",1954-10-10,2018-08-18,Arizona,United States,31.58833,-110.34416999999999,1438.4,15,9,"(9, 15)"
631,712,WBAN:00162,"FORT MORGAN MUNICIPAL AIRPORT, CO US",2013-12-31,2018-08-18,Colorado,United States,40.333,-103.8,1393.2,7,14,"(14, 7)"
632,713,WBAN:63847,"FORT PAYNE ISBELL FIELD, AL US",2005-12-31,2018-08-18,Alabama,United States,34.473890000000004,-85.72139,267.3,12,27,"(27, 12)"
633,714,WBAN:12895,"FORT PIERCE ST LUCIE CO INTERNATIONAL AIRPORT, FL US",2005-12-31,2018-08-17,Florida,United States,27.49806,-80.37666999999998,7.3,19,31,"(31, 19)"
635,716,WBAN:53988,"FORT POLK FULLERTON LANDING STRIP, LA US",2005-12-31,2018-08-18,Louisiana,United States,31.021700000000006,-92.9107,94.5,15,22,"(22, 15)"
636,718,WBAN:13947,"FORT RILEY MARSHALL ARMY AIR FIELD, KS US",1938-08-16,2018-08-18,Kansas,United States,39.05,-96.76667,324.6,8,19,"(19, 8)"
637,720,WBAN:53861,"FORT RUCKER LOWE ARMY HELIPORT, AL US",2008-07-16,2018-08-18,Alabama,United States,31.35583,-85.75111,74.4,15,27,"(27, 15)"
639,722,WBAN:13964,"FORT SMITH REGIONAL AIRPORT, AR US",1946-12-31,2018-08-18,Arkansas,United States,35.333,-94.3625,136.9,12,21,"(21, 12)"
640,723,WBAN:03875,"FORT STEWART WRIGHT, GA US",2006-01-02,2018-08-18,Georgia,United States,31.88333,-81.56667,13.7,15,30,"(30, 15)"
641,724,WBAN:23091,"FORT STOCKTON PECOS CO AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,30.91194,-102.91667,917.4,16,15,"(15, 16)"
642,725,WBAN:14827,"FORT WAYNE INTERNATIONAL AIRPORT, IN US",1941-10-31,2018-08-18,Indiana,United States,40.9705,-85.2063,241.1,7,27,"(27, 7)"
646,729,WBAN:04929,"FOSSTON MUNICIPAL AIRPORT, MN US",2005-12-31,2018-08-18,Minnesota,United States,47.59278,-95.77528000000001,389.2,1,20,"(20, 1)"
647,731,WBAN:53841,"FRANKFORT CAPITAL CITY AIRPORT, KY US",2005-12-31,2018-08-18,Kentucky,United States,38.18472,-84.90333000000001,245.1,9,27,"(27, 9)"
648,732,WBAN:54818,"FRANKFORT DOW MEMORIAL FIELD AIRPORT, MI US",2005-12-31,2018-08-18,Michigan,United States,44.62556,-86.20083000000001,192.6,4,26,"(26, 4)"
649,733,WBAN:00152,"FRANKLIN CO STATE AIRPORT, VT US",2008-03-31,2018-08-18,Vermont,United States,44.933,-73.10000000000002,70.10000000000001,3,36,"(36, 3)"
651,735,WBAN:94868,"FRANKLIN, PA US",1967-12-31,2018-08-18,Pennsylvania,United States,41.38333,-79.86667,469.4,6,31,"(31, 6)"
653,737,WBAN:03981,"FREDERICK MUNICIPAL AIRPORT, OK US",2005-12-31,2018-08-18,Oklahoma,United States,34.344440000000006,-98.98306,382.5,13,17,"(17, 13)"
654,738,WBAN:93947,"FREDERICKSBURG GILLESPIE CO AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,30.24333,-98.90972,516.6,16,17,"(17, 16)"
655,739,WBAN:03706,"FREDERICKSBURG SHANNON AIRPORT, VA US",2005-12-31,2018-08-18,Virginia,United States,38.26667,-77.44917,25.9,9,33,"(33, 9)"
656,740,WBAN:04876,"FREEPORT ALBERTUS AIRPORT, IL US",2005-12-31,2018-08-18,Illinois,United States,42.246109999999994,-89.58221999999998,261.8,6,24,"(24, 6)"
658,742,WBAN:04924,"FREMONT MUNICIPAL AIRPORT, NE US",2005-12-31,2018-08-18,Nebraska,United States,41.448890000000006,-96.52,366.7,6,19,"(19, 6)"
659,743,WBAN:04836,"FRENCHVILLE NORTHERN AROOSTOOK AIRPORT, ME US",2005-12-31,2018-08-18,Maine,United States,47.28556,-68.31333000000001,301.1,1,39,"(39, 1)"
660,744,WBAN:93193,"FRESNO YOSEMITE INTERNATIONAL, CA US",1941-12-03,2018-08-18,California,United States,36.78,-119.7194,101.5,10,3,"(3, 10)"
661,745,WBAN:94276,"FRIDAY HARBOR AIRPORT, WA US",2005-12-31,2018-08-18,Washington,United States,48.522220000000004,-123.02306000000002,33.2,0,0,"(0, 0)"
662,746,WBAN:00450,"FRONT RANGE AIRPORT, CO US",2013-12-31,2018-08-18,Colorado,United States,39.7842,-104.5376,1680.4,8,13,"(13, 8)"
663,747,WBAN:54772,"FRYEBURG EASTERN SLOPES REGL AIRPORT, ME US",2005-12-31,2018-08-18,Maine,United States,43.99056,-70.9475,135.6,4,37,"(37, 4)"
665,749,WBAN:00265,"FULTON CO AIRPORT, IN US",2013-12-31,2018-08-18,Indiana,United States,41.066,-86.182,241.1,7,26,"(26, 7)"
667,752,WBAN:03896,"GADSDEN MUNICIPAL AIRPORT, AL US",2005-12-31,2018-08-18,Alabama,United States,33.96667,-86.08332999999998,173.4,13,27,"(27, 13)"
668,753,WBAN:13975,"GAGE AIRPORT, OK US",1956-12-31,2018-08-18,Oklahoma,United States,36.2967,-99.7689,667.8000000000002,11,17,"(17, 11)"
669,754,WBAN:03056,"GAINES CO AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,32.67528,-102.65444000000001,1010.4,14,15,"(15, 14)"
673,759,WBAN:93764,"GAITHERSBURG MONTGOMERY CO AIR PARK, MD US",2013-12-31,2018-08-18,Maryland,United States,39.16667,-77.16667,164.3,8,33,"(33, 8)"
674,760,WBAN:94959,"GALESBURG MUNICIPAL AIRPORT, IL US",2005-12-31,2018-08-18,Illinois,United States,40.93333,-90.43333,232.9,7,23,"(23, 7)"
675,761,WBAN:12993,"GALLIANO SOUTH LAFOURCHE AIRPORT, LA US",2005-12-31,2018-08-18,Louisiana,United States,29.44472,-90.26111,0.3,17,24,"(24, 17)"
676,762,WBAN:23081,"GALLUP MUNICIPAL AIRPORT, NM US",1972-12-31,2018-08-18,New Mexico,United States,35.5144,-108.794,1972.4,12,10,"(10, 12)"
678,765,WBAN:23064,"GARDEN CITY REGIONAL AIRPORT, KS US",1943-01-31,2018-08-18,Kansas,United States,37.92722,-100.72471999999999,878.4,9,16,"(16, 9)"
680,767,WBAN:94041,"GARRISON, ND US",2005-12-31,2018-08-18,North Dakota,United States,47.64583,-101.43944,582.2,1,16,"(16, 1)"
681,768,WBAN:04807,"GARY, IN US",2005-12-31,2018-08-18,Indiana,United States,41.61667,-87.41667,180.1,6,26,"(26, 6)"
682,769,WBAN:53870,"GASTONIA MUNICIPAL AIRPORT, NC US",2005-12-31,2018-08-18,North Carolina,United States,35.196670000000005,-81.15583000000001,242.9,12,30,"(30, 12)"
684,772,WBAN:04854,"GAYLORD OTSEGO CO AIRPORT, MI US",1999-08-31,2018-08-18,Michigan,United States,45.01333,-84.70138999999998,406.9,3,28,"(28, 3)"
687,776,WBAN:00391,"GEORGETOWN CO AIRPORT, SC US",2013-12-31,2018-08-18,South Carolina,United States,33.317,-79.31700000000002,12.2,13,31,"(31, 13)"
689,778,WBAN:13764,"GEORGETOWN SUSSEX CO AIRPORT, DE US",2005-12-31,2018-08-18,Delaware,United States,38.689170000000004,-75.35916999999998,15.5,9,34,"(34, 9)"
693,784,WBAN:53982,"GILMER MUNICIPAL AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,32.698890000000006,-94.94889,126.5,14,20,"(20, 14)"
694,785,WBAN:94008,"GLASGOW INTERNATIONAL AIRPORT, MT US",1942-12-09,2018-08-18,Montana,United States,48.2138,-106.6214,696.5,0,12,"(12, 0)"
695,786,WBAN:00361,"GLASGOW MUNICIPAL AIRPORT, KY US",2012-12-31,2018-08-18,Kentucky,United States,37.033,-85.95,218.2,10,27,"(27, 10)"
697,788,WBAN:53126,"GLENDALE MUNICIPAL AIRPORT, AZ US",2005-12-31,2018-08-18,Arizona,United States,33.52722,-112.295,324.9000000000001,13,8,"(8, 13)"
698,789,WBAN:24087,"GLENDIVE DAWSON COMMUNITY AIRPORT, MT US",2005-12-31,2018-08-18,Montana,United States,47.13333,-104.8,748.9,1,13,"(13, 1)"
699,790,WBAN:14750,"GLENS FALLS AIRPORT, NY US",1972-12-31,2018-08-18,New York,United States,43.33845,-73.61028,97.8,5,35,"(35, 5)"
701,793,WBAN:00135,"GNOSS FIELD AIRPORT, CA US",2014-07-30,2018-08-18,California,United States,38.15,-122.55,1.2,9,1,"(1, 9)"
702,794,WBAN:53893,"GOLDEN TRIANGLE, MS US",2005-12-31,2018-08-18,Mississippi,United States,33.45,-88.58332999999998,80.5,13,25,"(25, 13)"
704,796,WBAN:03708,"GOLDSBORO WAYNE MUNICIPAL AIRPORT, NC US",2005-12-31,2018-08-18,North Carolina,United States,35.46028,-77.96472,40.8,12,32,"(32, 12)"
705,797,WBAN:23065,"GOODLAND RENNER FIELD, KS US",1956-12-31,2018-08-18,Kansas,United States,39.36722,-101.69333,1114.3,8,16,"(16, 8)"
706,798,WBAN:04994,"GOODRIDGE 12 NNW, MN US",2003-08-19,2018-08-16,Minnesota,United States,48.3055,-95.8744,350.5,0,20,"(20, 0)"
708,800,WBAN:14829,"GOSHEN MUNICIPAL AIRPORT, IN US",1998-12-31,2018-08-18,Indiana,United States,41.5333,-85.78330000000003,253.0,6,27,"(27, 6)"
710,802,WBAN:53977,"GRANBURY MUNICIPAL AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,32.44444,-97.81694,237.1,14,18,"(18, 14)"
711,803,WBAN:03195,"GRAND CANYON NATIONAL PARK AIRPORT, AZ US",2005-12-31,2018-08-18,Arizona,United States,35.94611,-112.15472,2013.5,11,8,"(8, 11)"
713,805,WBAN:14916,"GRAND FORKS INTERNATIONAL AIRPORT, ND US",1956-12-31,2018-08-18,North Dakota,United States,47.94280000000001,-97.1839,256.6,1,19,"(19, 1)"
715,810,WBAN:23066,"GRAND JUNCTION WALKER FIELD, CO US",1956-12-31,2018-08-18,Colorado,United States,39.1342,-108.54,1480.7,8,11,"(11, 8)"
717,812,WBAN:94992,"GRAND MARAIS, MN US",2005-12-31,2018-08-18,Minnesota,United States,47.74722,-90.34444,185.9,1,24,"(24, 1)"
720,815,WBAN:94919,"GRAND RAPIDS ITASCA CO AIRPORT, MN US",2005-12-31,2018-08-18,Minnesota,United States,47.21111,-93.50972,413.0,1,21,"(21, 1)"
721,816,WBAN:04999,"GRANITE FALLS MUNICIPAL AIRPORT LENZEN ROE MEMORIAL FIELD, MN US",2005-12-31,2018-08-18,Minnesota,United States,44.75333,-95.55611,319.1,3,20,"(20, 3)"
722,818,WBAN:00481,"GRANITE PEAK FILLMORE AIRPORT, UT US",2014-07-29,2018-08-17,Utah,United States,38.95813,-112.36313,1519.4,9,8,"(8, 9)"
723,819,WBAN:00387,"GRANT CO REGIONAL AIRPORT OGILVIE FIELD, OR US",2013-12-31,2018-08-18,Oregon,United States,44.4,-118.96700000000001,1127.2,4,3,"(3, 4)"
724,821,WBAN:93057,"GRANTS MILAN MUNICIPAL AIRPORT, NM US",1947-12-31,2018-08-18,New Mexico,United States,35.16528,-107.90222,1987.3,12,11,"(11, 12)"
725,822,WBAN:24201,"GRAY ARMY AIR FIELD, WA US",1960-05-31,2018-08-18,Washington,United States,47.08333,-122.58333,91.4,1,1,"(1, 1)"
727,824,WBAN:53967,"GRAYSON CO AIRPORT SHERMAN DENISON, TX US",2005-12-31,2018-08-18,Texas,United States,33.71417,-96.67361,228.3,13,19,"(19, 13)"
729,826,WBAN:24143,"GREAT FALLS AIRPORT, MT US",1956-12-31,2018-08-18,Montana,United States,47.4733,-111.3822,1116.8,1,9,"(9, 1)"
730,827,WBAN:04880,"GREATER KANKAKEE AIRPORT, IL US",2005-12-31,2018-08-18,Illinois,United States,41.121390000000005,-87.84611,191.7,7,25,"(25, 7)"
731,828,WBAN:24051,"GREELEY WELD CO AIRPORT, CO US",2005-12-31,2018-08-18,Colorado,United States,40.43556,-104.63194,1431.6,7,13,"(13, 7)"
732,829,WBAN:14898,"GREEN BAY A S INTERNATIONAL AIRPORT, WI US",1949-12-31,2018-08-18,Wisconsin,United States,44.47940000000001,-88.1366,209.4,4,25,"(25, 4)"
733,832,WBAN:13723,"GREENSBORO AIRPORT, NC US",1945-10-31,2018-08-18,North Carolina,United States,36.09690000000001,-79.9432,271.3,11,31,"(31, 11)"
735,834,WBAN:13939,"GREENVILLE ASOS, MS US",1942-01-19,2018-08-18,Mississippi,United States,33.4825,-90.98528,39.0,13,23,"(23, 13)"
738,837,WBAN:63874,"GREENVILLE MAC CRENSHAW MEMORIAL AIRPORT, AL US",2006-08-31,2018-08-18,Alabama,United States,31.84556,-86.61082999999998,137.5,15,26,"(26, 15)"
739,838,WBAN:94626,"GREENVILLE MAINE FORESTRY SERVICE, ME US",2005-12-31,2018-08-18,Maine,United States,45.46222,-69.59528,316.1,3,38,"(38, 3)"
740,839,WBAN:13926,"GREENVILLE MUNICIPAL AIRPORT MAJORS FIELD, TX US",2005-12-31,2018-08-18,Texas,United States,33.06778,-96.06528,163.1,14,19,"(19, 14)"
742,841,WBAN:53874,"GREENWOOD CO AIRPORT, SC US",2005-12-31,2018-08-18,South Carolina,United States,34.24861,-82.15916999999999,192.3,13,29,"(29, 13)"
743,842,WBAN:13978,"GREENWOOD LEFLORE AIRPORT, MS US",1943-02-04,2018-08-18,Mississippi,United States,33.496300000000005,-90.0866,40.5,13,24,"(24, 13)"
744,843,WBAN:24048,"GREYBULL SOUTH BIG HORN CO AIRPORT, WY US",2005-12-31,2018-08-18,Wyoming,United States,44.516940000000005,-108.08221999999999,1198.8,4,11,"(11, 4)"
745,844,WBAN:00339,"GRIFFIN SPALDING CO AIRPORT, GA US",2012-12-31,2018-08-18,Georgia,United States,33.227000000000004,-84.275,292.3,14,28,"(28, 14)"
746,845,WBAN:14976,"GRINNELL, IA US",2006-08-30,2018-08-18,Iowa,United States,41.71667,-92.7,307.2,6,22,"(22, 6)"
747,846,WBAN:03870,"GRNVL SPART INTERNATIONAL AIRPORT, SC US",1962-10-14,2018-08-18,South Carolina,United States,34.8842,-82.2209,287.4000000000001,12,29,"(29, 12)"
748,847,WBAN:54819,"GROSSE ILE MUNICIPAL AIRPORT, MI US",2005-12-31,2018-08-18,Michigan,United States,42.09861,-83.16111,178.9,6,29,"(29, 6)"
750,849,WBAN:53941,"GROVE MUNICIPAL AIRPORT, OK US",2005-12-31,2018-08-18,Oklahoma,United States,36.605,-94.73833,253.9,11,20,"(20, 11)"
752,851,WBAN:93874,"GULFPORT BILOXI AIRPORT, MS US",2004-12-31,2018-08-18,Mississippi,United States,30.411900000000006,-89.08080000000002,12.8,16,24,"(24, 16)"
754,854,WBAN:53913,"GUTHRIE MUNICIPAL AIRPORT, OK US",2005-12-31,2018-08-18,Oklahoma,United States,35.8517,-97.4142,325.5,11,19,"(19, 11)"
755,855,WBAN:03030,"GUYMON MUNICIPAL AIRPORT, OK US",2005-12-31,2018-08-18,Oklahoma,United States,36.681670000000004,-101.50528,951.9,11,16,"(16, 11)"
756,856,WBAN:94836,"GWINN K I SAWYER AFB, MI US",2005-12-31,2018-08-18,Michigan,United States,46.35,-87.4,372.2,2,26,"(26, 2)"
757,857,WBAN:00150,"GWINNER ROGER MELROE FIELD AIRPORT, ND US",2014-06-30,2018-08-18,North Dakota,United States,46.217,-97.633,386.2,2,18,"(18, 2)"
758,858,WBAN:00221,"H A CLARK MEMORIAL FIELD AIRPORT, AZ US",2013-12-31,2018-08-18,Arizona,United States,35.30000000000001,-112.2,2035.1,12,8,"(8, 12)"
759,859,WBAN:00186,"H L SONNY CALLAHAN AIRPORT, AL US",2013-12-31,2018-08-18,Alabama,United States,30.46,-87.87700000000002,28.0,16,25,"(25, 16)"
760,861,WBAN:93706,"HAGERSTOWN WASHINGTON CO REGIONAL AIRPORT, MD US",2005-12-31,2018-08-18,Maryland,United States,39.70778,-77.72972,212.8,8,32,"(32, 8)"
761,862,WBAN:94161,"HAILEY FRIEDMAN MEMORIAL AIRPORT, ID US",2005-12-31,2018-08-18,Idaho,United States,43.5,-114.3,1617.3,5,7,"(7, 5)"
763,864,WBAN:00231,"HALIFAX NORTHAMPTON REGIONAL AIRPORT, NC US",2013-12-31,2018-08-18,North Carolina,United States,36.33,-77.635,44.2,11,33,"(33, 11)"
764,865,WBAN:53938,"HALLIBURTON FIELD AIRPORT, OK US",2005-12-31,2018-08-18,Oklahoma,United States,34.47083,-97.95083000000001,339.2,12,18,"(18, 12)"
766,867,WBAN:53855,"HAMILTON BUTLER CO REGIONAL AIRPORT, OH US",2005-12-31,2018-08-18,Ohio,United States,39.36444,-84.52472,193.2,8,28,"(28, 8)"
767,868,WBAN:00357,"HAMILTON MUNICIPAL AIRPORT, TX US",2013-12-31,2018-08-18,Texas,United States,31.666,-98.149,396.2,15,18,"(18, 15)"
768,869,WBAN:03908,"HAMMOND MUNICIPAL AIRPORT, LA US",2005-12-31,2018-08-18,Louisiana,United States,30.52083,-90.4175,13.4,16,23,"(23, 16)"
769,870,WBAN:00154,"HAMPTON ROADS EXECUTIVE AIRPORT, VA US",2012-12-31,2018-08-18,Virginia,United States,36.783,-76.45,7.0,10,33,"(33, 10)"
770,871,WBAN:14858,"HANCOCK HOUGHTON CO AIRPORT, MI US",1956-12-31,2018-08-18,Michigan,United States,47.16861,-88.48889,333.8,1,25,"(25, 1)"
771,872,WBAN:53119,"HANFORD MUNICIPAL AIRPORT, CA US",2005-12-31,2018-08-18,California,United States,36.31889,-119.62888999999998,75.9,11,3,"(3, 11)"
772,874,WBAN:23170,"HANKSVILLE AIRPORT, UT US",1972-12-31,2018-08-18,Utah,United States,38.41667,-110.7,1355.1,9,9,"(9, 9)"
773,875,WBAN:00455,"HANNIBAL REGIONAL AIRPORT, MO US",2013-12-31,2018-08-18,Missouri,United States,39.72516,-91.44386,234.7,8,23,"(23, 8)"
774,876,WBAN:04884,"HARBOR SPRINGS AIRPORT, MI US",2005-12-31,2018-08-18,Michigan,United States,45.42556,-84.91333,206.3,3,27,"(27, 3)"
775,877,WBAN:04936,"HARLAN MUNICIPAL AIRPORT, IA US",2005-12-31,2018-08-18,Iowa,United States,41.58417,-95.33944,375.2,6,20,"(20, 6)"
777,879,WBAN:00159,"HARRIET ALEXANDER FIELD AIRPORT, CO US",2013-12-31,2018-08-18,Colorado,United States,38.533,-106.05,2294.2000000000007,9,12,"(12, 9)"
778,880,WBAN:14751,"HARRISBURG CAPITAL CITY AIRPORT, PA US",1956-12-31,2018-08-18,Pennsylvania,United States,40.217220000000005,-76.85139000000001,103.6,7,33,"(33, 7)"
780,883,WBAN:13971,"HARRISON BOONE CO AIRPORT, AR US",1946-07-31,2018-08-18,Arkansas,United States,36.2668,-93.1566,418.8,11,22,"(22, 11)"
781,884,WBAN:00431,"HARRISON CO AIRPORT, TX US",2012-12-31,2018-08-18,Texas,United States,32.5205,-94.3077,108.8,14,21,"(21, 14)"
783,886,WBAN:14752,"HARTFORD BRAINARD FIELD, CT US",1973-12-31,2018-08-18,Connecticut,United States,41.73611,-72.65056,5.8,6,36,"(36, 6)"
784,887,WBAN:00219,"HARTSVILLE REGIONAL AIRPORT, SC US",2012-12-31,2018-08-18,South Carolina,United States,34.4,-80.117,111.3,12,31,"(31, 12)"
785,888,WBAN:00322,"HARVEY MUNICIPAL AIRPORT, ND US",2014-07-30,2018-08-18,North Dakota,United States,47.783,-99.93299999999999,489.2,1,17,"(17, 1)"
787,890,WBAN:13833,"HATTIESBURG CHAIN MUNICIPAL AIRPORT, MS US",1942-08-19,2018-08-18,Mississippi,United States,31.281940000000002,-89.25305999999998,46.0,15,24,"(24, 15)"
789,892,WBAN:94012,"HAVRE AIRPORT ASOS, MT US",1961-01-31,2018-08-18,Montana,United States,48.5428,-109.7633,787.9,0,10,"(10, 0)"
790,893,WBAN:03167,"HAWTHORNE MUNICIPAL AIRPORT, CA US",2005-12-31,2018-08-18,California,United States,33.92278,-118.33417,19.2,13,4,"(4, 13)"
791,894,WBAN:94025,"HAYDEN YAMPA VALLEY AIRPORT, CO US",2005-12-31,2018-08-18,Colorado,United States,40.48111,-107.2175,2011.7,7,12,"(12, 7)"
792,895,WBAN:03968,"HAYS MUNICIPAL AIRPORT, KS US",2005-12-31,2018-08-18,Kansas,United States,38.85,-99.26667,609.0,9,17,"(17, 9)"
793,896,WBAN:93228,"HAYWARD AIR TERMINAL, CA US",1999-12-31,2018-08-18,California,United States,37.6542,-122.115,13.1,10,1,"(1, 10)"
794,897,WBAN:94973,"HAYWARD MUNICIPAL AIRPORT, WI US",2005-12-31,2018-08-18,Wisconsin,United States,46.02611,-91.44417,367.0,2,23,"(23, 2)"
796,899,WBAN:53973,"HEARNE MUNICIPAL AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,30.871940000000002,-96.62222,86.9,16,19,"(19, 16)"
797,900,WBAN:00337,"HEART OF GEORGIA REGIONAL AIRPORT, GA US",2012-12-31,2018-08-18,Georgia,United States,32.214,-83.12799999999999,93.3,14,29,"(29, 14)"
798,903,WBAN:04998,"HEBRON MUNICIPAL AIRPORT, NE US",2005-12-31,2018-08-18,Nebraska,United States,40.14917,-97.58667,449.0,7,18,"(18, 7)"
799,904,WBAN:24144,"HELENA AIRPORT ASOS, MT US",1956-12-31,2018-08-18,Montana,United States,46.6056,-111.9636,1166.8,2,8,"(8, 2)"
800,905,WBAN:53886,"HENDERSON CITY CO AIRPORT, KY US",2005-12-31,2018-08-18,Kentucky,United States,37.8,-87.68333,118.0,10,25,"(25, 10)"
801,906,WBAN:03711,"HENDERSON OXFORD AIRPORT, NC US",2005-12-31,2018-08-18,North Carolina,United States,36.36139,-78.52888999999998,160.6,11,32,"(32, 11)"
802,907,WBAN:00250,"HENRY TIFT MYERS AIRPORT, GA US",2012-12-31,2018-08-18,Georgia,United States,31.429,-83.48899999999999,108.2,15,28,"(28, 15)"
803,908,WBAN:00129,"HEREFORD MUNICIPAL AIRPORT, TX US",2013-12-31,2018-08-18,Texas,United States,34.85,-102.333,1153.1,12,15,"(15, 12)"
804,909,WBAN:04113,"HERMISTON MUNICIPAL AIRPORT, OR US",2005-12-31,2018-08-18,Oregon,United States,45.82583,-119.26111000000002,195.4,3,3,"(3, 3)"
805,910,WBAN:94038,"HETTINGER MUNICIPAL AIRPORT, ND US",2005-12-31,2018-08-18,North Dakota,United States,46.01389,-102.65472,824.5,2,15,"(15, 2)"
806,911,WBAN:94931,"HIBBING CHISHOLM HIBBING AIRPORT, MN US",1971-12-31,2018-08-18,Minnesota,United States,47.386390000000006,-92.83889,412.1,1,22,"(22, 1)"
807,912,WBAN:03810,"HICKORY FAA AIRPORT, NC US",1972-12-31,2018-08-18,North Carolina,United States,35.74207,-81.38229,358.1,11,30,"(30, 11)"
808,913,WBAN:00306,HIGH ISLAND 179 OIL PLATFORM,2012-12-31,2018-08-18,,,29.183000000000003,-94.517,75.3,17,21,"(21, 17)"
809,914,WBAN:00260,HIGH ISLAND 376,2013-12-31,2018-08-18,,,27.962,-93.671,0.3,18,21,"(21, 18)"
810,916,WBAN:93990,"HILL CITY MUNICIPAL AIRPORT, KS US",1972-12-31,2018-08-18,Kansas,United States,39.37556,-99.82972,666.9,8,17,"(17, 8)"
811,917,WBAN:53972,"HILLSBORO MUNICIPAL AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,32.08361,-97.09722,208.8,15,19,"(19, 15)"
813,919,WBAN:63837,"HILTON HEAD ISLAND AIRPORT, SC US",2005-12-31,2018-08-18,South Carolina,United States,32.21667,-80.7,7.3,14,30,"(30, 14)"
814,920,WBAN:93986,"HOBART MUNICIPAL AIRPORT, OK US",1972-12-31,2018-08-18,Oklahoma,United States,34.9894,-99.0525,474.3,12,17,"(17, 12)"
815,921,WBAN:93034,"HOBBS LEA CO AIRPORT, NM US",1942-10-31,2018-08-18,New Mexico,United States,32.6933,-103.2125,1114.0,14,14,"(14, 14)"
816,923,WBAN:04935,"HOLDREGE BREWSTER FIELD AIRPORT, NE US",2005-12-31,2018-08-18,Nebraska,United States,40.45,-99.33917,702.3000000000002,7,17,"(17, 7)"
818,925,WBAN:00392,"HOLLISTER MUNICIPAL AIRPORT, CA US",1945-02-28,2018-08-18,California,United States,36.9,-121.417,72.2,10,2,"(2, 10)"
819,926,WBAN:23002,"HOLLOMAN AFB, NM US",2006-01-02,2018-08-18,New Mexico,United States,32.85,-106.1,1267.4,14,12,"(12, 14)"
820,927,WBAN:23803,"HOLLY SPRINGS 4 N, MS US",2008-01-31,2018-08-16,Mississippi,United States,34.8223,-89.43480000000002,147.5,12,24,"(24, 12)"
821,928,WBAN:00163,"HOLYOKE AIRPORT, CO US",2013-12-31,2018-08-18,Colorado,United States,40.567,-102.267,1137.2,7,15,"(15, 7)"
822,929,WBAN:00128,"HOMERVILLE AIRPORT, GA US",2012-12-31,2018-08-18,Georgia,United States,31.055999999999997,-82.76700000000002,57.3,15,29,"(29, 15)"
823,930,WBAN:12962,"HONDO MUNICIPAL AIRPORT, TX US",1942-09-14,2018-08-18,Texas,United States,29.360100000000006,-99.1742,280.40000000000003,17,17,"(17, 17)"
824,931,WBAN:00429,"HOPKINS FIELD AIRPORT, CO US",2012-12-31,2018-08-18,Colorado,United States,38.23875,-108.56326999999999,1810.5,9,11,"(11, 9)"
825,932,WBAN:94225,"HOQUIAM BOWERMAN AIRPORT, WA US",1956-12-31,2018-08-18,Washington,United States,46.9727,-123.9302,3.7,2,0,"(0, 2)"
826,933,WBAN:00225,"HORSESHOE BAY RESORT AIRPORT, TX US",2012-12-31,2018-08-18,Texas,United States,30.533,-98.367,333.1,16,18,"(18, 16)"
827,934,WBAN:03962,"HOT SPRINGS ASOS, AR US",2005-12-31,2018-08-18,Arkansas,United States,34.29,-93.06,163.1,13,22,"(22, 13)"
828,935,WBAN:93757,"HOT SPRINGS INGALLS FIELD, VA US",2005-12-31,2018-08-18,Virginia,United States,37.95,-79.81667,1156.1,9,31,"(31, 9)"
830,937,WBAN:14609,"HOULTON AIRPORT, ME US",1999-12-31,2018-08-18,Maine,United States,46.1185,-67.7928,145.1,2,39,"(39, 2)"
831,938,WBAN:12927,"HOUMA TERREBONNE AIRPORT, LA US",2005-12-31,2018-08-18,Louisiana,United States,29.566390000000002,-90.66028,4.0,17,23,"(23, 17)"
840,948,WBAN:12918,"HOUSTON WILLIAM P HOBBY AIRPORT, TX US",1946-07-27,2018-08-18,Texas,United States,29.63806,-95.28194,13.4,17,20,"(20, 17)"
841,949,WBAN:04887,"HOWELL LIVINGSTON CO AIRPORT, MI US",2005-12-31,2018-08-18,Michigan,United States,42.62944,-83.98416999999998,287.7,5,28,"(28, 5)"
842,950,WBAN:00484,"HULETT MUNICIPAL AIRPORT, WY US",2014-07-30,2018-08-18,Wyoming,United States,44.66286,-104.56783,1300.0,4,13,"(13, 4)"
843,951,WBAN:53896,"HUNTINGBURG AIRPORT, IN US",2005-12-31,2018-08-18,Indiana,United States,38.24889,-86.95361,161.20000000000005,9,26,"(26, 9)"
844,952,WBAN:03860,"HUNTINGTON TRI STATE AIRPORT, WV US",1961-11-30,2018-08-18,West Virginia,United States,38.365,-82.555,251.2,9,29,"(29, 9)"
846,954,WBAN:63804,"HUNTSVILLE MADISON CO EXECUTIVE AIRPORT, AL US",2005-12-31,2018-08-18,Alabama,United States,34.86139,-86.55722,230.1,12,26,"(26, 12)"
847,955,WBAN:53903,"HUNTSVILLE MUNICIPAL AIRPORT, TX US",2005-12-31,2018-08-18,Texas,United States,30.743890000000004,-95.58611,111.6,16,20,"(20, 16)"
848,956,WBAN:14936,"HURON REGIONAL AIRPORT, SD US",1956-12-31,2018-08-18,South Dakota,United States,44.3981,-98.2231,390.1,4,18,"(18, 4)"
849,957,WBAN:13986,"HUTCHINSON MUNICIPAL AIRPORT, KS US",1945-01-31,2018-08-18,Kansas,United States,38.06528,-97.86056,470.3,9,18,"(18, 9)"
850,958,WBAN:04933,"HUTCHINSON MUNICIPAL BUTLER FIELD AIRPORT, MN US",2005-12-31,2018-08-18,Minnesota,United States,44.85889,-94.38167,323.1,3,21,"(21, 3)"
851,959,WBAN:00291,"HUTSON FIELD AIRPORT, ND US",2013-12-31,2018-08-18,North Dakota,United States,48.405,-97.371,251.2,0,19,"(19, 0)"
852,960,WBAN:94720,"HYANNIS BARNSTABLE MUNICIPAL AIRPORT, MA US",2005-12-31,2018-08-18,Massachusetts,United States,41.66861,-70.28,16.8,6,38,"(38, 6)"
853,961,WBAN:53990,"IDABEL MCCURTAIN CO REGIONAL AIRPORT, OK US",2005-12-31,2018-08-18,Oklahoma,United States,33.909440000000004,-94.85944,143.9,13,20,"(20, 13)"
854,962,WBAN:00452,"IDAHO CO AIRPORT, ID US",2013-12-31,2018-08-18,Idaho,United States,45.94255,-116.12341,1010.1,2,5,"(5, 2)"
855,963,WBAN:24145,"IDAHO FALLS FANNING FIELD, ID US",1956-12-31,2018-08-18,Idaho,United States,43.51639,-112.06722,1441.4,5,8,"(8, 5)"
857,965,WBAN:93115,"IMPERIAL BEACH REAM FIELD NAS, CA US",1956-12-31,2018-08-18,California,United States,32.56667,-117.11667,7.3,14,5,"(5, 14)"
858,966,WBAN:03144,"IMPERIAL CO AIRPORT, CA US",2005-12-31,2018-08-18,California,United States,32.83417,-115.57861000000001,-17.7,14,6,"(6, 14)"
859,967,WBAN:24091,"IMPERIAL MUNICIPAL AIRPORT, NE US",1973-03-31,2018-08-18,Nebraska,United States,40.51,-101.62,996.1,7,16,"(16, 7)"
861,969,WBAN:00141,"INDEPENDENCE MUNICIPAL AIRPORT, KS US",1944-01-31,2018-08-18,Kansas,United States,37.158,-95.77799999999999,251.2,10,20,"(20, 10)"
862,971,WBAN:23141,"INDIAN SPRINGS, NV US",1963-09-02,2018-08-18,Nevada,United States,36.58333,-115.68333,951.9,11,6,"(6, 11)"
863,972,WBAN:64706,"INDIANA J STEWART, PA US",2005-12-31,2018-08-18,Pennsylvania,United States,40.63333,-79.10000000000002,428.2,7,31,"(31, 7)"
866,975,WBAN:93819,"INDIANAPOLIS INTERNATIONAL AIRPORT, IN US",1942-10-05,2018-08-18,Indiana,United States,39.72517,-86.28168000000001,241.1,8,26,"(26, 8)"
867,977,WBAN:14918,"INTERNATIONAL FALLS INTERNATIONAL AIRPORT, MN US",1956-12-31,2018-08-18,Minnesota,United States,48.5614,-93.3981,360.6,0,21,"(21, 0)"
868,978,WBAN:00377,"INVERNESS AIRPORT, FL US",2012-12-31,2018-08-18,Florida,United States,28.816999999999997,-82.31700000000002,15.2,17,29,"(29, 17)"
869,980,WBAN:00240,"IONIA CO AIRPORT, MI US",2014-07-30,2018-08-18,Michigan,United States,42.938,-85.061,249.0,5,27,"(27, 5)"
870,981,WBAN:14937,"IOWA CITY MUNICIPAL AIRPORT, IA US",1997-01-22,2018-08-18,Iowa,United States,41.63278,-91.54306,198.1,6,23,"(23, 6)"
871,982,WBAN:54941,"IOWA FALLS MUNICIPAL AIRPORT, IA US",2013-06-20,2018-08-18,Iowa,United States,42.47138,-93.20707,346.6,5,22,"(22, 5)"
873,984,WBAN:94926,"IRONWOOD, MI US",2005-12-31,2018-08-18,Michigan,United States,46.53333,-90.13333,374.9,2,24,"(24, 2)"
874,985,WBAN:04997,"ISEDOR IVERSON AIRPORT, MN US",2005-12-31,2018-08-18,Minnesota,United States,46.61889,-93.30972,374.3,2,21,"(21, 2)"
875,986,WBAN:04781,"ISLIP LI MACARTHUR AIRPORT, NY US",1972-12-31,2018-08-18,New York,United States,40.7939,-73.10170000000002,25.6,7,36,"(36, 7)"
876,988,WBAN:94761,"ITHACA TOMPKINS CNTY, NY US",2005-12-31,2018-08-18,New York,United States,42.48333,-76.46667,335.0,5,33,"(33, 5)"
877,989,WBAN:00464,"J DOUGLAS BAKE MEMORIAL AIRPORT, WI US",2014-07-30,2018-08-18,Wisconsin,United States,44.87405,-87.90977,184.4,3,25,"(25, 3)"
878,990,WBAN:00216,"JACK BARSTOW AIRPORT, MI US",2013-12-31,2018-08-18,Michigan,United States,43.663,-84.26100000000002,194.2,4,28,"(28, 4)"
879,991,WBAN:00394,"JACKSON CO AIRPORT, GA US",2013-12-31,2018-08-17,Georgia,United States,34.147,-83.561,290.2,13,28,"(28, 13)"
881,993,WBAN:24166,"JACKSON HOLE AIRPORT, WY US",2005-12-31,2018-08-17,Wyoming,United States,43.6,-110.73333000000001,1956.5,4,9,"(9, 4)"
882,994,WBAN:03940,"JACKSON INTERNATIONAL AIRPORT, MS US",1942-08-31,2018-08-18,Mississippi,United States,32.3205,-90.0777,100.6,14,24,"(24, 14)"
883,995,WBAN:03889,"JACKSON JULIAN CARROLL AIRPORT, KY US",1973-01-01,2018-08-18,Kentucky,United States,37.591390000000004,-83.31443999999998,416.1,10,29,"(29, 10)"
884,996,WBAN:03811,"JACKSON MCKELLAR SIPES AIRPORT, TN US",1972-12-31,2018-08-18,Tennessee,United States,35.593,-88.9167,132.0,11,25,"(25, 11)"
885,997,WBAN:04946,"JACKSON MUNICIPAL AIRPORT, MN US",2005-12-31,2018-08-18,Minnesota,United States,43.65,-94.98639,440.7,4,20,"(20, 4)"
886,998,WBAN:14833,"JACKSON REYNOLDS FIELD, MI US",1972-12-31,2018-08-18,Michigan,United States,42.2667,-84.4667,304.2,6,28,"(28, 6)"
887,999,WBAN:93753,"JACKSONVILLE ALBERT ELLIS AIRPORT, NC US",2005-12-31,2018-08-18,North Carolina,United States,34.83333,-77.61667,29.3,12,33,"(33, 12)"
1 index STATION_ID STATION BEGIN_DATE END_DATE STATE COUNTRY LATITUDE LONGITUDE ELEVATION LAT_SCALED LON_SCALED TUPLES
2 0 0 WBAN:00184 ABBEVILLE CHRIS CRUSTA MEMORIAL AIRPORT, LA US 2013-12-31 2018-08-18 Louisiana United States 29.976000000000006 -92.084 15.2 16 22 (22, 16)
3 2 3 WBAN:14929 ABERDEEN REGIONAL AIRPORT, SD US 1964-06-30 2018-08-18 South Dakota United States 45.4433 -98.413 395.3 3 18 (18, 3)
4 4 5 WBAN:13962 ABILENE REGIONAL AIRPORT, TX US 1946-07-31 2018-08-18 Texas United States 32.4105 -99.6822 545.6 14 17 (17, 14)
5 10 11 WBAN:94975 AINSWORTH MUNICIPAL AIRPORT, NE US 2005-12-31 2018-08-18 Nebraska United States 42.57694 -100.00056 787.6 5 17 (17, 5)
6 13 16 WBAN:14813 AKRON FULTON INTERNATIONAL AIRPORT, OH US 1998-12-31 2018-08-18 Ohio United States 41.0375 -81.46417 318.2 7 30 (30, 7)
7 15 18 WBAN:53864 ALABASTER SHELBY CO AIRPORT, AL US 2001-12-31 2018-08-18 Alabama United States 33.178329999999995 -86.78166999999998 172.20000000000005 14 26 (26, 14)
8 17 21 WBAN:23061 ALAMOSA SAN LUIS VALLEY REGIONAL AIRPORT, CO US 1956-12-31 2018-08-18 Colorado United States 37.4389 -105.8613 2296.1 10 13 (13, 10)
9 22 26 WBAN:54921 ALBION MUNICIPAL AIRPORT, NE US 2005-12-31 2018-08-18 Nebraska United States 41.73 -98.05444 548.3000000000002 6 18 (18, 6)
10 26 30 WBAN:00258 ALEXANDER MUNICIPAL AIRPORT, NM US 2014-07-30 2018-08-18 New Mexico United States 34.645 -106.834 1583.1 12 12 (12, 12)
11 33 38 WBAN:24044 ALLIANCE MUNICIPAL AIRPORT ASOS, NE US 2005-12-31 2018-08-18 Nebraska United States 42.05730000000001 -102.8017 1197.6 6 15 (15, 6)
12 37 42 WBAN:03049 ALPINE CASPARIS MUNICIPAL AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 30.38333 -103.68333 1375.6 16 14 (14, 16)
13 40 45 WBAN:94299 ALTURAS MUNICIPAL AIRPORT, CA US 2005-12-31 2018-08-18 California United States 41.49139 -120.56444 1333.5 6 2 (2, 6)
14 42 47 WBAN:53933 ALVA REGIONAL AIRPORT, OK US 2005-12-31 2018-08-18 Oklahoma United States 36.77306 -98.66972 449.3 10 18 (18, 10)
15 43 49 WBAN:23047 AMARILLO AIRPORT, TX US 1943-02-28 2018-08-18 Texas United States 35.2295 -101.7042 1098.5 12 16 (16, 12)
16 50 56 WBAN:63811 ANDREWS MURPHY AIRPORT, NC US 2005-12-31 2018-08-18 North Carolina United States 35.195 -83.86528 516.9 12 28 (28, 12)
17 51 57 WBAN:00137 ANGEL FIRE AIRPORT, NM US 2013-12-31 2018-08-18 New Mexico United States 36.422 -105.29 2554.2000000000007 11 13 (13, 11)
18 58 64 WBAN:04864 ANTIGO LANGLADE CO AIRPORT, WI US 2005-12-31 2018-08-18 Wisconsin United States 45.15417 -89.11055999999998 463.9 3 24 (24, 3)
19 59 65 WBAN:12832 APALACHICOLA AIRPORT, FL US 1944-12-31 2018-08-18 Florida United States 29.73333 -85.03332999999998 5.8 17 27 (27, 17)
20 82 91 WBAN:93730 ATLANTIC CITY INTERNATIONAL AIRPORT, NJ US 1946-12-31 2018-08-18 New Jersey United States 39.452020000000005 -74.56698999999998 18.3 8 35 (35, 8)
21 84 94 WBAN:53932 ATOKA MUNICIPAL AIRPORT, OK US 2005-12-31 2018-08-18 Oklahoma United States 34.39833 -96.14806 179.8 12 19 (19, 12)
22 91 102 WBAN:14605 AUGUSTA STATE AIRPORT, ME US 1972-12-31 2018-08-18 Maine United States 44.3155 -69.7972 107.0 4 38 (38, 4)
23 94 105 WBAN:94281 AURORA STATE AIRPORT, OR US 2005-12-31 2018-08-18 Oregon United States 45.24861 -122.76861000000001 59.7 3 1 (1, 3)
24 102 114 WBAN:54817 BAD AXE HURON CO MEMORIAL AIRPORT, MI US 2005-12-31 2018-08-18 Michigan United States 43.78028 -82.98555999999998 233.5 4 29 (29, 4)
25 104 116 WBAN:53138 BAKER 5 W, NV US 2004-05-08 2018-08-17 Nevada United States 39.0118 -114.209 2016.9 8 7 (7, 8)
26 105 117 WBAN:24130 BAKER CITY AIRPORT, OR US 1956-12-31 2018-08-18 Oregon United States 44.8428 -117.8086 1024.4 3 4 (4, 3)
27 107 119 WBAN:23155 BAKERSFIELD AIRPORT, CA US 1941-09-30 2018-08-18 California United States 35.43440000000001 -119.0542 149.0 12 3 (3, 12)
28 111 124 WBAN:14606 BANGOR INTERNATIONAL AIRPORT, ME US 1956-12-31 2018-08-18 Maine United States 44.7978 -68.8185 45.1 3 39 (39, 3)
29 112 125 WBAN:14616 BAR HARBOR AIRPORT, ME US 2005-12-31 2018-08-18 Maine United States 44.45 -68.36667 26.8 4 39 (39, 4)
30 113 126 WBAN:54833 BARABOO WISCONSIN DELLS AIRPORT, WI US 2005-12-31 2018-08-18 Wisconsin United States 43.52194 -89.77360999999998 297.5 5 24 (24, 5)
31 124 137 WBAN:24119 BATTTLE MOUNTAIN 4 SE, NV US 1972-12-31 2018-08-18 Nevada United States 40.6118 -116.8917 1373.1 7 5 (5, 7)
32 129 142 WBAN:00282 BEACH AIRPORT, ND US 2014-08-18 2018-08-18 North Dakota United States 46.925 -103.98200000000001 840.0 2 14 (14, 2)
33 131 144 WBAN:94947 BEATRICE MUNICIPAL AIRPORT, NE US 2005-12-31 2018-08-18 Nebraska United States 40.301390000000005 -96.75389 403.6 7 19 (19, 7)
34 140 155 WBAN:00127 BEEVILLE MUNICIPAL AIRPORT, TX US 2013-12-31 2018-08-18 Texas United States 28.35 -97.71700000000001 82.3 18 18 (18, 18)
35 148 163 WBAN:00224 BEND MUNICIPAL AIRPORT, OR US 2012-12-31 2018-08-18 Oregon United States 44.095 -121.2 1055.2 4 2 (2, 4)
36 149 165 WBAN:54781 BENNINGTON MORSE STATE AIRPORT, VT US 2005-12-31 2018-08-18 Vermont United States 42.89139 -73.24694000000001 251.8 5 36 (36, 5)
37 163 179 WBAN:03044 BIG SPRING MCMAHON WRINKLE AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 32.2125 -101.52139 784.3000000000002 14 16 (16, 14)
38 164 180 WBAN:24033 BILLINGS INTERNATIONAL AIRPORT, MT US 1935-04-30 2018-08-18 Montana United States 45.8069 -108.5422 1091.5 3 11 (11, 3)
39 166 182 WBAN:04725 BINGHAMTON GREATER AP, NY US 1956-12-31 2018-08-18 New York United States 42.2068 -75.98 486.2 6 34 (34, 6)
40 168 185 WBAN:23157 BISHOP AIRPORT, CA US 1943-01-15 2018-08-18 California United States 37.3711 -118.35799999999999 1250.3 10 4 (4, 10)
41 169 186 WBAN:24011 BISMARCK MUNICIPAL AIRPORT, ND US 1936-06-30 2018-08-18 North Dakota United States 46.7825 -100.7572 503.2 2 16 (16, 2)
42 171 188 WBAN:00286 BLACK RIVER FALLS AREA AIRPORT, WI US 2013-12-31 2018-08-17 Wisconsin United States 44.25100000000001 -90.855 255.1 4 23 (23, 4)
43 172 189 WBAN:53881 BLACKSBURG VIRGINIA TECH AIRPORT, VA US 2005-12-31 2018-08-18 Virginia United States 37.2075 -80.40778 649.8000000000002 10 31 (31, 10)
44 175 195 WBAN:03036 BLANDING MUNICIPAL AIRPORT, UT US 2014-07-23 2018-08-18 Utah United States 37.58278 -109.48306000000001 1787.7 10 10 (10, 10)
45 176 196 WBAN:94793 BLOCK ISLAND STATE AIRPORT, RI US 1989-12-31 2018-08-18 Rhode Island United States 41.16806 -71.57777999999998 32.0 7 37 (37, 7)
46 179 199 WBAN:23225 BLUE CANYON AIRPORT, CA US 1956-12-31 2018-08-18 California United States 39.2774 -120.7102 1608.1 8 2 (2, 8)
47 181 201 WBAN:03859 BLUEFIELD MERCER CO AIRPORT, WV US 1999-12-31 2018-08-18 West Virginia United States 37.2978 -81.20366 870.5 10 30 (30, 10)
48 182 203 WBAN:23158 BLYTHE ASOS, CA US 1942-06-12 2018-08-18 California United States 33.6186 -114.7142 120.4 13 6 (6, 13)
49 185 207 WBAN:00263 BOERNE STAGE FIELD AIRPORT, TX US 2014-07-30 2018-08-18 Texas United States 29.724 -98.695 422.1 17 18 (18, 17)
50 186 208 WBAN:24131 BOISE AIR TERMINAL, ID US 1930-12-31 2018-08-18 Idaho United States 43.5666 -116.2405 857.7 5 5 (5, 5)
51 187 209 WBAN:63871 BONIFAY TRI CO AIRPORT, FL US 2006-08-31 2018-08-18 Florida United States 30.84583 -85.60139000000001 25.9 16 27 (27, 16)
52 193 215 WBAN:14739 BOSTON, MA US 1943-11-20 2018-08-18 Massachusetts United States 42.36060000000001 -71.00970000000002 3.7 6 37 (37, 6)
53 196 219 WBAN:00310 BOUNDARY CO AIRPORT, ID US 2013-12-31 2018-08-18 Idaho United States 48.726000000000006 -116.295 711.1 0 5 (5, 0)
54 198 223 WBAN:93808 BOWLING GREEN WARREN CO AIRPORT, KY US 1972-12-31 2018-08-18 Kentucky United States 36.9647 -86.4238 160.9 10 26 (26, 10)
55 199 224 WBAN:00353 BOYSEN THERMOPOL, WY US 2012-12-31 2018-08-18 Wyoming United States 43.467 -108.389 2225.0 5 11 (11, 5)
56 200 225 WBAN:24132 BOZEMAN GALLATIN FIELD AIRPORT, MT US 1972-12-31 2018-08-18 Montana United States 45.788 -111.1608 1349.3 3 9 (9, 3)
57 205 230 WBAN:00451 BRANSON WEST MUNICIPAL EMERSON FIELD AIRPORT, MO US 2014-07-30 2018-08-18 Missouri United States 36.6985 -93.4022 411.2 10 21 (21, 10)
58 207 232 WBAN:00435 BRAZOS 451 OILP 2013-07-16 2018-08-18 28.5 -95.716 34.1 18 20 (20, 18)
59 211 237 WBAN:00433 BRIDGEPORT SONORA JUNCTION, CA US 2013-01-09 2018-08-18 California United States 38.3557 -119.51899999999999 2057.1 9 3 (3, 9)
60 213 239 WBAN:24180 BRIGHAM CITY AIRPORT, UT US 2014-07-23 2018-08-18 Utah United States 41.55222 -112.06222 1288.1 6 8 (8, 6)
61 215 241 WBAN:94946 BROKEN BOW MUNICIPAL AIRPORT, NE US 2005-12-31 2018-08-18 Nebraska United States 41.43333 -99.63333 771.1 6 17 (17, 6)
62 218 245 WBAN:94902 BROOKINGS, SD US 2005-12-31 2018-08-18 South Dakota United States 44.3 -96.8 502.3 4 19 (19, 4)
63 222 250 WBAN:03721 BRUNSWICK CO AIRPORT, NC US 2005-12-31 2018-08-18 North Carolina United States 33.92917 -78.07472 7.6 13 32 (32, 13)
64 225 254 WBAN:23159 BRYCE CANYON AIRPORT, UT US 1956-12-31 2018-08-18 Utah United States 37.70639 -112.14556 2312.2000000000007 10 8 (8, 10)
65 228 259 WBAN:94037 BUFFALO ASOS, SD US 1998-12-31 2018-08-18 South Dakota United States 45.604440000000004 -103.54639 915.6 3 14 (14, 3)
66 229 260 WBAN:94054 BUFFALO JOHNSON CO AIRPORT, WY US 2005-12-31 2018-08-18 Wyoming United States 44.38139 -106.72111000000001 1513.9 4 12 (12, 4)
67 232 263 WBAN:03068 BULLSEYE AUXILIARY AIRFIELD USAFA, CO US 2006-04-30 2018-08-18 Colorado United States 38.76667 -104.3 1837.9 9 14 (14, 9)
68 238 269 WBAN:04866 BURLINGTON MUNICIPAL AIRPORT, WI US 2005-12-31 2018-08-18 Wisconsin United States 42.69 -88.30360999999998 237.4 5 25 (25, 5)
69 239 270 WBAN:94282 BURLINGTON SKAGIT REGIONAL BAYVIEW AIRPORT, WA US 2005-12-31 2018-08-18 Washington United States 48.46667 -122.41667 42.7 0 1 (1, 0)
70 240 271 WBAN:14742 BURLINGTON WEATHER SERVICE OFFICE AIRPORT, VT US 1947-12-31 2018-08-18 Vermont United States 44.4683 -73.1499 100.6 4 36 (36, 4)
71 246 277 WBAN:14817 CADILLAC WEXFORD CO AIRPORT, MI US 1990-07-23 2018-08-18 Michigan United States 44.28333 -85.41667 397.8 4 27 (27, 4)
72 250 281 WBAN:54743 CALDWELL ESSEX CO AIRPORT, NJ US 2005-12-31 2018-08-18 New Jersey United States 40.87639 -74.28305999999998 52.7 7 35 (35, 7)
73 251 282 WBAN:94195 CALDWELL INDUSTRIAL AIRPORT, ID US 2005-12-31 2018-08-18 Idaho United States 43.65 -116.63333 740.4 4 5 (5, 4)
74 254 285 WBAN:12986 CALHOUN CO AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 28.65417 -96.68139000000001 9.1 17 19 (19, 17)
75 255 287 WBAN:23136 CAMARILLO AIRPORT, CA US 1956-12-31 2018-08-18 California United States 34.21667 -119.08333 23.5 13 3 (3, 13)
76 265 300 WBAN:54923 CANBY MYERS FIELD AIRPORT, MN US 2006-10-17 2018-08-18 Minnesota United States 44.729440000000004 -96.26611 363.6 3 19 (19, 3)
77 266 301 WBAN:00285 CANDO MUNICIPAL AIRPORT, ND US 2013-12-31 2018-08-18 North Dakota United States 48.48 -99.236 450.2 0 17 (17, 0)
78 269 305 WBAN:93729 CAPE HATTERAS BILLY MITCHELL FIELD, NC US 1957-02-28 2018-08-18 North Carolina United States 35.23260000000001 -75.6219 3.4 12 34 (34, 12)
79 270 306 WBAN:93810 CARBONDALE SOUTHERN ILLINOIS AIRPORT, IL US 2005-12-31 2018-08-18 Illinois United States 37.779720000000005 -89.24972 123.7 10 24 (24, 10)
80 273 309 WBAN:03177 CARLSBAD MCCLELLAN PALOMAR AIRPORT, CA US 2005-12-31 2018-08-18 California United States 33.12806 -117.27944 100.0 14 4 (4, 14)
81 280 317 WBAN:03914 CASA GRANDE MUNICIPAL AIRPORT, AZ US 2005-12-31 2018-08-18 Arizona United States 32.95 -111.76666999999999 445.6 14 8 (8, 14)
82 281 319 WBAN:24089 CASPER NATRONA CO AIRPORT, WY US 1939-12-31 2018-08-18 Wyoming United States 42.89779 -106.47371000000001 1620.9 5 12 (12, 5)
83 284 322 WBAN:00465 CATTARAUGUS CO OLEAN AIRPORT, NY US 2012-12-31 2018-08-18 New York United States 42.24122 -78.37136 651.1 6 32 (32, 6)
84 285 323 WBAN:00283 CAVALIER MUNICIPAL AIRPORT, ND US 2013-12-31 2018-08-18 North Dakota United States 48.784 -97.632 272.2 0 18 (18, 0)
85 290 330 WBAN:53887 CENTRALIA MUNICIPAL AIRPORT, IL US 2005-12-31 2018-08-18 Illinois United States 38.514720000000004 -89.09194000000001 162.8 9 24 (24, 9)
86 291 332 WBAN:24017 CHADRON MUNICIPAL AIRPORT, NE US 1972-12-31 2018-08-18 Nebraska United States 42.8374 -103.0981 1004.0 5 15 (15, 5)
87 292 333 WBAN:04114 CHALLIS AIRPORT, ID US 2001-08-31 2018-08-18 Idaho United States 44.52278 -114.215 1534.1 4 7 (7, 4)
88 293 335 WBAN:94943 CHAMBERLAIN MUNICIPAL AIRPORT, SD US 2005-12-31 2018-08-18 South Dakota United States 43.76667 -99.31833 519.1 4 17 (17, 4)
89 300 344 WBAN:13880 CHARLESTON INTL. AIRPORT, SC US 1944-12-31 2018-08-18 South Carolina United States 32.899429999999995 -80.04075 12.2 14 31 (31, 14)
90 301 345 WBAN:13866 CHARLESTON YEAGER AIRPORT, WV US 1956-12-31 2018-08-18 West Virginia United States 38.3794 -81.59 277.40000000000003 9 30 (30, 9)
91 317 364 WBAN:00143 CHEYENNE CO MUNICIPAL AIRPORT, KS US 2012-12-31 2018-08-18 Kansas United States 39.766999999999996 -101.8 1040.3 8 15 (15, 8)
92 327 374 WBAN:93203 CHICO ARMY FLYING SCHOOL, CA US 2005-12-31 2018-08-18 California United States 39.8 -121.85 82.9 8 1 (1, 8)
93 330 377 WBAN:13301 CHILLICOTHE 22 ENE, MO US 2005-06-10 2018-08-16 Missouri United States 39.86680000000001 -93.147 253.9 8 22 (22, 8)
94 331 378 WBAN:53916 CHILLICOTHE AGRI SCIENCE CENTER, MO US 2005-12-31 2018-08-18 Missouri United States 39.82333 -93.57917 234.4 8 21 (21, 8)
95 332 379 WBAN:93104 CHINA LAKE NAF, CA US 1956-12-31 2018-08-18 California United States 35.6875 -117.6931 679.7 11 4 (4, 11)
96 345 395 WBAN:94605 CLAYTON LAKE RAMOS, ME US 2005-12-31 2018-08-18 Maine United States 46.61667 -69.53332999999999 304.8 2 38 (38, 2)
97 346 396 WBAN:23051 CLAYTON MUNICIPAL AIR PARK, NM US 1956-12-31 2018-08-18 New Mexico United States 36.4486 -103.1539 1511.8 11 14 (14, 11)
98 348 398 WBAN:92828 CLEARWATER AIR PARK, FL US 2018-06-30 2018-08-18 Florida United States 27.977214 -82.759057 21.6 18 29 (29, 18)
99 354 404 WBAN:14820 CLEVELAND HOPKINS INTERNATIONAL AIRPORT, OH US 1956-12-31 2018-08-18 Ohio United States 41.4057 -81.852 238.0 6 30 (30, 6)
100 357 407 WBAN:03027 CLINES CORNERS, NM US 2005-12-31 2018-08-18 New Mexico United States 35.00278 -105.66278 2159.8 12 13 (13, 12)
101 358 408 WBAN:00222 CLINTON MEMORIAL AIRPORT, MO US 2013-12-31 2018-08-18 Missouri United States 38.35 -93.68299999999999 251.2 9 21 (21, 9)
102 365 417 WBAN:23008 CLOVIS CANNON AFB, NM US 1943-01-24 2018-08-18 New Mexico United States 34.38333 -103.31667 1309.1 13 14 (14, 13)
103 368 420 WBAN:12867 COCOA BEACH PATRICK AFB, FL US 1945-02-28 2018-08-18 Florida United States 28.23333 -80.60000000000002 2.4 18 30 (30, 18)
104 369 421 WBAN:24045 CODY MUNICIPAL AIRPORT, WY US 2005-12-31 2018-08-18 Wyoming United States 44.51667 -109.01666999999999 1552.0 4 10 (10, 4)
105 370 422 WBAN:24136 COEUR D ALENE AIR TERMINAL, ID US 2005-12-31 2018-08-18 Idaho United States 47.76667 -116.81667 703.2 1 5 (5, 1)
106 374 426 WBAN:00276 COLEMAN MUNICIPAL AIRPORT, TX US 2012-12-31 2018-08-18 Texas United States 31.840999999999998 -99.404 517.2 15 17 (17, 15)
107 377 429 WBAN:53129 COLORADO CITY MUNICIPAL AIRPORT, AZ US 2014-02-26 2018-08-18 Arizona United States 36.959720000000004 -113.01388999999999 1485.6 10 7 (7, 10)
108 380 433 WBAN:00206 COLUMBIA AIRPORT, CA US 2013-12-31 2018-08-18 California United States 38.033 -120.417 646.2 9 2 (2, 9)
109 383 436 WBAN:03945 COLUMBIA REGIONAL AIRPORT, MO US 1969-10-31 2018-08-18 Missouri United States 38.8169 -92.2183 272.2 9 22 (22, 9)
110 385 438 WBAN:13803 COLUMBUS BAKALAR MUNICIPAL AIRPORT, IN US 1956-12-31 2018-08-18 Indiana United States 39.26667 -85.9 199.9 8 27 (27, 8)
111 389 442 WBAN:13812 COLUMBUS RICKENBACKER, OH US 1942-07-31 2018-08-18 Ohio United States 39.81667 -82.93333 226.8 8 29 (29, 8)
112 395 448 WBAN:13984 CONCORDIA ASOS, KS US 1962-05-31 2018-08-18 Kansas United States 39.5514 -97.6508 447.8 8 18 (18, 8)
113 397 451 WBAN:94057 CONVERSE CO AIRPORT ASOS, WY US 2005-12-31 2018-08-18 Wyoming United States 42.79611 -105.38028 1504.5 5 13 (13, 5)
114 400 455 WBAN:00327 COOPERSTOWN MUNICIPAL AIRPORT, ND US 2015-09-25 2018-08-18 North Dakota United States 47.423 -98.106 434.0 1 18 (18, 1)
115 401 456 WBAN:04141 COOS BAY 8 SW, OR US 2008-08-18 2018-08-16 Oregon United States 43.2718 -124.3186 3.7 5 0 (0, 5)
116 403 458 WBAN:00234 CORNING MUNICIPAL AIRPORT, AR US 2014-07-31 2018-08-18 Arkansas United States 36.4 -90.65 89.0 11 23 (23, 11)
117 412 468 WBAN:04908 COUNCIL BLUFFS MUNICIPAL AIRPORT, IA US 2005-12-31 2018-08-18 Iowa United States 41.259440000000005 -95.75972 381.9 7 20 (20, 7)
118 414 475 WBAN:94977 CRANE LAKE, MN US 2005-12-31 2018-08-18 Minnesota United States 48.26667 -92.48333000000001 341.1 0 22 (22, 0)
119 415 476 WBAN:24286 CRESCENT CITY MCNAMARA AIRPORT, CA US 1972-12-31 2018-08-18 California United States 41.78028 -124.23666999999999 17.1 6 0 (0, 6)
120 416 477 WBAN:04915 CRESTON MUNICIPAL AIRPORT, IA US 2005-12-31 2018-08-18 Iowa United States 41.007220000000004 -94.36306 394.4 7 21 (21, 7)
121 419 480 WBAN:03073 CROCKETT HOUSTON CO AIRPORT, TX US 2013-12-31 2018-08-18 Texas United States 31.30694 -95.40389 106.1 15 20 (20, 15)
122 421 482 WBAN:00287 CROSBY MUNICIPAL AIRPORT, ND US 2012-12-31 2018-08-18 North Dakota United States 48.928999999999995 -103.297 594.1 0 14 (14, 0)
123 423 485 WBAN:03847 CROSSVILLE MEMORIAL AIRPORT, TN US 1972-12-31 2018-08-18 Tennessee United States 35.95090000000001 -85.0813 569.1 11 27 (27, 11)
124 425 489 WBAN:63839 CULLMAN FOLSOM FIELD AIRPORT, AL US 2005-12-31 2018-08-17 Alabama United States 34.26889 -86.85833000000001 293.5 13 26 (26, 13)
125 427 491 WBAN:93798 CULPEPER REGIONAL AIRPORT, VA US 2005-12-31 2018-08-18 Virginia United States 38.52667 -77.85861 96.3 9 32 (32, 9)
126 428 492 WBAN:00316 CUMBERLAND MUNICIPAL AIRPORT, WI US 2013-12-31 2018-08-18 Wisconsin United States 45.506 -91.981 378.3 3 22 (22, 3)
127 432 496 WBAN:94032 CUSTER CO AIRPORT, SD US 2005-12-31 2018-08-18 South Dakota United States 43.73306 -103.61139 1690.1 4 14 (14, 4)
128 433 497 WBAN:24137 CUT BANK AIRPORT, MT US 1942-11-30 2018-08-18 Montana United States 48.6033 -112.3752 1169.8 0 8 (8, 0)
129 434 498 WBAN:23161 DAGGETT AIRPORT, CA US 1948-12-31 2018-08-18 California United States 34.8536 -116.7858 584.3000000000002 12 5 (5, 12)
130 441 506 WBAN:24219 DALLESPORT AIRPORT, WA US 1956-12-31 2018-08-18 Oregon United States 45.6194 -121.1661 71.60000000000002 3 2 (2, 3)
131 443 508 WBAN:54734 DANBURY MUNICIPAL AIRPORT, CT US 2005-12-31 2018-08-18 Connecticut United States 41.371390000000005 -73.48277999999998 139.3 6 35 (35, 6)
132 444 509 WBAN:94704 DANSVILLE MUNICIPAL AIRPORT, NY US 1972-12-31 2018-08-18 New York United States 42.57083 -77.71333 208.8 5 32 (32, 5)
133 449 514 WBAN:04223 DARRINGTON 21 NNE, WA US 2003-04-02 2018-08-16 Washington United States 48.5405 -121.446 124.1 0 2 (2, 0)
134 452 517 WBAN:23109 DAVIS MONTHAN AFB, AZ US 1941-07-16 2018-08-18 Arizona United States 32.16667 -110.88333 824.2 14 9 (9, 14)
135 459 524 WBAN:04871 DE KALB TAYLOR MUNICIPAL AIRPORT, IL US 2005-12-31 2018-08-18 Illinois United States 41.931670000000004 -88.70805999999997 278.90000000000003 6 25 (25, 6)
136 460 525 WBAN:53925 DE QUEEN SEVIER CO AIRPORT, AR US 2003-12-31 2018-08-18 Arkansas United States 34.05 -94.40083 108.2 13 21 (21, 13)
137 462 527 WBAN:03976 DE RIDDER BEAUREGARD PARISH AIRPORT, LA US 2005-12-31 2018-08-18 Louisiana United States 30.83333 -93.33333 62.2 16 21 (21, 16)
138 464 529 WBAN:53964 DECATUR MUNICIPAL AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 33.254439999999995 -97.58056 319.1 13 18 (18, 13)
139 466 531 WBAN:04916 DECORAH MUNICIPAL AIRPORT, IA US 2005-12-31 2018-08-18 Iowa United States 43.27528 -91.73917 352.7 5 23 (23, 5)
140 470 535 WBAN:22001 DEL RIO LAUGHLIN AFB, TX US 1943-02-16 2018-08-18 Texas United States 29.366670000000003 -100.78333 329.8 17 16 (16, 17)
141 472 537 WBAN:00315 DELAWARE MUNICIPAL JIM MOORE FIELD AIRPORT, OH US 2012-12-31 2018-08-18 Ohio United States 40.28 -83.11500000000002 288.0 7 29 (29, 7)
142 473 539 WBAN:23162 DELTA FAA AIRPORT, UT US 2014-08-19 2018-08-18 Utah United States 39.38333 -112.51666999999999 1450.5 8 8 (8, 8)
143 474 540 WBAN:23078 DEMING MUNICIPAL AIRPORT, NM US 2005-12-31 2018-08-18 New Mexico United States 32.26222 -107.72056 1310.9 14 11 (11, 14)
144 475 541 WBAN:00445 DEMOPOLIS MUNICIPAL AIRPORT, AL US 2014-07-30 2018-08-18 Alabama United States 32.46383 -87.95405 34.1 14 25 (25, 14)
145 476 542 WBAN:04139 DENIO 52 WSW, NV US 2008-06-15 2018-08-16 Nevada United States 41.84840000000001 -119.6357 1981.2 6 3 (3, 6)
146 481 548 WBAN:14933 DES MOINES INTERNATIONAL AIRPORT, IA US 1956-12-31 2018-08-18 Iowa United States 41.5338 -93.65299999999999 291.7 6 21 (21, 6)
147 482 549 WBAN:03104 DESERT RESORTS REGIONAL AIRPORT, CA US 1943-07-11 2018-08-18 California United States 33.626670000000004 -116.15943999999999 -36.0 13 5 (5, 13)
148 483 550 WBAN:53853 DESTIN FORT WALTON BEACH AIRPORT, FL US 2005-12-31 2018-08-18 Florida United States 30.4 -86.47166999999999 6.7 16 26 (26, 16)
149 492 560 WBAN:24138 DILLON AIRPORT, MT US 1956-12-31 2018-08-18 Montana United States 45.2575 -112.5544 1585.0 3 8 (8, 3)
150 493 562 WBAN:00444 DIXON AIRPORT, WY US 2013-12-31 2018-08-18 Wyoming United States 41.037440000000004 -107.49252 1996.1 7 11 (11, 7)
151 494 563 WBAN:04978 DODGE CENTER AIRPORT, MN US 2005-12-31 2018-08-18 Minnesota United States 44.01778 -92.83139 397.8 4 22 (22, 4)
152 495 564 WBAN:13985 DODGE CITY REGIONAL AIRPORT, KS US 1943-04-18 2018-08-18 Kansas United States 37.7686 -99.9678 787.0 10 17 (17, 10)
153 497 567 WBAN:93026 DOUGLAS BISBEE INL AIRPORT, AZ US 1972-12-31 2018-08-18 Arizona Mexico 31.4583 -109.6061 1251.2 15 10 (10, 15)
154 499 569 WBAN:13707 DOVER AFB, DE US 1942-11-30 2018-08-18 Delaware United States 39.13333 -75.46667 8.5 8 34 (34, 8)
155 500 571 WBAN:54786 DOYLESTOWN AIRPORT, PA US 2005-12-31 2018-08-18 Pennsylvania United States 40.33 -75.1225 120.1 7 34 (34, 7)
156 502 574 WBAN:54844 DRUMMOND ISLAND AIRPORT, MI US 2006-08-30 2018-08-18 Michigan United States 46.007220000000004 -83.74278000000001 202.7 2 28 (28, 2)
157 505 577 WBAN:04787 DUBOIS JEFFERSON CO AIRPORT, PA US 1972-12-31 2018-08-18 Pennsylvania United States 41.17833 -78.89889000000001 552.9 7 32 (32, 7)
158 506 578 WBAN:00443 DUBOIS MUNICIPAL AIRPORT, WY US 2013-05-13 2018-08-18 Wyoming United States 43.54836 -109.69025 2224.1 5 10 (10, 5)
159 508 580 WBAN:24103 DUGWAY PROVING GROUNDS, UT US 2006-01-02 2018-08-15 Utah United States 40.18333 -112.93333 1325.6 7 8 (8, 7)
160 511 584 WBAN:03070 DUMAS MOORE CO AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 35.858059999999995 -102.01306 1129.3 11 15 (15, 11)
161 512 585 WBAN:14747 DUNKIRK CHAUTAUQUA CO AIRPORT, NY US 1998-12-31 2018-08-18 New York United States 42.49333 -79.27221999999998 203.0 5 31 (31, 5)
162 513 586 WBAN:00298 DUPONT LAPEER AIRPORT, MI US 2012-12-31 2018-08-18 Michigan United States 43.067 -83.26700000000002 254.2 5 29 (29, 5)
163 517 592 WBAN:03809 DYERSBURG MUNICIPAL AIRPORT, TN US 1943-04-11 2018-08-18 Tennessee United States 36.0002 -89.4094 91.4 11 24 (24, 11)
164 518 595 WBAN:23063 EAGLE CO AIRPORT, CO US 1956-12-31 2018-08-18 Colorado United States 39.65 -106.91667 1980.3 8 12 (12, 8)
165 519 596 WBAN:00480 EAGLE RANGE WEATHER SERVICE OFFICE, UT US 2014-07-30 2018-08-16 Utah United States 41.05 -113.06 1292.0 7 7 (7, 7)
166 522 599 WBAN:00254 EAST CAMERON 278 OIL PLATFORM 2013-12-31 2018-08-18 28.433000000000003 -92.883 224.0 18 22 (22, 18)
167 528 606 WBAN:14991 EAU CLAIRE REGIONAL AIRPORT, WI US 1956-12-31 2018-08-18 Wisconsin United States 44.8665 -91.4879 269.7 3 23 (23, 3)
168 531 609 WBAN:23114 EDWARDS AFB, CA US 1941-11-30 2018-08-18 California United States 34.9 -117.86667 704.4 12 4 (4, 12)
169 532 610 WBAN:93816 EFFINGHAM CO MEMORIAL AIRPORT, IL US 2005-12-31 2018-08-18 Illinois United States 39.07028 -88.53332999999998 178.9 8 25 (25, 8)
170 534 612 WBAN:93992 EL DORADO S AR REGIONAL AIRPORT, AR US 1972-12-31 2018-08-18 Arkansas United States 33.22083 -92.81417 76.8 14 22 (22, 14)
171 536 614 WBAN:23044 EL PASO INTERNATIONAL AIRPORT, TX US 1941-03-31 2018-08-18 Texas United States 31.81111 -106.37583000000001 1194.2 15 12 (12, 15)
172 539 618 WBAN:00182 ELBOW LAKE MUNICIPAL PRIDE OF THE PRAIRIE AIRPORT, MN US 2014-07-30 2018-08-18 Minnesota United States 45.986 -95.992 367.3 2 20 (20, 2)
173 541 620 WBAN:13786 ELIZABETH CITY COAST GUARD AIR STATION, NC US 1948-12-31 2018-08-18 North Carolina United States 36.26056 -76.175 4.0 11 34 (34, 11)
174 542 621 WBAN:00210 ELIZABETHTON MUNICIPAL AIRPORT, TN US 2014-07-30 2018-08-18 Tennessee United States 36.367 -82.167 486.2 11 29 (29, 11)
175 546 625 WBAN:93076 ELKHART, KS US 2005-12-31 2018-08-18 Kansas United States 37.0 -101.88333 1105.8 10 15 (15, 10)
176 547 626 WBAN:03733 ELKINS 21 ENE, WV US 2003-11-16 2018-08-16 West Virginia United States 39.01300000000001 -79.4743 1033.3 8 31 (31, 8)
177 549 628 WBAN:24121 ELKO REGIONAL AIRPORT, NV US 1956-12-31 2018-08-18 Nevada United States 40.8288 -115.7886 1533.1 7 6 (6, 7)
178 550 629 WBAN:24220 ELLENSBURG BOWERS FIELD, WA US 1988-01-05 2018-08-18 Washington United States 47.03389 -120.53028 538.3 1 2 (2, 1)
179 551 630 WBAN:24006 ELLSWORTH AFB, SD US 1939-01-31 2018-08-18 South Dakota United States 44.15 -103.1 999.1 4 15 (15, 4)
180 552 631 WBAN:14748 ELMIRA CORNING REGIONAL AIRPORT, NY US 1972-12-31 2018-08-18 New York United States 42.159440000000004 -76.89193999999998 291.1 6 33 (33, 6)
181 553 632 WBAN:23154 ELY AIRPORT, NV US 1956-12-31 2018-08-18 Nevada United States 39.2952 -114.8466 1908.7 8 6 (6, 8)
182 556 635 WBAN:13989 EMPORIA ASOS, KS US 1972-12-31 2018-08-18 Kansas United States 38.3291 -96.1946 364.5 9 19 (19, 9)
183 559 638 WBAN:53986 ENID WOODRING AIRPORT, OK US 2005-12-31 2018-08-18 Oklahoma United States 36.38333 -97.8 355.7 11 18 (18, 11)
184 560 639 WBAN:24141 EPHRATA MUNICIPAL AIRPORT, WA US 1941-12-31 2018-08-18 Washington United States 47.3078 -119.5154 381.6 1 3 (3, 1)
185 564 643 WBAN:94853 ESCANABA DELTA CO AIRPORT, MI US 2005-12-31 2018-08-18 Michigan United States 45.73333 -87.08332999999998 181.1 3 26 (26, 3)
186 565 644 WBAN:94971 ESTHERVILLE MUNICIPAL AIRPORT, IA US 2005-12-31 2018-08-18 Iowa United States 43.40111 -94.74722 401.4 5 20 (20, 5)
187 567 646 WBAN:00304 EUGENE ISLAND OIL PLATFORM 2012-12-31 2018-08-18 28.633000000000006 -91.48299999999999 28.0 18 23 (23, 18)
188 568 647 WBAN:24221 EUGENE MAHLON SWEET FIELD, OR US 1956-12-31 2018-08-18 Oregon United States 44.1278 -123.2206 107.6 4 0 (0, 4)
189 570 649 WBAN:03170 EUREKA AIRPORT, NV US 2005-12-31 2018-08-18 Nevada United States 39.6013 -116.0055 1809.3 8 5 (5, 8)
190 571 650 WBAN:24213 EUREKA WEATHER FORECAST OFFICE WOODLEY ISLAND, CA US 2005-12-31 2018-08-17 California United States 40.8097 -124.1602 6.1000000000000005 7 0 (0, 7)
191 572 651 WBAN:04111 EVANSTON UINTA CO BURNS FIELD, WY US 1972-12-31 2018-08-18 Wyoming United States 41.27306 -111.03056000000001 2183.3 7 9 (9, 7)
192 577 656 WBAN:24114 FAIRCHILD AFB, WA US 1940-03-31 2018-08-18 Washington United States 47.63333 -117.65 750.1 1 4 (4, 1)
193 578 657 WBAN:00220 FAIRFIELD CO AIRPORT, SC US 2013-12-31 2018-08-18 South Carolina United States 34.315000000000005 -81.10900000000002 176.20000000000005 13 30 (30, 13)
194 579 658 WBAN:04925 FAIRFIELD MUNICIPAL AIRPORT, IA US 2005-12-31 2018-08-18 Iowa United States 41.05306 -91.97889 243.5 7 22 (22, 7)
195 582 662 WBAN:94056 FAITH MUNICIPAL AIRPORT, SD US 2005-12-31 2018-08-18 South Dakota United States 45.031940000000006 -102.01916999999999 786.4 3 15 (15, 3)
196 583 663 WBAN:00270 FAITH RANCH AIRPORT, TX US 2014-01-06 2018-08-18 Texas United States 28.209 -100.01899999999999 236.2 18 17 (17, 18)
197 584 665 WBAN:93102 FALLON NAAS, NV US 1956-12-31 2018-08-18 Nevada United States 39.41667 -118.71667 1199.1 8 3 (3, 8)
198 585 666 WBAN:94957 FALLS CITY BRENNER FIELD, NE US 1999-12-31 2018-08-18 Nebraska United States 40.08028 -95.59194000000001 298.7 8 20 (20, 8)
199 589 670 WBAN:94969 FARIBAULT MUNICIPAL AIRPORT, MN US 2005-12-31 2018-08-18 Minnesota United States 44.33333 -93.31667 323.1 4 21 (21, 4)
200 591 672 WBAN:23090 FARMINGTON FOUR CORNERS REGIONAL AIRPORT, NM US 1956-12-31 2018-08-18 New Mexico United States 36.74361 -108.22917 1674.9 10 11 (11, 10)
201 592 673 WBAN:93996 FARMINGTON REGIONAL AIRPORT, MO US 1995-02-09 2018-08-18 Missouri United States 37.76083 -90.42833 288.6 10 23 (23, 10)
202 593 674 WBAN:03707 FARMVILLE REGIONAL AIRPORT, VA US 2005-12-31 2018-08-18 Virginia United States 37.3575 -78.43777999999998 127.1 10 32 (32, 10)
203 598 679 WBAN:53922 FAYETTEVILLE SPRINGDALE NW AR REGL AIRPORT, AR US 2005-12-31 2018-08-18 Arkansas United States 36.28333 -94.3 392.3 11 21 (21, 11)
204 599 680 WBAN:13762 FENTRESS NAVAL AUXILIARY FIELD, VA US 2007-05-31 2018-08-18 Virginia United States 36.695 -76.13556 4.9 10 34 (34, 10)
205 600 681 WBAN:94966 FERGUS FALLS AIRPORT, MN US 2005-12-31 2018-08-18 Minnesota United States 46.28333 -96.15 360.6 2 19 (19, 2)
206 601 682 WBAN:00326 FERNANDINA BEACH MUNICIPAL AIRPORT, FL US 2013-12-31 2018-08-18 Florida United States 30.616999999999997 -81.467 5.2 16 30 (30, 16)
207 602 683 WBAN:00237 FIELD OF DREAMS AIRPORT, MN US 2014-07-30 2018-08-18 Minnesota United States 46.023 -92.895 311.2 2 22 (22, 2)
208 603 684 WBAN:14825 FINDLAY AIRPORT, OH US 1972-12-31 2018-08-18 Ohio United States 41.01361 -83.66861 243.8 7 28 (28, 7)
209 604 685 WBAN:04780 FITCHBURG MUNICIPAL AIRPORT, MA US 1956-12-31 2018-08-18 Massachusetts United States 42.55194 -71.75583 106.1 5 37 (37, 5)
210 607 688 WBAN:00485 FLAGLER CO AIRPORT, FL US 2012-12-31 2018-08-17 Florida United States 29.46738 -81.20633000000001 10.1 17 30 (30, 17)
211 612 693 WBAN:53889 FLORA MUNICIPAL AIRPORT, IL US 2005-12-31 2018-08-18 Illinois United States 38.66472 -88.45277999999998 143.9 9 25 (25, 9)
212 617 698 WBAN:13829 FORT BENNING LAWSON FIELD, AL US 1939-04-30 2018-08-18 Alabama United States 32.35 -85.0 70.7 14 27 (27, 14)
213 620 701 WBAN:00449 FORT BRIDGER AIRPORT, WY US 2013-07-31 2018-08-18 Wyoming United States 41.39333 -110.40597 2145.5 6 9 (9, 6)
214 621 702 WBAN:13806 FORT CAMPBELL ARMY AIR FIELD, KY US 1943-07-14 2018-08-18 Kentucky United States 36.66667 -87.48333000000001 174.70000000000005 11 26 (26, 11)
215 622 703 WBAN:94015 FORT CARSON BUTTS ARMY AIR FIELD, CO US 1966-09-14 2018-08-18 Colorado United States 38.67833 -104.75667 1779.4 9 13 (13, 9)
216 624 705 WBAN:94933 FORT DODGE OZARK AIRLINES, IA US 2005-12-31 2018-08-18 Iowa United States 42.55 -94.18333 352.3 5 21 (21, 5)
217 628 709 WBAN:03124 FORT HUACHUCA SIERRA VISTA MUNICIPAL AIRPORT, AZ US 1954-10-10 2018-08-18 Arizona United States 31.58833 -110.34416999999999 1438.4 15 9 (9, 15)
218 631 712 WBAN:00162 FORT MORGAN MUNICIPAL AIRPORT, CO US 2013-12-31 2018-08-18 Colorado United States 40.333 -103.8 1393.2 7 14 (14, 7)
219 632 713 WBAN:63847 FORT PAYNE ISBELL FIELD, AL US 2005-12-31 2018-08-18 Alabama United States 34.473890000000004 -85.72139 267.3 12 27 (27, 12)
220 633 714 WBAN:12895 FORT PIERCE ST LUCIE CO INTERNATIONAL AIRPORT, FL US 2005-12-31 2018-08-17 Florida United States 27.49806 -80.37666999999998 7.3 19 31 (31, 19)
221 635 716 WBAN:53988 FORT POLK FULLERTON LANDING STRIP, LA US 2005-12-31 2018-08-18 Louisiana United States 31.021700000000006 -92.9107 94.5 15 22 (22, 15)
222 636 718 WBAN:13947 FORT RILEY MARSHALL ARMY AIR FIELD, KS US 1938-08-16 2018-08-18 Kansas United States 39.05 -96.76667 324.6 8 19 (19, 8)
223 637 720 WBAN:53861 FORT RUCKER LOWE ARMY HELIPORT, AL US 2008-07-16 2018-08-18 Alabama United States 31.35583 -85.75111 74.4 15 27 (27, 15)
224 639 722 WBAN:13964 FORT SMITH REGIONAL AIRPORT, AR US 1946-12-31 2018-08-18 Arkansas United States 35.333 -94.3625 136.9 12 21 (21, 12)
225 640 723 WBAN:03875 FORT STEWART WRIGHT, GA US 2006-01-02 2018-08-18 Georgia United States 31.88333 -81.56667 13.7 15 30 (30, 15)
226 641 724 WBAN:23091 FORT STOCKTON PECOS CO AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 30.91194 -102.91667 917.4 16 15 (15, 16)
227 642 725 WBAN:14827 FORT WAYNE INTERNATIONAL AIRPORT, IN US 1941-10-31 2018-08-18 Indiana United States 40.9705 -85.2063 241.1 7 27 (27, 7)
228 646 729 WBAN:04929 FOSSTON MUNICIPAL AIRPORT, MN US 2005-12-31 2018-08-18 Minnesota United States 47.59278 -95.77528000000001 389.2 1 20 (20, 1)
229 647 731 WBAN:53841 FRANKFORT CAPITAL CITY AIRPORT, KY US 2005-12-31 2018-08-18 Kentucky United States 38.18472 -84.90333000000001 245.1 9 27 (27, 9)
230 648 732 WBAN:54818 FRANKFORT DOW MEMORIAL FIELD AIRPORT, MI US 2005-12-31 2018-08-18 Michigan United States 44.62556 -86.20083000000001 192.6 4 26 (26, 4)
231 649 733 WBAN:00152 FRANKLIN CO STATE AIRPORT, VT US 2008-03-31 2018-08-18 Vermont United States 44.933 -73.10000000000002 70.10000000000001 3 36 (36, 3)
232 651 735 WBAN:94868 FRANKLIN, PA US 1967-12-31 2018-08-18 Pennsylvania United States 41.38333 -79.86667 469.4 6 31 (31, 6)
233 653 737 WBAN:03981 FREDERICK MUNICIPAL AIRPORT, OK US 2005-12-31 2018-08-18 Oklahoma United States 34.344440000000006 -98.98306 382.5 13 17 (17, 13)
234 654 738 WBAN:93947 FREDERICKSBURG GILLESPIE CO AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 30.24333 -98.90972 516.6 16 17 (17, 16)
235 655 739 WBAN:03706 FREDERICKSBURG SHANNON AIRPORT, VA US 2005-12-31 2018-08-18 Virginia United States 38.26667 -77.44917 25.9 9 33 (33, 9)
236 656 740 WBAN:04876 FREEPORT ALBERTUS AIRPORT, IL US 2005-12-31 2018-08-18 Illinois United States 42.246109999999994 -89.58221999999998 261.8 6 24 (24, 6)
237 658 742 WBAN:04924 FREMONT MUNICIPAL AIRPORT, NE US 2005-12-31 2018-08-18 Nebraska United States 41.448890000000006 -96.52 366.7 6 19 (19, 6)
238 659 743 WBAN:04836 FRENCHVILLE NORTHERN AROOSTOOK AIRPORT, ME US 2005-12-31 2018-08-18 Maine United States 47.28556 -68.31333000000001 301.1 1 39 (39, 1)
239 660 744 WBAN:93193 FRESNO YOSEMITE INTERNATIONAL, CA US 1941-12-03 2018-08-18 California United States 36.78 -119.7194 101.5 10 3 (3, 10)
240 661 745 WBAN:94276 FRIDAY HARBOR AIRPORT, WA US 2005-12-31 2018-08-18 Washington United States 48.522220000000004 -123.02306000000002 33.2 0 0 (0, 0)
241 662 746 WBAN:00450 FRONT RANGE AIRPORT, CO US 2013-12-31 2018-08-18 Colorado United States 39.7842 -104.5376 1680.4 8 13 (13, 8)
242 663 747 WBAN:54772 FRYEBURG EASTERN SLOPES REGL AIRPORT, ME US 2005-12-31 2018-08-18 Maine United States 43.99056 -70.9475 135.6 4 37 (37, 4)
243 665 749 WBAN:00265 FULTON CO AIRPORT, IN US 2013-12-31 2018-08-18 Indiana United States 41.066 -86.182 241.1 7 26 (26, 7)
244 667 752 WBAN:03896 GADSDEN MUNICIPAL AIRPORT, AL US 2005-12-31 2018-08-18 Alabama United States 33.96667 -86.08332999999998 173.4 13 27 (27, 13)
245 668 753 WBAN:13975 GAGE AIRPORT, OK US 1956-12-31 2018-08-18 Oklahoma United States 36.2967 -99.7689 667.8000000000002 11 17 (17, 11)
246 669 754 WBAN:03056 GAINES CO AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 32.67528 -102.65444000000001 1010.4 14 15 (15, 14)
247 673 759 WBAN:93764 GAITHERSBURG MONTGOMERY CO AIR PARK, MD US 2013-12-31 2018-08-18 Maryland United States 39.16667 -77.16667 164.3 8 33 (33, 8)
248 674 760 WBAN:94959 GALESBURG MUNICIPAL AIRPORT, IL US 2005-12-31 2018-08-18 Illinois United States 40.93333 -90.43333 232.9 7 23 (23, 7)
249 675 761 WBAN:12993 GALLIANO SOUTH LAFOURCHE AIRPORT, LA US 2005-12-31 2018-08-18 Louisiana United States 29.44472 -90.26111 0.3 17 24 (24, 17)
250 676 762 WBAN:23081 GALLUP MUNICIPAL AIRPORT, NM US 1972-12-31 2018-08-18 New Mexico United States 35.5144 -108.794 1972.4 12 10 (10, 12)
251 678 765 WBAN:23064 GARDEN CITY REGIONAL AIRPORT, KS US 1943-01-31 2018-08-18 Kansas United States 37.92722 -100.72471999999999 878.4 9 16 (16, 9)
252 680 767 WBAN:94041 GARRISON, ND US 2005-12-31 2018-08-18 North Dakota United States 47.64583 -101.43944 582.2 1 16 (16, 1)
253 681 768 WBAN:04807 GARY, IN US 2005-12-31 2018-08-18 Indiana United States 41.61667 -87.41667 180.1 6 26 (26, 6)
254 682 769 WBAN:53870 GASTONIA MUNICIPAL AIRPORT, NC US 2005-12-31 2018-08-18 North Carolina United States 35.196670000000005 -81.15583000000001 242.9 12 30 (30, 12)
255 684 772 WBAN:04854 GAYLORD OTSEGO CO AIRPORT, MI US 1999-08-31 2018-08-18 Michigan United States 45.01333 -84.70138999999998 406.9 3 28 (28, 3)
256 687 776 WBAN:00391 GEORGETOWN CO AIRPORT, SC US 2013-12-31 2018-08-18 South Carolina United States 33.317 -79.31700000000002 12.2 13 31 (31, 13)
257 689 778 WBAN:13764 GEORGETOWN SUSSEX CO AIRPORT, DE US 2005-12-31 2018-08-18 Delaware United States 38.689170000000004 -75.35916999999998 15.5 9 34 (34, 9)
258 693 784 WBAN:53982 GILMER MUNICIPAL AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 32.698890000000006 -94.94889 126.5 14 20 (20, 14)
259 694 785 WBAN:94008 GLASGOW INTERNATIONAL AIRPORT, MT US 1942-12-09 2018-08-18 Montana United States 48.2138 -106.6214 696.5 0 12 (12, 0)
260 695 786 WBAN:00361 GLASGOW MUNICIPAL AIRPORT, KY US 2012-12-31 2018-08-18 Kentucky United States 37.033 -85.95 218.2 10 27 (27, 10)
261 697 788 WBAN:53126 GLENDALE MUNICIPAL AIRPORT, AZ US 2005-12-31 2018-08-18 Arizona United States 33.52722 -112.295 324.9000000000001 13 8 (8, 13)
262 698 789 WBAN:24087 GLENDIVE DAWSON COMMUNITY AIRPORT, MT US 2005-12-31 2018-08-18 Montana United States 47.13333 -104.8 748.9 1 13 (13, 1)
263 699 790 WBAN:14750 GLENS FALLS AIRPORT, NY US 1972-12-31 2018-08-18 New York United States 43.33845 -73.61028 97.8 5 35 (35, 5)
264 701 793 WBAN:00135 GNOSS FIELD AIRPORT, CA US 2014-07-30 2018-08-18 California United States 38.15 -122.55 1.2 9 1 (1, 9)
265 702 794 WBAN:53893 GOLDEN TRIANGLE, MS US 2005-12-31 2018-08-18 Mississippi United States 33.45 -88.58332999999998 80.5 13 25 (25, 13)
266 704 796 WBAN:03708 GOLDSBORO WAYNE MUNICIPAL AIRPORT, NC US 2005-12-31 2018-08-18 North Carolina United States 35.46028 -77.96472 40.8 12 32 (32, 12)
267 705 797 WBAN:23065 GOODLAND RENNER FIELD, KS US 1956-12-31 2018-08-18 Kansas United States 39.36722 -101.69333 1114.3 8 16 (16, 8)
268 706 798 WBAN:04994 GOODRIDGE 12 NNW, MN US 2003-08-19 2018-08-16 Minnesota United States 48.3055 -95.8744 350.5 0 20 (20, 0)
269 708 800 WBAN:14829 GOSHEN MUNICIPAL AIRPORT, IN US 1998-12-31 2018-08-18 Indiana United States 41.5333 -85.78330000000003 253.0 6 27 (27, 6)
270 710 802 WBAN:53977 GRANBURY MUNICIPAL AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 32.44444 -97.81694 237.1 14 18 (18, 14)
271 711 803 WBAN:03195 GRAND CANYON NATIONAL PARK AIRPORT, AZ US 2005-12-31 2018-08-18 Arizona United States 35.94611 -112.15472 2013.5 11 8 (8, 11)
272 713 805 WBAN:14916 GRAND FORKS INTERNATIONAL AIRPORT, ND US 1956-12-31 2018-08-18 North Dakota United States 47.94280000000001 -97.1839 256.6 1 19 (19, 1)
273 715 810 WBAN:23066 GRAND JUNCTION WALKER FIELD, CO US 1956-12-31 2018-08-18 Colorado United States 39.1342 -108.54 1480.7 8 11 (11, 8)
274 717 812 WBAN:94992 GRAND MARAIS, MN US 2005-12-31 2018-08-18 Minnesota United States 47.74722 -90.34444 185.9 1 24 (24, 1)
275 720 815 WBAN:94919 GRAND RAPIDS ITASCA CO AIRPORT, MN US 2005-12-31 2018-08-18 Minnesota United States 47.21111 -93.50972 413.0 1 21 (21, 1)
276 721 816 WBAN:04999 GRANITE FALLS MUNICIPAL AIRPORT LENZEN ROE MEMORIAL FIELD, MN US 2005-12-31 2018-08-18 Minnesota United States 44.75333 -95.55611 319.1 3 20 (20, 3)
277 722 818 WBAN:00481 GRANITE PEAK FILLMORE AIRPORT, UT US 2014-07-29 2018-08-17 Utah United States 38.95813 -112.36313 1519.4 9 8 (8, 9)
278 723 819 WBAN:00387 GRANT CO REGIONAL AIRPORT OGILVIE FIELD, OR US 2013-12-31 2018-08-18 Oregon United States 44.4 -118.96700000000001 1127.2 4 3 (3, 4)
279 724 821 WBAN:93057 GRANTS MILAN MUNICIPAL AIRPORT, NM US 1947-12-31 2018-08-18 New Mexico United States 35.16528 -107.90222 1987.3 12 11 (11, 12)
280 725 822 WBAN:24201 GRAY ARMY AIR FIELD, WA US 1960-05-31 2018-08-18 Washington United States 47.08333 -122.58333 91.4 1 1 (1, 1)
281 727 824 WBAN:53967 GRAYSON CO AIRPORT SHERMAN DENISON, TX US 2005-12-31 2018-08-18 Texas United States 33.71417 -96.67361 228.3 13 19 (19, 13)
282 729 826 WBAN:24143 GREAT FALLS AIRPORT, MT US 1956-12-31 2018-08-18 Montana United States 47.4733 -111.3822 1116.8 1 9 (9, 1)
283 730 827 WBAN:04880 GREATER KANKAKEE AIRPORT, IL US 2005-12-31 2018-08-18 Illinois United States 41.121390000000005 -87.84611 191.7 7 25 (25, 7)
284 731 828 WBAN:24051 GREELEY WELD CO AIRPORT, CO US 2005-12-31 2018-08-18 Colorado United States 40.43556 -104.63194 1431.6 7 13 (13, 7)
285 732 829 WBAN:14898 GREEN BAY A S INTERNATIONAL AIRPORT, WI US 1949-12-31 2018-08-18 Wisconsin United States 44.47940000000001 -88.1366 209.4 4 25 (25, 4)
286 733 832 WBAN:13723 GREENSBORO AIRPORT, NC US 1945-10-31 2018-08-18 North Carolina United States 36.09690000000001 -79.9432 271.3 11 31 (31, 11)
287 735 834 WBAN:13939 GREENVILLE ASOS, MS US 1942-01-19 2018-08-18 Mississippi United States 33.4825 -90.98528 39.0 13 23 (23, 13)
288 738 837 WBAN:63874 GREENVILLE MAC CRENSHAW MEMORIAL AIRPORT, AL US 2006-08-31 2018-08-18 Alabama United States 31.84556 -86.61082999999998 137.5 15 26 (26, 15)
289 739 838 WBAN:94626 GREENVILLE MAINE FORESTRY SERVICE, ME US 2005-12-31 2018-08-18 Maine United States 45.46222 -69.59528 316.1 3 38 (38, 3)
290 740 839 WBAN:13926 GREENVILLE MUNICIPAL AIRPORT MAJORS FIELD, TX US 2005-12-31 2018-08-18 Texas United States 33.06778 -96.06528 163.1 14 19 (19, 14)
291 742 841 WBAN:53874 GREENWOOD CO AIRPORT, SC US 2005-12-31 2018-08-18 South Carolina United States 34.24861 -82.15916999999999 192.3 13 29 (29, 13)
292 743 842 WBAN:13978 GREENWOOD LEFLORE AIRPORT, MS US 1943-02-04 2018-08-18 Mississippi United States 33.496300000000005 -90.0866 40.5 13 24 (24, 13)
293 744 843 WBAN:24048 GREYBULL SOUTH BIG HORN CO AIRPORT, WY US 2005-12-31 2018-08-18 Wyoming United States 44.516940000000005 -108.08221999999999 1198.8 4 11 (11, 4)
294 745 844 WBAN:00339 GRIFFIN SPALDING CO AIRPORT, GA US 2012-12-31 2018-08-18 Georgia United States 33.227000000000004 -84.275 292.3 14 28 (28, 14)
295 746 845 WBAN:14976 GRINNELL, IA US 2006-08-30 2018-08-18 Iowa United States 41.71667 -92.7 307.2 6 22 (22, 6)
296 747 846 WBAN:03870 GRNVL SPART INTERNATIONAL AIRPORT, SC US 1962-10-14 2018-08-18 South Carolina United States 34.8842 -82.2209 287.4000000000001 12 29 (29, 12)
297 748 847 WBAN:54819 GROSSE ILE MUNICIPAL AIRPORT, MI US 2005-12-31 2018-08-18 Michigan United States 42.09861 -83.16111 178.9 6 29 (29, 6)
298 750 849 WBAN:53941 GROVE MUNICIPAL AIRPORT, OK US 2005-12-31 2018-08-18 Oklahoma United States 36.605 -94.73833 253.9 11 20 (20, 11)
299 752 851 WBAN:93874 GULFPORT BILOXI AIRPORT, MS US 2004-12-31 2018-08-18 Mississippi United States 30.411900000000006 -89.08080000000002 12.8 16 24 (24, 16)
300 754 854 WBAN:53913 GUTHRIE MUNICIPAL AIRPORT, OK US 2005-12-31 2018-08-18 Oklahoma United States 35.8517 -97.4142 325.5 11 19 (19, 11)
301 755 855 WBAN:03030 GUYMON MUNICIPAL AIRPORT, OK US 2005-12-31 2018-08-18 Oklahoma United States 36.681670000000004 -101.50528 951.9 11 16 (16, 11)
302 756 856 WBAN:94836 GWINN K I SAWYER AFB, MI US 2005-12-31 2018-08-18 Michigan United States 46.35 -87.4 372.2 2 26 (26, 2)
303 757 857 WBAN:00150 GWINNER ROGER MELROE FIELD AIRPORT, ND US 2014-06-30 2018-08-18 North Dakota United States 46.217 -97.633 386.2 2 18 (18, 2)
304 758 858 WBAN:00221 H A CLARK MEMORIAL FIELD AIRPORT, AZ US 2013-12-31 2018-08-18 Arizona United States 35.30000000000001 -112.2 2035.1 12 8 (8, 12)
305 759 859 WBAN:00186 H L SONNY CALLAHAN AIRPORT, AL US 2013-12-31 2018-08-18 Alabama United States 30.46 -87.87700000000002 28.0 16 25 (25, 16)
306 760 861 WBAN:93706 HAGERSTOWN WASHINGTON CO REGIONAL AIRPORT, MD US 2005-12-31 2018-08-18 Maryland United States 39.70778 -77.72972 212.8 8 32 (32, 8)
307 761 862 WBAN:94161 HAILEY FRIEDMAN MEMORIAL AIRPORT, ID US 2005-12-31 2018-08-18 Idaho United States 43.5 -114.3 1617.3 5 7 (7, 5)
308 763 864 WBAN:00231 HALIFAX NORTHAMPTON REGIONAL AIRPORT, NC US 2013-12-31 2018-08-18 North Carolina United States 36.33 -77.635 44.2 11 33 (33, 11)
309 764 865 WBAN:53938 HALLIBURTON FIELD AIRPORT, OK US 2005-12-31 2018-08-18 Oklahoma United States 34.47083 -97.95083000000001 339.2 12 18 (18, 12)
310 766 867 WBAN:53855 HAMILTON BUTLER CO REGIONAL AIRPORT, OH US 2005-12-31 2018-08-18 Ohio United States 39.36444 -84.52472 193.2 8 28 (28, 8)
311 767 868 WBAN:00357 HAMILTON MUNICIPAL AIRPORT, TX US 2013-12-31 2018-08-18 Texas United States 31.666 -98.149 396.2 15 18 (18, 15)
312 768 869 WBAN:03908 HAMMOND MUNICIPAL AIRPORT, LA US 2005-12-31 2018-08-18 Louisiana United States 30.52083 -90.4175 13.4 16 23 (23, 16)
313 769 870 WBAN:00154 HAMPTON ROADS EXECUTIVE AIRPORT, VA US 2012-12-31 2018-08-18 Virginia United States 36.783 -76.45 7.0 10 33 (33, 10)
314 770 871 WBAN:14858 HANCOCK HOUGHTON CO AIRPORT, MI US 1956-12-31 2018-08-18 Michigan United States 47.16861 -88.48889 333.8 1 25 (25, 1)
315 771 872 WBAN:53119 HANFORD MUNICIPAL AIRPORT, CA US 2005-12-31 2018-08-18 California United States 36.31889 -119.62888999999998 75.9 11 3 (3, 11)
316 772 874 WBAN:23170 HANKSVILLE AIRPORT, UT US 1972-12-31 2018-08-18 Utah United States 38.41667 -110.7 1355.1 9 9 (9, 9)
317 773 875 WBAN:00455 HANNIBAL REGIONAL AIRPORT, MO US 2013-12-31 2018-08-18 Missouri United States 39.72516 -91.44386 234.7 8 23 (23, 8)
318 774 876 WBAN:04884 HARBOR SPRINGS AIRPORT, MI US 2005-12-31 2018-08-18 Michigan United States 45.42556 -84.91333 206.3 3 27 (27, 3)
319 775 877 WBAN:04936 HARLAN MUNICIPAL AIRPORT, IA US 2005-12-31 2018-08-18 Iowa United States 41.58417 -95.33944 375.2 6 20 (20, 6)
320 777 879 WBAN:00159 HARRIET ALEXANDER FIELD AIRPORT, CO US 2013-12-31 2018-08-18 Colorado United States 38.533 -106.05 2294.2000000000007 9 12 (12, 9)
321 778 880 WBAN:14751 HARRISBURG CAPITAL CITY AIRPORT, PA US 1956-12-31 2018-08-18 Pennsylvania United States 40.217220000000005 -76.85139000000001 103.6 7 33 (33, 7)
322 780 883 WBAN:13971 HARRISON BOONE CO AIRPORT, AR US 1946-07-31 2018-08-18 Arkansas United States 36.2668 -93.1566 418.8 11 22 (22, 11)
323 781 884 WBAN:00431 HARRISON CO AIRPORT, TX US 2012-12-31 2018-08-18 Texas United States 32.5205 -94.3077 108.8 14 21 (21, 14)
324 783 886 WBAN:14752 HARTFORD BRAINARD FIELD, CT US 1973-12-31 2018-08-18 Connecticut United States 41.73611 -72.65056 5.8 6 36 (36, 6)
325 784 887 WBAN:00219 HARTSVILLE REGIONAL AIRPORT, SC US 2012-12-31 2018-08-18 South Carolina United States 34.4 -80.117 111.3 12 31 (31, 12)
326 785 888 WBAN:00322 HARVEY MUNICIPAL AIRPORT, ND US 2014-07-30 2018-08-18 North Dakota United States 47.783 -99.93299999999999 489.2 1 17 (17, 1)
327 787 890 WBAN:13833 HATTIESBURG CHAIN MUNICIPAL AIRPORT, MS US 1942-08-19 2018-08-18 Mississippi United States 31.281940000000002 -89.25305999999998 46.0 15 24 (24, 15)
328 789 892 WBAN:94012 HAVRE AIRPORT ASOS, MT US 1961-01-31 2018-08-18 Montana United States 48.5428 -109.7633 787.9 0 10 (10, 0)
329 790 893 WBAN:03167 HAWTHORNE MUNICIPAL AIRPORT, CA US 2005-12-31 2018-08-18 California United States 33.92278 -118.33417 19.2 13 4 (4, 13)
330 791 894 WBAN:94025 HAYDEN YAMPA VALLEY AIRPORT, CO US 2005-12-31 2018-08-18 Colorado United States 40.48111 -107.2175 2011.7 7 12 (12, 7)
331 792 895 WBAN:03968 HAYS MUNICIPAL AIRPORT, KS US 2005-12-31 2018-08-18 Kansas United States 38.85 -99.26667 609.0 9 17 (17, 9)
332 793 896 WBAN:93228 HAYWARD AIR TERMINAL, CA US 1999-12-31 2018-08-18 California United States 37.6542 -122.115 13.1 10 1 (1, 10)
333 794 897 WBAN:94973 HAYWARD MUNICIPAL AIRPORT, WI US 2005-12-31 2018-08-18 Wisconsin United States 46.02611 -91.44417 367.0 2 23 (23, 2)
334 796 899 WBAN:53973 HEARNE MUNICIPAL AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 30.871940000000002 -96.62222 86.9 16 19 (19, 16)
335 797 900 WBAN:00337 HEART OF GEORGIA REGIONAL AIRPORT, GA US 2012-12-31 2018-08-18 Georgia United States 32.214 -83.12799999999999 93.3 14 29 (29, 14)
336 798 903 WBAN:04998 HEBRON MUNICIPAL AIRPORT, NE US 2005-12-31 2018-08-18 Nebraska United States 40.14917 -97.58667 449.0 7 18 (18, 7)
337 799 904 WBAN:24144 HELENA AIRPORT ASOS, MT US 1956-12-31 2018-08-18 Montana United States 46.6056 -111.9636 1166.8 2 8 (8, 2)
338 800 905 WBAN:53886 HENDERSON CITY CO AIRPORT, KY US 2005-12-31 2018-08-18 Kentucky United States 37.8 -87.68333 118.0 10 25 (25, 10)
339 801 906 WBAN:03711 HENDERSON OXFORD AIRPORT, NC US 2005-12-31 2018-08-18 North Carolina United States 36.36139 -78.52888999999998 160.6 11 32 (32, 11)
340 802 907 WBAN:00250 HENRY TIFT MYERS AIRPORT, GA US 2012-12-31 2018-08-18 Georgia United States 31.429 -83.48899999999999 108.2 15 28 (28, 15)
341 803 908 WBAN:00129 HEREFORD MUNICIPAL AIRPORT, TX US 2013-12-31 2018-08-18 Texas United States 34.85 -102.333 1153.1 12 15 (15, 12)
342 804 909 WBAN:04113 HERMISTON MUNICIPAL AIRPORT, OR US 2005-12-31 2018-08-18 Oregon United States 45.82583 -119.26111000000002 195.4 3 3 (3, 3)
343 805 910 WBAN:94038 HETTINGER MUNICIPAL AIRPORT, ND US 2005-12-31 2018-08-18 North Dakota United States 46.01389 -102.65472 824.5 2 15 (15, 2)
344 806 911 WBAN:94931 HIBBING CHISHOLM HIBBING AIRPORT, MN US 1971-12-31 2018-08-18 Minnesota United States 47.386390000000006 -92.83889 412.1 1 22 (22, 1)
345 807 912 WBAN:03810 HICKORY FAA AIRPORT, NC US 1972-12-31 2018-08-18 North Carolina United States 35.74207 -81.38229 358.1 11 30 (30, 11)
346 808 913 WBAN:00306 HIGH ISLAND 179 OIL PLATFORM 2012-12-31 2018-08-18 29.183000000000003 -94.517 75.3 17 21 (21, 17)
347 809 914 WBAN:00260 HIGH ISLAND 376 2013-12-31 2018-08-18 27.962 -93.671 0.3 18 21 (21, 18)
348 810 916 WBAN:93990 HILL CITY MUNICIPAL AIRPORT, KS US 1972-12-31 2018-08-18 Kansas United States 39.37556 -99.82972 666.9 8 17 (17, 8)
349 811 917 WBAN:53972 HILLSBORO MUNICIPAL AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 32.08361 -97.09722 208.8 15 19 (19, 15)
350 813 919 WBAN:63837 HILTON HEAD ISLAND AIRPORT, SC US 2005-12-31 2018-08-18 South Carolina United States 32.21667 -80.7 7.3 14 30 (30, 14)
351 814 920 WBAN:93986 HOBART MUNICIPAL AIRPORT, OK US 1972-12-31 2018-08-18 Oklahoma United States 34.9894 -99.0525 474.3 12 17 (17, 12)
352 815 921 WBAN:93034 HOBBS LEA CO AIRPORT, NM US 1942-10-31 2018-08-18 New Mexico United States 32.6933 -103.2125 1114.0 14 14 (14, 14)
353 816 923 WBAN:04935 HOLDREGE BREWSTER FIELD AIRPORT, NE US 2005-12-31 2018-08-18 Nebraska United States 40.45 -99.33917 702.3000000000002 7 17 (17, 7)
354 818 925 WBAN:00392 HOLLISTER MUNICIPAL AIRPORT, CA US 1945-02-28 2018-08-18 California United States 36.9 -121.417 72.2 10 2 (2, 10)
355 819 926 WBAN:23002 HOLLOMAN AFB, NM US 2006-01-02 2018-08-18 New Mexico United States 32.85 -106.1 1267.4 14 12 (12, 14)
356 820 927 WBAN:23803 HOLLY SPRINGS 4 N, MS US 2008-01-31 2018-08-16 Mississippi United States 34.8223 -89.43480000000002 147.5 12 24 (24, 12)
357 821 928 WBAN:00163 HOLYOKE AIRPORT, CO US 2013-12-31 2018-08-18 Colorado United States 40.567 -102.267 1137.2 7 15 (15, 7)
358 822 929 WBAN:00128 HOMERVILLE AIRPORT, GA US 2012-12-31 2018-08-18 Georgia United States 31.055999999999997 -82.76700000000002 57.3 15 29 (29, 15)
359 823 930 WBAN:12962 HONDO MUNICIPAL AIRPORT, TX US 1942-09-14 2018-08-18 Texas United States 29.360100000000006 -99.1742 280.40000000000003 17 17 (17, 17)
360 824 931 WBAN:00429 HOPKINS FIELD AIRPORT, CO US 2012-12-31 2018-08-18 Colorado United States 38.23875 -108.56326999999999 1810.5 9 11 (11, 9)
361 825 932 WBAN:94225 HOQUIAM BOWERMAN AIRPORT, WA US 1956-12-31 2018-08-18 Washington United States 46.9727 -123.9302 3.7 2 0 (0, 2)
362 826 933 WBAN:00225 HORSESHOE BAY RESORT AIRPORT, TX US 2012-12-31 2018-08-18 Texas United States 30.533 -98.367 333.1 16 18 (18, 16)
363 827 934 WBAN:03962 HOT SPRINGS ASOS, AR US 2005-12-31 2018-08-18 Arkansas United States 34.29 -93.06 163.1 13 22 (22, 13)
364 828 935 WBAN:93757 HOT SPRINGS INGALLS FIELD, VA US 2005-12-31 2018-08-18 Virginia United States 37.95 -79.81667 1156.1 9 31 (31, 9)
365 830 937 WBAN:14609 HOULTON AIRPORT, ME US 1999-12-31 2018-08-18 Maine United States 46.1185 -67.7928 145.1 2 39 (39, 2)
366 831 938 WBAN:12927 HOUMA TERREBONNE AIRPORT, LA US 2005-12-31 2018-08-18 Louisiana United States 29.566390000000002 -90.66028 4.0 17 23 (23, 17)
367 840 948 WBAN:12918 HOUSTON WILLIAM P HOBBY AIRPORT, TX US 1946-07-27 2018-08-18 Texas United States 29.63806 -95.28194 13.4 17 20 (20, 17)
368 841 949 WBAN:04887 HOWELL LIVINGSTON CO AIRPORT, MI US 2005-12-31 2018-08-18 Michigan United States 42.62944 -83.98416999999998 287.7 5 28 (28, 5)
369 842 950 WBAN:00484 HULETT MUNICIPAL AIRPORT, WY US 2014-07-30 2018-08-18 Wyoming United States 44.66286 -104.56783 1300.0 4 13 (13, 4)
370 843 951 WBAN:53896 HUNTINGBURG AIRPORT, IN US 2005-12-31 2018-08-18 Indiana United States 38.24889 -86.95361 161.20000000000005 9 26 (26, 9)
371 844 952 WBAN:03860 HUNTINGTON TRI STATE AIRPORT, WV US 1961-11-30 2018-08-18 West Virginia United States 38.365 -82.555 251.2 9 29 (29, 9)
372 846 954 WBAN:63804 HUNTSVILLE MADISON CO EXECUTIVE AIRPORT, AL US 2005-12-31 2018-08-18 Alabama United States 34.86139 -86.55722 230.1 12 26 (26, 12)
373 847 955 WBAN:53903 HUNTSVILLE MUNICIPAL AIRPORT, TX US 2005-12-31 2018-08-18 Texas United States 30.743890000000004 -95.58611 111.6 16 20 (20, 16)
374 848 956 WBAN:14936 HURON REGIONAL AIRPORT, SD US 1956-12-31 2018-08-18 South Dakota United States 44.3981 -98.2231 390.1 4 18 (18, 4)
375 849 957 WBAN:13986 HUTCHINSON MUNICIPAL AIRPORT, KS US 1945-01-31 2018-08-18 Kansas United States 38.06528 -97.86056 470.3 9 18 (18, 9)
376 850 958 WBAN:04933 HUTCHINSON MUNICIPAL BUTLER FIELD AIRPORT, MN US 2005-12-31 2018-08-18 Minnesota United States 44.85889 -94.38167 323.1 3 21 (21, 3)
377 851 959 WBAN:00291 HUTSON FIELD AIRPORT, ND US 2013-12-31 2018-08-18 North Dakota United States 48.405 -97.371 251.2 0 19 (19, 0)
378 852 960 WBAN:94720 HYANNIS BARNSTABLE MUNICIPAL AIRPORT, MA US 2005-12-31 2018-08-18 Massachusetts United States 41.66861 -70.28 16.8 6 38 (38, 6)
379 853 961 WBAN:53990 IDABEL MCCURTAIN CO REGIONAL AIRPORT, OK US 2005-12-31 2018-08-18 Oklahoma United States 33.909440000000004 -94.85944 143.9 13 20 (20, 13)
380 854 962 WBAN:00452 IDAHO CO AIRPORT, ID US 2013-12-31 2018-08-18 Idaho United States 45.94255 -116.12341 1010.1 2 5 (5, 2)
381 855 963 WBAN:24145 IDAHO FALLS FANNING FIELD, ID US 1956-12-31 2018-08-18 Idaho United States 43.51639 -112.06722 1441.4 5 8 (8, 5)
382 857 965 WBAN:93115 IMPERIAL BEACH REAM FIELD NAS, CA US 1956-12-31 2018-08-18 California United States 32.56667 -117.11667 7.3 14 5 (5, 14)
383 858 966 WBAN:03144 IMPERIAL CO AIRPORT, CA US 2005-12-31 2018-08-18 California United States 32.83417 -115.57861000000001 -17.7 14 6 (6, 14)
384 859 967 WBAN:24091 IMPERIAL MUNICIPAL AIRPORT, NE US 1973-03-31 2018-08-18 Nebraska United States 40.51 -101.62 996.1 7 16 (16, 7)
385 861 969 WBAN:00141 INDEPENDENCE MUNICIPAL AIRPORT, KS US 1944-01-31 2018-08-18 Kansas United States 37.158 -95.77799999999999 251.2 10 20 (20, 10)
386 862 971 WBAN:23141 INDIAN SPRINGS, NV US 1963-09-02 2018-08-18 Nevada United States 36.58333 -115.68333 951.9 11 6 (6, 11)
387 863 972 WBAN:64706 INDIANA J STEWART, PA US 2005-12-31 2018-08-18 Pennsylvania United States 40.63333 -79.10000000000002 428.2 7 31 (31, 7)
388 866 975 WBAN:93819 INDIANAPOLIS INTERNATIONAL AIRPORT, IN US 1942-10-05 2018-08-18 Indiana United States 39.72517 -86.28168000000001 241.1 8 26 (26, 8)
389 867 977 WBAN:14918 INTERNATIONAL FALLS INTERNATIONAL AIRPORT, MN US 1956-12-31 2018-08-18 Minnesota United States 48.5614 -93.3981 360.6 0 21 (21, 0)
390 868 978 WBAN:00377 INVERNESS AIRPORT, FL US 2012-12-31 2018-08-18 Florida United States 28.816999999999997 -82.31700000000002 15.2 17 29 (29, 17)
391 869 980 WBAN:00240 IONIA CO AIRPORT, MI US 2014-07-30 2018-08-18 Michigan United States 42.938 -85.061 249.0 5 27 (27, 5)
392 870 981 WBAN:14937 IOWA CITY MUNICIPAL AIRPORT, IA US 1997-01-22 2018-08-18 Iowa United States 41.63278 -91.54306 198.1 6 23 (23, 6)
393 871 982 WBAN:54941 IOWA FALLS MUNICIPAL AIRPORT, IA US 2013-06-20 2018-08-18 Iowa United States 42.47138 -93.20707 346.6 5 22 (22, 5)
394 873 984 WBAN:94926 IRONWOOD, MI US 2005-12-31 2018-08-18 Michigan United States 46.53333 -90.13333 374.9 2 24 (24, 2)
395 874 985 WBAN:04997 ISEDOR IVERSON AIRPORT, MN US 2005-12-31 2018-08-18 Minnesota United States 46.61889 -93.30972 374.3 2 21 (21, 2)
396 875 986 WBAN:04781 ISLIP LI MACARTHUR AIRPORT, NY US 1972-12-31 2018-08-18 New York United States 40.7939 -73.10170000000002 25.6 7 36 (36, 7)
397 876 988 WBAN:94761 ITHACA TOMPKINS CNTY, NY US 2005-12-31 2018-08-18 New York United States 42.48333 -76.46667 335.0 5 33 (33, 5)
398 877 989 WBAN:00464 J DOUGLAS BAKE MEMORIAL AIRPORT, WI US 2014-07-30 2018-08-18 Wisconsin United States 44.87405 -87.90977 184.4 3 25 (25, 3)
399 878 990 WBAN:00216 JACK BARSTOW AIRPORT, MI US 2013-12-31 2018-08-18 Michigan United States 43.663 -84.26100000000002 194.2 4 28 (28, 4)
400 879 991 WBAN:00394 JACKSON CO AIRPORT, GA US 2013-12-31 2018-08-17 Georgia United States 34.147 -83.561 290.2 13 28 (28, 13)
401 881 993 WBAN:24166 JACKSON HOLE AIRPORT, WY US 2005-12-31 2018-08-17 Wyoming United States 43.6 -110.73333000000001 1956.5 4 9 (9, 4)
402 882 994 WBAN:03940 JACKSON INTERNATIONAL AIRPORT, MS US 1942-08-31 2018-08-18 Mississippi United States 32.3205 -90.0777 100.6 14 24 (24, 14)
403 883 995 WBAN:03889 JACKSON JULIAN CARROLL AIRPORT, KY US 1973-01-01 2018-08-18 Kentucky United States 37.591390000000004 -83.31443999999998 416.1 10 29 (29, 10)
404 884 996 WBAN:03811 JACKSON MCKELLAR SIPES AIRPORT, TN US 1972-12-31 2018-08-18 Tennessee United States 35.593 -88.9167 132.0 11 25 (25, 11)
405 885 997 WBAN:04946 JACKSON MUNICIPAL AIRPORT, MN US 2005-12-31 2018-08-18 Minnesota United States 43.65 -94.98639 440.7 4 20 (20, 4)
406 886 998 WBAN:14833 JACKSON REYNOLDS FIELD, MI US 1972-12-31 2018-08-18 Michigan United States 42.2667 -84.4667 304.2 6 28 (28, 6)
407 887 999 WBAN:93753 JACKSONVILLE ALBERT ELLIS AIRPORT, NC US 2005-12-31 2018-08-18 North Carolina United States 34.83333 -77.61667 29.3 12 33 (33, 12)

532
Project Final/Project.ipynb
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@@ -1,532 +0,0 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Project Notebook\n",
"This is the full and complete notebook that takes in the data from NOAA and processes it into frames to be used in the PredNet architecture and produce a resulting prediction."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import os\n",
"from tqdm import tqdm"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#Getting a list of files in raw data folder\n",
"filenames = os.listdir('D:/Nico/Desktop/processed_data')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"header_wanted = [\n",
" 'HOURLYVISIBILITY',\n",
" 'HOURLYDRYBULBTEMPC',\n",
" 'HOURLYWETBULBTEMPC',\n",
" 'HOURLYDewPointTempC',\n",
" 'HOURLYRelativeHumidity',\n",
" 'HOURLYWindSpeed',\n",
" 'HOURLYWindGustSpeed',\n",
" 'HOURLYStationPressure',\n",
" 'HOURLYPressureTendency',\n",
" 'HOURLYPressureChange',\n",
" 'HOURLYSeaLevelPressure',\n",
" 'HOURLYPrecip',\n",
" 'HOURLYAltimeterSetting']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"usecols = ['DATE','STATION'] + header_wanted"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#Loading all files into a pandas Dataframe\n",
"tqdm.pandas()\n",
"df = pd.concat([pd.read_csv('D:/Nico/Desktop/processed_data/{}'.format(x), usecols=usecols, low_memory=False) for x in tqdm(filenames)])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"At this point all the data has been loaded into a single dataframe and any data changes have been made. The next step is to break the data up by WBAN and place in a 2D array at the appropriate grid cell. "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"stations = pd.read_csv(\"../Playground/stations_unique.csv\", usecols = ['STATION_ID', 'LON_SCALED', 'LAT_SCALED'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"height = 20\n",
"width = 40"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mask = [([0] * width) for i in range(height)]\n",
"\n",
"wban_loc = dict(zip(stations.STATION_ID,zip(stations.LON_SCALED,stations.LAT_SCALED)))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"grid = [([pd.DataFrame()] * width) for i in range(height)]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for key, value in tqdm(wban_loc.items()):\n",
" mask[value[1]][value[0]] = 1\n",
" grid[value[1]][value[0]] = df.loc[df.STATION == key]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.imshow(mask)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#TODO Handle different sized data some stacks too short\n",
"def create_frames(data,height, width, depth):\n",
" days = []\n",
" frames = []\n",
" for i in tqdm(range(depth)):\n",
" frame = np.zeros((height,width,12))\n",
" for y in range(height):\n",
" for x in range(width):\n",
" if(not data[y][x].empty):\n",
" frame[y][x] = data[y][x].iloc[[i],1:13].values.flatten()\n",
" if((i+1)%24 != 0):\n",
" frames.append(frame)\n",
" else:\n",
" frames.append(frame)\n",
" days.append(frames)\n",
" frames = []\n",
" return days"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def average_grid_fill(mask,data, height, width):\n",
" \n",
" for i in range(height):\n",
" for j in range(width):\n",
" if(mask[i][j] != 1):\n",
" neighbors = get_neighbors(j,i,data)\n",
" data[i][j] = np.mean(neighbors)\n",
" \n",
" return data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def get_neighbors(x,y,g):\n",
" neighbors = []\n",
" for i in [y-1,y,y+1]:\n",
" for j in [x-1,x,x+1]:\n",
" if(i >= 0 and j >= 0):\n",
" if(i != y or j != x ):\n",
" try:\n",
" neighbors.append(g[i][j])\n",
" except:\n",
" pass\n",
" return neighbors"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def store_sequence(frames):\n",
" import hickle as hkl\n",
" source_list = []\n",
" \n",
" for days in range(len(frames)):\n",
" for day in range(len(frames[days])):\n",
" source_list += '{}'.format(days)\n",
" \n",
" hkl.dump(frames, './data/train/x_train.hkl')\n",
" hkl.dump(source_list, './data/train/x_sources.hkl')\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Splits is a dictionary holding train, test, val\n",
"the values for train, test, and val are lists of tuples holding category and folder name\n",
"in the end each image gets a source associated with it\n",
"there is only one data and one source hickle dump for each of train test and val"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"frames = create_frames(grid, height, width,504)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#TODO use loop to average each frame\n",
"for x in tqdm(range(len(frames))):\n",
" for y in range(len(frames[0])):\n",
" frames[x][y] = average_grid_fill(mask, frames[x][y], height, width )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"store_sequence(frames)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"np_frames = np.array(frames)\n",
"np_frames.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"store_sequence(np_frames)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"At this point I have processed the data and made it into discrete frames of data and it is time to run it through the PredNet architecture for training."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
]
}
],
"source": [
"np.random.seed(123)\n",
"from six.moves import cPickle\n",
"\n",
"from keras import backend as K\n",
"from keras.models import Model\n",
"from keras.layers import Input, Dense, Flatten\n",
"from keras.layers import LSTM\n",
"from keras.layers import TimeDistributed\n",
"from keras.callbacks import LearningRateScheduler, ModelCheckpoint\n",
"from keras.optimizers import Adam\n",
"\n",
"from prednet import PredNet\n",
"from data_utils import SequenceGenerator"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"WEIGHTS_DIR = './weights/'\n",
"DATA_DIR = './data/'"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"save_model = True # if weights will be saved\n",
"weights_file = os.path.join(WEIGHTS_DIR, 'prednet_weather_weights.hdf5') # where weights will be saved\n",
"json_file = os.path.join(WEIGHTS_DIR, 'prednet_weather_model.json')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# Data files\n",
"#TODO: Use the files from NOAA and process them into proper frames\n",
"train_file = os.path.join(DATA_DIR,'train/', 'x_train.hkl')\n",
"train_sources = os.path.join(DATA_DIR, 'train/', 'x_sources.hkl')\n",
"#val_file = os.path.join(DATA_DIR, 'X_val.hkl')\n",
"#val_sources = os.path.join(DATA_DIR, 'sources_val.hkl')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# Training parameters\n",
"nb_epoch = 1\n",
"batch_size = 4\n",
"samples_per_epoch = 500\n",
"N_seq_val = 100 # number of sequences to use for validation"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Model parameters\n",
"n_channels, im_height, im_width = (12, 20, 40)\n",
"input_shape = (n_channels, im_height, im_width) if K.image_data_format() == 'channels_first' else (im_height, im_width, n_channels)\n",
"stack_sizes = (n_channels, 48, 96)\n",
"R_stack_sizes = stack_sizes\n",
"A_filt_sizes = (3, 3)\n",
"Ahat_filt_sizes = (3, 3, 3)\n",
"R_filt_sizes = (3, 3, 3)\n",
"layer_loss_weights = np.array([1., 0., 0.]) # weighting for each layer in final loss; \"L_0\" model: [1, 0, 0, 0], \"L_all\": [1, 0.1, 0.1, 0.1]\n",
"layer_loss_weights = np.expand_dims(layer_loss_weights, 1)\n",
"nt = 24 # number of timesteps used for sequences in training\n",
"time_loss_weights = 1./ (nt - 1) * np.ones((nt,1)) # equally weight all timesteps except the first\n",
"time_loss_weights[0] = 0"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"prednet = PredNet(stack_sizes, R_stack_sizes,\n",
" A_filt_sizes, Ahat_filt_sizes, R_filt_sizes,\n",
" output_mode='error', return_sequences=True)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"inputs = Input(shape=(nt,) + input_shape)\n",
"errors = prednet(inputs) # errors will be (batch_size, nt, nb_layers)\n",
"errors_by_time = TimeDistributed(Dense(1, trainable=False), weights=[layer_loss_weights, np.zeros(1)], trainable=False)(errors) # calculate weighted error by layer\n",
"errors_by_time = Flatten()(errors_by_time) # will be (batch_size, nt)\n",
"final_errors = Dense(1, weights=[time_loss_weights, np.zeros(1)], trainable=False)(errors_by_time) # weight errors by time\n",
"model = Model(inputs=inputs, outputs=final_errors)\n",
"model.compile(loss='mean_absolute_error', optimizer='adam')"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"_________________________________________________________________\n",
"Layer (type) Output Shape Param # \n",
"=================================================================\n",
"input_1 (InputLayer) (None, 24, 20, 40, 12) 0 \n",
"_________________________________________________________________\n",
"pred_net_1 (PredNet) (None, 24, 3) 1645548 \n",
"_________________________________________________________________\n",
"time_distributed_1 (TimeDist (None, 24, 1) 4 \n",
"_________________________________________________________________\n",
"flatten_1 (Flatten) (None, 24) 0 \n",
"_________________________________________________________________\n",
"dense_2 (Dense) (None, 1) 25 \n",
"=================================================================\n",
"Total params: 1,645,577\n",
"Trainable params: 1,645,548\n",
"Non-trainable params: 29\n",
"_________________________________________________________________\n"
]
}
],
"source": [
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"truth = []\n",
"for i in range(20):\n",
" truth.append(np.random.randint(255,size=(1)))\n",
"output = np.array(truth)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"train_generator = SequenceGenerator(train_file, train_sources, nt, batch_size=batch_size, shuffle=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"lr_schedule = lambda epoch: 0.001 if epoch < 75 else 0.0001 # start with lr of 0.001 and then drop to 0.0001 after 75 epochs\n",
"callbacks = [LearningRateScheduler(lr_schedule)]\n",
"#history = model.fit(np_frames, output ,batch_size, nb_epoch, callbacks=callbacks)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/1\n"
]
}
],
"source": [
"history = model.fit_generator(train_generator, samples_per_epoch / batch_size, nb_epoch, callbacks=callbacks)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

544
Project Final/Training/Training.ipynb Normal file
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@@ -0,0 +1,544 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
]
}
],
"source": [
"import numpy as np\n",
"import os\n",
"np.random.seed(123)\n",
"from six.moves import cPickle\n",
"\n",
"from keras import backend as K\n",
"from keras.models import Model\n",
"from keras.layers import Input, Dense, Flatten\n",
"from keras.layers import LSTM\n",
"from keras.layers import TimeDistributed\n",
"from keras.callbacks import LearningRateScheduler, ModelCheckpoint\n",
"from keras.optimizers import Adam\n",
"\n",
"from prednet import PredNet\n",
"from data_utils import SequenceGenerator"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"WEIGHTS_DIR = './weights/'\n",
"DATA_DIR = '../data/'"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"save_model = True # if weights will be saved\n",
"weights_file = os.path.join(WEIGHTS_DIR, 'prednet_weather_weights.hdf5') # where weights will be saved\n",
"json_file = os.path.join(WEIGHTS_DIR, 'prednet_weather_model.json')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Data files\n",
"train_file = os.path.join(DATA_DIR, 'x_train.hkl')\n",
"train_sources = os.path.join(DATA_DIR, 'sources_train.hkl')\n",
"val_file = os.path.join(DATA_DIR, 'x_val.hkl')\n",
"val_sources = os.path.join(DATA_DIR, 'sources_val.hkl')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# Training parameters\n",
"nb_epoch = 150\n",
"batch_size = 24\n",
"samples_per_epoch = 500\n",
"N_seq_val = 140 # number of sequences to use for validation"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# Model parameters\n",
"n_channels, im_height, im_width = (7, 20, 40)\n",
"input_shape = (n_channels, im_height, im_width) if K.image_data_format() == 'channels_first' else (im_height, im_width, n_channels)\n",
"stack_sizes = (n_channels, 48, 96)\n",
"R_stack_sizes = stack_sizes\n",
"A_filt_sizes = (3, 3)\n",
"Ahat_filt_sizes = (3, 3, 3)\n",
"R_filt_sizes = (3, 3, 3)\n",
"layer_loss_weights = np.array([1., 0., 0.]) # weighting for each layer in final loss; \"L_0\" model: [1, 0, 0, 0], \"L_all\": [1, 0.1, 0.1, 0.1]\n",
"layer_loss_weights = np.expand_dims(layer_loss_weights, 1)\n",
"nt = 24 # number of timesteps used for sequences in training\n",
"time_loss_weights = 1./ (nt - 1) * np.ones((nt,1)) # equally weight all timesteps except the first\n",
"time_loss_weights[0] = 0"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"prednet = PredNet(stack_sizes, R_stack_sizes,\n",
" A_filt_sizes, Ahat_filt_sizes, R_filt_sizes,\n",
" output_mode='error', return_sequences=True)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"inputs = Input(shape=(nt,) + input_shape)\n",
"errors = prednet(inputs) # errors will be (batch_size, nt, nb_layers)\n",
"errors_by_time = TimeDistributed(Dense(1, trainable=False), weights=[layer_loss_weights, np.zeros(1)], trainable=False)(errors) # calculate weighted error by layer\n",
"errors_by_time = Flatten()(errors_by_time) # will be (batch_size, nt)\n",
"final_errors = Dense(1, weights=[time_loss_weights, np.zeros(1)], trainable=False)(errors_by_time) # weight errors by time\n",
"model = Model(inputs=inputs, outputs=final_errors)\n",
"model.compile(loss='mean_absolute_error', optimizer='adam')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"_________________________________________________________________\n",
"Layer (type) Output Shape Param # \n",
"=================================================================\n",
"input_1 (InputLayer) (None, 24, 20, 40, 7) 0 \n",
"_________________________________________________________________\n",
"pred_net_1 (PredNet) (None, 24, 3) 1621448 \n",
"_________________________________________________________________\n",
"time_distributed_1 (TimeDist (None, 24, 1) 4 \n",
"_________________________________________________________________\n",
"flatten_1 (Flatten) (None, 24) 0 \n",
"_________________________________________________________________\n",
"dense_2 (Dense) (None, 1) 25 \n",
"=================================================================\n",
"Total params: 1,621,477\n",
"Trainable params: 1,621,448\n",
"Non-trainable params: 29\n",
"_________________________________________________________________\n"
]
}
],
"source": [
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"train_generator = SequenceGenerator(train_file, train_sources, nt, batch_size=batch_size, shuffle=False)\n",
"val_generator = SequenceGenerator(val_file, val_sources, nt, batch_size=batch_size, N_seq=N_seq_val)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"lr_schedule = lambda epoch: 0.001 if epoch < 75 else 0.0001 # start with lr of 0.001 and then drop to 0.0001 after 75 epochs\n",
"callbacks = [LearningRateScheduler(lr_schedule)]\n",
"if save_model:\n",
" if not os.path.exists(WEIGHTS_DIR): os.mkdir(WEIGHTS_DIR)\n",
" callbacks.append(ModelCheckpoint(filepath=weights_file, monitor='val_loss', save_best_only=True))"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/150\n",
" - 21s - loss: 0.9718 - val_loss: 0.9142\n",
"Epoch 2/150\n",
" - 15s - loss: 0.9089 - val_loss: 0.8895\n",
"Epoch 3/150\n",
" - 15s - loss: 0.9057 - val_loss: 0.8826\n",
"Epoch 4/150\n",
" - 15s - loss: 0.8905 - val_loss: 0.8765\n",
"Epoch 5/150\n",
" - 15s - loss: 0.9106 - val_loss: 0.8840\n",
"Epoch 6/150\n",
" - 15s - loss: 0.8812 - val_loss: 0.8749\n",
"Epoch 7/150\n",
" - 15s - loss: 0.9099 - val_loss: 0.8897\n",
"Epoch 8/150\n",
" - 15s - loss: 0.8829 - val_loss: 0.8711\n",
"Epoch 9/150\n",
" - 15s - loss: 0.9039 - val_loss: 0.8843\n",
"Epoch 10/150\n",
" - 15s - loss: 0.8814 - val_loss: 0.8696\n",
"Epoch 11/150\n",
" - 15s - loss: 0.8897 - val_loss: 0.8881\n",
"Epoch 12/150\n",
" - 15s - loss: 0.8803 - val_loss: 0.8696\n",
"Epoch 13/150\n",
" - 15s - loss: 0.8819 - val_loss: 0.8836\n",
"Epoch 14/150\n",
" - 15s - loss: 0.8786 - val_loss: 0.8672\n",
"Epoch 15/150\n",
" - 15s - loss: 0.8732 - val_loss: 0.8671\n",
"Epoch 16/150\n",
" - 15s - loss: 0.8805 - val_loss: 0.8698\n",
"Epoch 17/150\n",
" - 15s - loss: 0.8643 - val_loss: 0.8600\n",
"Epoch 18/150\n",
" - 15s - loss: 0.8845 - val_loss: 0.8574\n",
"Epoch 19/150\n",
" - 16s - loss: 0.8581 - val_loss: 0.8568\n",
"Epoch 20/150\n",
" - 15s - loss: 0.8815 - val_loss: 0.8588\n",
"Epoch 21/150\n",
" - 15s - loss: 0.8622 - val_loss: 0.8575\n",
"Epoch 22/150\n",
" - 15s - loss: 0.8737 - val_loss: 0.8604\n",
"Epoch 23/150\n",
" - 15s - loss: 0.8619 - val_loss: 0.8568\n",
"Epoch 24/150\n",
" - 15s - loss: 0.8694 - val_loss: 0.8606\n",
"Epoch 25/150\n",
" - 15s - loss: 0.8638 - val_loss: 0.8542\n",
"Epoch 26/150\n",
" - 15s - loss: 0.8664 - val_loss: 0.8591\n",
"Epoch 27/150\n",
" - 15s - loss: 0.8700 - val_loss: 0.8551\n",
"Epoch 28/150\n",
" - 15s - loss: 0.8576 - val_loss: 0.8534\n",
"Epoch 29/150\n",
" - 15s - loss: 0.8751 - val_loss: 0.8512\n",
"Epoch 30/150\n",
" - 15s - loss: 0.8532 - val_loss: 0.8520\n",
"Epoch 31/150\n",
" - 15s - loss: 0.8758 - val_loss: 0.8518\n",
"Epoch 32/150\n",
" - 15s - loss: 0.8565 - val_loss: 0.8514\n",
"Epoch 33/150\n",
" - 15s - loss: 0.8688 - val_loss: 0.8500\n",
"Epoch 34/150\n",
" - 15s - loss: 0.8571 - val_loss: 0.8521\n",
"Epoch 35/150\n",
" - 15s - loss: 0.8659 - val_loss: 0.8501\n",
"Epoch 36/150\n",
" - 15s - loss: 0.8595 - val_loss: 0.8508\n",
"Epoch 37/150\n",
" - 15s - loss: 0.8634 - val_loss: 0.8512\n",
"Epoch 38/150\n",
" - 15s - loss: 0.8642 - val_loss: 0.8505\n",
"Epoch 39/150\n",
" - 15s - loss: 0.8562 - val_loss: 0.8490\n",
"Epoch 40/150\n",
" - 15s - loss: 0.8706 - val_loss: 0.8491\n",
"Epoch 41/150\n",
" - 15s - loss: 0.8498 - val_loss: 0.8490\n",
"Epoch 42/150\n",
" - 15s - loss: 0.8727 - val_loss: 0.8479\n",
"Epoch 43/150\n",
" - 15s - loss: 0.8519 - val_loss: 0.8473\n",
"Epoch 44/150\n",
" - 15s - loss: 0.8671 - val_loss: 0.8474\n",
"Epoch 45/150\n",
" - 15s - loss: 0.8534 - val_loss: 0.8485\n",
"Epoch 46/150\n",
" - 15s - loss: 0.8624 - val_loss: 0.8466\n",
"Epoch 47/150\n",
" - 15s - loss: 0.8563 - val_loss: 0.8467\n",
"Epoch 48/150\n",
" - 15s - loss: 0.8607 - val_loss: 0.8468\n",
"Epoch 49/150\n",
" - 15s - loss: 0.8594 - val_loss: 0.8475\n",
"Epoch 50/150\n",
" - 15s - loss: 0.8548 - val_loss: 0.8457\n",
"Epoch 51/150\n",
" - 15s - loss: 0.8671 - val_loss: 0.8456\n",
"Epoch 52/150\n",
" - 15s - loss: 0.8476 - val_loss: 0.8453\n",
"Epoch 53/150\n",
" - 15s - loss: 0.8701 - val_loss: 0.8452\n",
"Epoch 54/150\n",
" - 15s - loss: 0.8470 - val_loss: 0.8455\n",
"Epoch 55/150\n",
" - 15s - loss: 0.8674 - val_loss: 0.8447\n",
"Epoch 56/150\n",
" - 15s - loss: 0.8502 - val_loss: 0.8457\n",
"Epoch 57/150\n",
" - 15s - loss: 0.8614 - val_loss: 0.8443\n",
"Epoch 58/150\n",
" - 15s - loss: 0.8532 - val_loss: 0.8448\n",
"Epoch 59/150\n",
" - 15s - loss: 0.8590 - val_loss: 0.8443\n",
"Epoch 60/150\n",
" - 15s - loss: 0.8561 - val_loss: 0.8439\n",
"Epoch 61/150\n",
" - 15s - loss: 0.8543 - val_loss: 0.8441\n",
"Epoch 62/150\n",
" - 15s - loss: 0.8630 - val_loss: 0.8444\n",
"Epoch 63/150\n",
" - 15s - loss: 0.8472 - val_loss: 0.8437\n",
"Epoch 64/150\n",
" - 15s - loss: 0.8688 - val_loss: 0.8435\n",
"Epoch 65/150\n",
" - 15s - loss: 0.8435 - val_loss: 0.8439\n",
"Epoch 66/150\n",
" - 15s - loss: 0.8675 - val_loss: 0.8439\n",
"Epoch 67/150\n",
" - 15s - loss: 0.8484 - val_loss: 0.8432\n",
"Epoch 68/150\n",
" - 15s - loss: 0.8605 - val_loss: 0.8433\n",
"Epoch 69/150\n",
" - 15s - loss: 0.8508 - val_loss: 0.8438\n",
"Epoch 70/150\n",
" - 15s - loss: 0.8582 - val_loss: 0.8433\n",
"Epoch 71/150\n",
" - 15s - loss: 0.8531 - val_loss: 0.8426\n",
"Epoch 72/150\n",
" - 15s - loss: 0.8553 - val_loss: 0.8435\n",
"Epoch 73/150\n",
" - 15s - loss: 0.8601 - val_loss: 0.8425\n",
"Epoch 74/150\n",
" - 15s - loss: 0.8472 - val_loss: 0.8424\n",
"Epoch 75/150\n",
" - 15s - loss: 0.8659 - val_loss: 0.8425\n",
"Epoch 76/150\n",
" - 15s - loss: 0.8433 - val_loss: 0.8422\n",
"Epoch 77/150\n",
" - 15s - loss: 0.8670 - val_loss: 0.8423\n",
"Epoch 78/150\n",
" - 15s - loss: 0.8471 - val_loss: 0.8426\n",
"Epoch 79/150\n",
" - 15s - loss: 0.8607 - val_loss: 0.8426\n",
"Epoch 80/150\n",
" - 15s - loss: 0.8487 - val_loss: 0.8426\n",
"Epoch 81/150\n",
" - 15s - loss: 0.8582 - val_loss: 0.8426\n",
"Epoch 82/150\n",
" - 15s - loss: 0.8521 - val_loss: 0.8424\n",
"Epoch 83/150\n",
" - 15s - loss: 0.8558 - val_loss: 0.8424\n",
"Epoch 84/150\n",
" - 15s - loss: 0.8576 - val_loss: 0.8421\n",
"Epoch 85/150\n",
" - 15s - loss: 0.8489 - val_loss: 0.8421\n",
"Epoch 86/150\n",
" - 15s - loss: 0.8648 - val_loss: 0.8421\n",
"Epoch 87/150\n",
" - 15s - loss: 0.8431 - val_loss: 0.8421\n",
"Epoch 88/150\n",
" - 15s - loss: 0.8673 - val_loss: 0.8422\n",
"Epoch 89/150\n",
" - 15s - loss: 0.8460 - val_loss: 0.8424\n",
"Epoch 90/150\n",
" - 15s - loss: 0.8621 - val_loss: 0.8425\n",
"Epoch 91/150\n",
" - 15s - loss: 0.8481 - val_loss: 0.8425\n",
"Epoch 92/150\n",
" - 15s - loss: 0.8578 - val_loss: 0.8426\n",
"Epoch 93/150\n",
" - 15s - loss: 0.8518 - val_loss: 0.8424\n",
"Epoch 94/150\n",
" - 15s - loss: 0.8564 - val_loss: 0.8424\n",
"Epoch 95/150\n",
" - 15s - loss: 0.8556 - val_loss: 0.8421\n",
"Epoch 96/150\n",
" - 15s - loss: 0.8506 - val_loss: 0.8421\n",
"Epoch 97/150\n",
" - 15s - loss: 0.8637 - val_loss: 0.8419\n",
"Epoch 98/150\n",
" - 15s - loss: 0.8438 - val_loss: 0.8420\n",
"Epoch 99/150\n",
" - 15s - loss: 0.8672 - val_loss: 0.8421\n",
"Epoch 100/150\n",
" - 15s - loss: 0.8437 - val_loss: 0.8422\n",
"Epoch 101/150\n",
" - 15s - loss: 0.8645 - val_loss: 0.8423\n",
"Epoch 102/150\n",
" - 15s - loss: 0.8472 - val_loss: 0.8424\n",
"Epoch 103/150\n",
" - 15s - loss: 0.8589 - val_loss: 0.8425\n",
"Epoch 104/150\n",
" - 15s - loss: 0.8508 - val_loss: 0.8424\n",
"Epoch 105/150\n",
" - 15s - loss: 0.8567 - val_loss: 0.8425\n",
"Epoch 106/150\n",
" - 15s - loss: 0.8542 - val_loss: 0.8421\n",
"Epoch 107/150\n",
" - 15s - loss: 0.8522 - val_loss: 0.8421\n",
"Epoch 108/150\n",
" - 15s - loss: 0.8613 - val_loss: 0.8419\n",
"Epoch 109/150\n",
" - 15s - loss: 0.8454 - val_loss: 0.8419\n",
"Epoch 110/150\n",
" - 15s - loss: 0.8672 - val_loss: 0.8420\n",
"Epoch 111/150\n",
" - 15s - loss: 0.8420 - val_loss: 0.8420\n",
"Epoch 112/150\n",
" - 15s - loss: 0.8660 - val_loss: 0.8422\n",
"Epoch 113/150\n",
" - 15s - loss: 0.8470 - val_loss: 0.8423\n",
"Epoch 114/150\n",
" - 15s - loss: 0.8593 - val_loss: 0.8424\n",
"Epoch 115/150\n",
" - 15s - loss: 0.8498 - val_loss: 0.8423\n",
"Epoch 116/150\n",
" - 15s - loss: 0.8572 - val_loss: 0.8425\n",
"Epoch 117/150\n",
" - 15s - loss: 0.8522 - val_loss: 0.8421\n",
"Epoch 118/150\n",
" - 15s - loss: 0.8545 - val_loss: 0.8421\n",
"Epoch 119/150\n",
" - 15s - loss: 0.8593 - val_loss: 0.8418\n",
"Epoch 120/150\n",
" - 15s - loss: 0.8466 - val_loss: 0.8418\n",
"Epoch 121/150\n",
" - 15s - loss: 0.8653 - val_loss: 0.8418\n",
"Epoch 122/150\n",
" - 15s - loss: 0.8429 - val_loss: 0.8418\n",
"Epoch 123/150\n",
" - 15s - loss: 0.8667 - val_loss: 0.8420\n",
"Epoch 124/150\n",
" - 15s - loss: 0.8467 - val_loss: 0.8422\n",
"Epoch 125/150\n",
" - 15s - loss: 0.8603 - val_loss: 0.8422\n",
"Epoch 126/150\n",
" - 15s - loss: 0.8483 - val_loss: 0.8422\n",
"Epoch 127/150\n",
" - 15s - loss: 0.8578 - val_loss: 0.8424\n",
"Epoch 128/150\n",
" - 15s - loss: 0.8517 - val_loss: 0.8421\n",
"Epoch 129/150\n",
" - 15s - loss: 0.8554 - val_loss: 0.8422\n",
"Epoch 130/150\n",
" - 15s - loss: 0.8572 - val_loss: 0.8418\n",
"Epoch 131/150\n",
" - 15s - loss: 0.8484 - val_loss: 0.8418\n",
"Epoch 132/150\n",
" - 15s - loss: 0.8645 - val_loss: 0.8417\n",
"Epoch 133/150\n",
" - 15s - loss: 0.8427 - val_loss: 0.8417\n",
"Epoch 134/150\n",
" - 15s - loss: 0.8669 - val_loss: 0.8419\n",
"Epoch 135/150\n",
" - 15s - loss: 0.8456 - val_loss: 0.8420\n",
"Epoch 136/150\n",
" - 15s - loss: 0.8617 - val_loss: 0.8421\n",
"Epoch 137/150\n",
" - 15s - loss: 0.8477 - val_loss: 0.8422\n",
"Epoch 138/150\n",
" - 15s - loss: 0.8574 - val_loss: 0.8423\n",
"Epoch 139/150\n",
" - 15s - loss: 0.8515 - val_loss: 0.8421\n",
"Epoch 140/150\n",
" - 15s - loss: 0.8560 - val_loss: 0.8422\n",
"Epoch 141/150\n",
" - 15s - loss: 0.8553 - val_loss: 0.8419\n",
"Epoch 142/150\n",
" - 15s - loss: 0.8502 - val_loss: 0.8418\n",
"Epoch 143/150\n",
" - 15s - loss: 0.8633 - val_loss: 0.8416\n",
"Epoch 144/150\n",
" - 15s - loss: 0.8434 - val_loss: 0.8416\n",
"Epoch 145/150\n",
" - 15s - loss: 0.8668 - val_loss: 0.8417\n",
"Epoch 146/150\n",
" - 15s - loss: 0.8433 - val_loss: 0.8418\n",
"Epoch 147/150\n",
" - 15s - loss: 0.8642 - val_loss: 0.8419\n",
"Epoch 148/150\n",
" - 15s - loss: 0.8468 - val_loss: 0.8421\n",
"Epoch 149/150\n",
" - 15s - loss: 0.8585 - val_loss: 0.8421\n",
"Epoch 150/150\n",
" - 15s - loss: 0.8504 - val_loss: 0.8420\n"
]
}
],
"source": [
"history = model.fit_generator(train_generator, steps_per_epoch=(samples_per_epoch / batch_size), \n",
" epochs=nb_epoch, callbacks=callbacks,\n",
" validation_data=val_generator, validation_steps=N_seq_val / batch_size,\n",
" verbose=2, workers=0)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"if save_model:\n",
" json_string = model.to_json()\n",
" with open(json_file, \"w\") as f:\n",
" f.write(json_string)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

68
Project Final/Training/data_utils.py Normal file
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import hickle as hkl
import numpy as np
from keras import backend as K
from keras.preprocessing.image import Iterator
# Data generator that creates sequences for input into PredNet.
class SequenceGenerator(Iterator):
def __init__(self, data_file, source_file, nt,
batch_size=8, shuffle=False, seed=None,
output_mode='error', sequence_start_mode='all', N_seq=None,
data_format=K.image_data_format()):
self.X = hkl.load(data_file) # X will be like (n_images, nb_cols, nb_rows, nb_channels)
self.sources = hkl.load(source_file) # source for each image so when creating sequences can assure that consecutive frames are from same video
self.nt = nt
self.batch_size = batch_size
self.data_format = data_format
assert sequence_start_mode in {'all', 'unique'}, 'sequence_start_mode must be in {all, unique}'
self.sequence_start_mode = sequence_start_mode
assert output_mode in {'error', 'prediction'}, 'output_mode must be in {error, prediction}'
self.output_mode = output_mode
if self.data_format == 'channels_first':
self.X = np.transpose(self.X, (0, 3, 1, 2))
self.im_shape = self.X[0].shape
if self.sequence_start_mode == 'all': # allow for any possible sequence, starting from any frame
self.possible_starts = np.array([i for i in range(self.X.shape[0] - self.nt) if self.sources[i] == self.sources[i + self.nt - 1]])
elif self.sequence_start_mode == 'unique': #create sequences where each unique frame is in at most one sequence
curr_location = 0
possible_starts = []
while curr_location < self.X.shape[0] - self.nt + 1:
if self.sources[curr_location] == self.sources[curr_location + self.nt - 1]:
possible_starts.append(curr_location)
curr_location += self.nt
else:
curr_location += 1
self.possible_starts = possible_starts
if shuffle:
self.possible_starts = np.random.permutation(self.possible_starts)
if N_seq is not None and len(self.possible_starts) > N_seq: # select a subset of sequences if want to
self.possible_starts = self.possible_starts[:N_seq]
self.N_sequences = len(self.possible_starts)
super(SequenceGenerator, self).__init__(len(self.possible_starts), batch_size, shuffle, seed)
def next(self):
with self.lock:
index_array = next(self.index_generator)
current_index = index_array[0]
current_batch_size = len(index_array)
batch_x = np.zeros((current_batch_size, self.nt) + self.im_shape, np.float32)
for i, idx in enumerate(index_array):
idx = self.possible_starts[idx]
batch_x[i] = self.preprocess(self.X[idx:idx+self.nt])
if self.output_mode == 'error': # model outputs errors, so y should be zeros
batch_y = np.zeros(current_batch_size, np.float32)
elif self.output_mode == 'prediction': # output actual pixels
batch_y = batch_x
return batch_x, batch_y
def preprocess(self, X):
return X.astype(np.float32) / 255
def create_all(self):
X_all = np.zeros((self.N_sequences, self.nt) + self.im_shape, np.float32)
for i, idx in enumerate(self.possible_starts):
X_all[i] = self.preprocess(self.X[idx:idx+self.nt])
return X_all

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import os
import numpy as np
from keras import backend as K
from keras.legacy.interfaces import generate_legacy_interface, recurrent_args_preprocessor
from keras.models import model_from_json
legacy_prednet_support = generate_legacy_interface(
allowed_positional_args=['stack_sizes', 'R_stack_sizes',
'A_filt_sizes', 'Ahat_filt_sizes', 'R_filt_sizes'],
conversions=[('dim_ordering', 'data_format'),
('consume_less', 'implementation')],
value_conversions={'dim_ordering': {'tf': 'channels_last',
'th': 'channels_first',
'default': None},
'consume_less': {'cpu': 0,
'mem': 1,
'gpu': 2}},
preprocessor=recurrent_args_preprocessor)
# Convert old Keras (1.2) json models and weights to Keras 2.0
def convert_model_to_keras2(old_json_file, old_weights_file, new_json_file, new_weights_file):
from prednet import PredNet
# If using tensorflow, it doesn't allow you to load the old weights.
if K.backend() != 'theano':
os.environ['KERAS_BACKEND'] = backend
reload(K)
f = open(old_json_file, 'r')
json_string = f.read()
f.close()
model = model_from_json(json_string, custom_objects = {'PredNet': PredNet})
model.load_weights(old_weights_file)
weights = model.layers[1].get_weights()
if weights[0].shape[0] == model.layers[1].stack_sizes[1]:
for i, w in enumerate(weights):
if w.ndim == 4:
weights[i] = np.transpose(w, (2, 3, 1, 0))
model.set_weights(weights)
model.save_weights(new_weights_file)
json_string = model.to_json()
with open(new_json_file, "w") as f:
f.write(json_string)
if __name__ == '__main__':
old_dir = './model_data/'
new_dir = './model_data_keras2/'
if not os.path.exists(new_dir):
os.mkdir(new_dir)
for w_tag in ['', '-Lall', '-extrapfinetuned']:
m_tag = '' if w_tag == '-Lall' else w_tag
convert_model_to_keras2(old_dir + 'prednet_kitti_model' + m_tag + '.json',
old_dir + 'prednet_kitti_weights' + w_tag + '.hdf5',
new_dir + 'prednet_kitti_model' + m_tag + '.json',
new_dir + 'prednet_kitti_weights' + w_tag + '.hdf5')

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import numpy as np
from keras import backend as K
from keras import activations
from keras.layers import Recurrent
from keras.layers import Conv2D, UpSampling2D, MaxPooling2D
from keras.engine import InputSpec
from keras_utils import legacy_prednet_support
class PredNet(Recurrent):
'''PredNet architecture - Lotter 2016.
Stacked convolutional LSTM inspired by predictive coding principles.
# Arguments
stack_sizes: number of channels in targets (A) and predictions (Ahat) in each layer of the architecture.
Length is the number of layers in the architecture.
First element is the number of channels in the input.
Ex. (3, 16, 32) would correspond to a 3 layer architecture that takes in RGB images and has 16 and 32
channels in the second and third layers, respectively.
R_stack_sizes: number of channels in the representation (R) modules.
Length must equal length of stack_sizes, but the number of channels per layer can be different.
A_filt_sizes: filter sizes for the target (A) modules.
Has length of 1 - len(stack_sizes).
Ex. (3, 3) would mean that targets for layers 2 and 3 are computed by a 3x3 convolution of the errors (E)
from the layer below (followed by max-pooling)
Ahat_filt_sizes: filter sizes for the prediction (Ahat) modules.
Has length equal to length of stack_sizes.
Ex. (3, 3, 3) would mean that the predictions for each layer are computed by a 3x3 convolution of the
representation (R) modules at each layer.
R_filt_sizes: filter sizes for the representation (R) modules.
Has length equal to length of stack_sizes.
Corresponds to the filter sizes for all convolutions in the LSTM.
pixel_max: the maximum pixel value.
Used to clip the pixel-layer prediction.
error_activation: activation function for the error (E) units.
A_activation: activation function for the target (A) and prediction (A_hat) units.
LSTM_activation: activation function for the cell and hidden states of the LSTM.
LSTM_inner_activation: activation function for the gates in the LSTM.
output_mode: either 'error', 'prediction', 'all' or layer specification (ex. R2, see below).
Controls what is outputted by the PredNet.
If 'error', the mean response of the error (E) units of each layer will be outputted.
That is, the output shape will be (batch_size, nb_layers).
If 'prediction', the frame prediction will be outputted.
If 'all', the output will be the frame prediction concatenated with the mean layer errors.
The frame prediction is flattened before concatenation.
Nomenclature of 'all' is kept for backwards compatibility, but should not be confused with returning all of the layers of the model
For returning the features of a particular layer, output_mode should be of the form unit_type + layer_number.
For instance, to return the features of the LSTM "representational" units in the lowest layer, output_mode should be specificied as 'R0'.
The possible unit types are 'R', 'Ahat', 'A', and 'E' corresponding to the 'representation', 'prediction', 'target', and 'error' units respectively.
extrap_start_time: time step for which model will start extrapolating.
Starting at this time step, the prediction from the previous time step will be treated as the "actual"
data_format: 'channels_first' or 'channels_last'.
It defaults to the `image_data_format` value found in your
Keras config file at `~/.keras/keras.json`.
# References
- [Deep predictive coding networks for video prediction and unsupervised learning](https://arxiv.org/abs/1605.08104)
- [Long short-term memory](http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf)
- [Convolutional LSTM network: a machine learning approach for precipitation nowcasting](http://arxiv.org/abs/1506.04214)
- [Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects](http://www.nature.com/neuro/journal/v2/n1/pdf/nn0199_79.pdf)
'''
@legacy_prednet_support
def __init__(self, stack_sizes, R_stack_sizes,
A_filt_sizes, Ahat_filt_sizes, R_filt_sizes,
pixel_max=1., error_activation='relu', A_activation='relu',
LSTM_activation='tanh', LSTM_inner_activation='hard_sigmoid',
output_mode='error', extrap_start_time=None,
data_format=K.image_data_format(), **kwargs):
self.stack_sizes = stack_sizes
self.nb_layers = len(stack_sizes)
assert len(R_stack_sizes) == self.nb_layers, 'len(R_stack_sizes) must equal len(stack_sizes)'
self.R_stack_sizes = R_stack_sizes
assert len(A_filt_sizes) == (self.nb_layers - 1), 'len(A_filt_sizes) must equal len(stack_sizes) - 1'
self.A_filt_sizes = A_filt_sizes
assert len(Ahat_filt_sizes) == self.nb_layers, 'len(Ahat_filt_sizes) must equal len(stack_sizes)'
self.Ahat_filt_sizes = Ahat_filt_sizes
assert len(R_filt_sizes) == (self.nb_layers), 'len(R_filt_sizes) must equal len(stack_sizes)'
self.R_filt_sizes = R_filt_sizes
self.pixel_max = pixel_max
self.error_activation = activations.get(error_activation)
self.A_activation = activations.get(A_activation)
self.LSTM_activation = activations.get(LSTM_activation)
self.LSTM_inner_activation = activations.get(LSTM_inner_activation)
default_output_modes = ['prediction', 'error', 'all']
layer_output_modes = [layer + str(n) for n in range(self.nb_layers) for layer in ['R', 'E', 'A', 'Ahat']]
assert output_mode in default_output_modes + layer_output_modes, 'Invalid output_mode: ' + str(output_mode)
self.output_mode = output_mode
if self.output_mode in layer_output_modes:
self.output_layer_type = self.output_mode[:-1]
self.output_layer_num = int(self.output_mode[-1])
else:
self.output_layer_type = None
self.output_layer_num = None
self.extrap_start_time = extrap_start_time
assert data_format in {'channels_last', 'channels_first'}, 'data_format must be in {channels_last, channels_first}'
self.data_format = data_format
self.channel_axis = -3 if data_format == 'channels_first' else -1
self.row_axis = -2 if data_format == 'channels_first' else -3
self.column_axis = -1 if data_format == 'channels_first' else -2
super(PredNet, self).__init__(**kwargs)
self.input_spec = [InputSpec(ndim=5)]
def compute_output_shape(self, input_shape):
if self.output_mode == 'prediction':
out_shape = input_shape[2:]
elif self.output_mode == 'error':
out_shape = (self.nb_layers,)
elif self.output_mode == 'all':
out_shape = (np.prod(input_shape[2:]) + self.nb_layers,)
else:
stack_str = 'R_stack_sizes' if self.output_layer_type == 'R' else 'stack_sizes'
stack_mult = 2 if self.output_layer_type == 'E' else 1
out_stack_size = stack_mult * getattr(self, stack_str)[self.output_layer_num]
out_nb_row = input_shape[self.row_axis] / 2**self.output_layer_num
out_nb_col = input_shape[self.column_axis] / 2**self.output_layer_num
if self.data_format == 'channels_first':
out_shape = (out_stack_size, out_nb_row, out_nb_col)
else:
out_shape = (out_nb_row, out_nb_col, out_stack_size)
if self.return_sequences:
return (input_shape[0], input_shape[1]) + out_shape
else:
return (input_shape[0],) + out_shape
def get_initial_state(self, x):
input_shape = self.input_spec[0].shape
init_nb_row = input_shape[self.row_axis]
init_nb_col = input_shape[self.column_axis]
base_initial_state = K.zeros_like(x) # (samples, timesteps) + image_shape
non_channel_axis = -1 if self.data_format == 'channels_first' else -2
for _ in range(2):
base_initial_state = K.sum(base_initial_state, axis=non_channel_axis)
base_initial_state = K.sum(base_initial_state, axis=1) # (samples, nb_channels)
initial_states = []
states_to_pass = ['r', 'c', 'e']
nlayers_to_pass = {u: self.nb_layers for u in states_to_pass}
if self.extrap_start_time is not None:
states_to_pass.append('ahat') # pass prediction in states so can use as actual for t+1 when extrapolating
nlayers_to_pass['ahat'] = 1
for u in states_to_pass:
for l in range(nlayers_to_pass[u]):
ds_factor = 2 ** l
nb_row = init_nb_row // ds_factor
nb_col = init_nb_col // ds_factor
if u in ['r', 'c']:
stack_size = self.R_stack_sizes[l]
elif u == 'e':
stack_size = 2 * self.stack_sizes[l]
elif u == 'ahat':
stack_size = self.stack_sizes[l]
output_size = stack_size * nb_row * nb_col # flattened size
reducer = K.zeros((input_shape[self.channel_axis], output_size)) # (nb_channels, output_size)
initial_state = K.dot(base_initial_state, reducer) # (samples, output_size)
if self.data_format == 'channels_first':
output_shp = (-1, stack_size, nb_row, nb_col)
else:
output_shp = (-1, nb_row, nb_col, stack_size)
initial_state = K.reshape(initial_state, output_shp)
initial_states += [initial_state]
if K._BACKEND == 'theano':
from theano import tensor as T
# There is a known issue in the Theano scan op when dealing with inputs whose shape is 1 along a dimension.
# In our case, this is a problem when training on grayscale images, and the below line fixes it.
initial_states = [T.unbroadcast(init_state, 0, 1) for init_state in initial_states]
if self.extrap_start_time is not None:
initial_states += [K.variable(0, int if K.backend() != 'tensorflow' else 'int32')] # the last state will correspond to the current timestep
return initial_states
def build(self, input_shape):
self.input_spec = [InputSpec(shape=input_shape)]
self.conv_layers = {c: [] for c in ['i', 'f', 'c', 'o', 'a', 'ahat']}
for l in range(self.nb_layers):
for c in ['i', 'f', 'c', 'o']:
act = self.LSTM_activation if c == 'c' else self.LSTM_inner_activation
self.conv_layers[c].append(Conv2D(self.R_stack_sizes[l], self.R_filt_sizes[l], padding='same', activation=act, data_format=self.data_format))
act = 'relu' if l == 0 else self.A_activation
self.conv_layers['ahat'].append(Conv2D(self.stack_sizes[l], self.Ahat_filt_sizes[l], padding='same', activation=act, data_format=self.data_format))
if l < self.nb_layers - 1:
self.conv_layers['a'].append(Conv2D(self.stack_sizes[l+1], self.A_filt_sizes[l], padding='same', activation=self.A_activation, data_format=self.data_format))
self.upsample = UpSampling2D(data_format=self.data_format)
self.pool = MaxPooling2D(data_format=self.data_format)
self.trainable_weights = []
nb_row, nb_col = (input_shape[-2], input_shape[-1]) if self.data_format == 'channels_first' else (input_shape[-3], input_shape[-2])
for c in sorted(self.conv_layers.keys()):
for l in range(len(self.conv_layers[c])):
ds_factor = 2 ** l
if c == 'ahat':
nb_channels = self.R_stack_sizes[l]
elif c == 'a':
nb_channels = 2 * self.R_stack_sizes[l]
else:
nb_channels = self.stack_sizes[l] * 2 + self.R_stack_sizes[l]
if l < self.nb_layers - 1:
nb_channels += self.R_stack_sizes[l+1]
in_shape = (input_shape[0], nb_channels, nb_row // ds_factor, nb_col // ds_factor)
if self.data_format == 'channels_last': in_shape = (in_shape[0], in_shape[2], in_shape[3], in_shape[1])
with K.name_scope('layer_' + c + '_' + str(l)):
self.conv_layers[c][l].build(in_shape)
self.trainable_weights += self.conv_layers[c][l].trainable_weights
self.states = [None] * self.nb_layers*3
if self.extrap_start_time is not None:
self.t_extrap = K.variable(self.extrap_start_time, int if K.backend() != 'tensorflow' else 'int32')
self.states += [None] * 2 # [previous frame prediction, timestep]
def step(self, a, states):
r_tm1 = states[:self.nb_layers]
c_tm1 = states[self.nb_layers:2*self.nb_layers]
e_tm1 = states[2*self.nb_layers:3*self.nb_layers]
if self.extrap_start_time is not None:
t = states[-1]
a = K.switch(t >= self.t_extrap, states[-2], a) # if past self.extrap_start_time, the previous prediction will be treated as the actual
c = []
r = []
e = []
# Update R units starting from the top
for l in reversed(range(self.nb_layers)):
inputs = [r_tm1[l], e_tm1[l]]
if l < self.nb_layers - 1:
inputs.append(r_up)
inputs = K.concatenate(inputs, axis=self.channel_axis)
i = self.conv_layers['i'][l].call(inputs)
f = self.conv_layers['f'][l].call(inputs)
o = self.conv_layers['o'][l].call(inputs)
_c = f * c_tm1[l] + i * self.conv_layers['c'][l].call(inputs)
_r = o * self.LSTM_activation(_c)
c.insert(0, _c)
r.insert(0, _r)
if l > 0:
r_up = self.upsample.call(_r)
# Update feedforward path starting from the bottom
for l in range(self.nb_layers):
ahat = self.conv_layers['ahat'][l].call(r[l])
if l == 0:
ahat = K.minimum(ahat, self.pixel_max)
frame_prediction = ahat
# compute errors
e_up = self.error_activation(ahat - a)
e_down = self.error_activation(a - ahat)
e.append(K.concatenate((e_up, e_down), axis=self.channel_axis))
if self.output_layer_num == l:
if self.output_layer_type == 'A':
output = a
elif self.output_layer_type == 'Ahat':
output = ahat
elif self.output_layer_type == 'R':
output = r[l]
elif self.output_layer_type == 'E':
output = e[l]
if l < self.nb_layers - 1:
a = self.conv_layers['a'][l].call(e[l])
a = self.pool.call(a) # target for next layer
if self.output_layer_type is None:
if self.output_mode == 'prediction':
output = frame_prediction
else:
for l in range(self.nb_layers):
layer_error = K.mean(K.batch_flatten(e[l]), axis=-1, keepdims=True)
all_error = layer_error if l == 0 else K.concatenate((all_error, layer_error), axis=-1)
if self.output_mode == 'error':
output = all_error
else:
output = K.concatenate((K.batch_flatten(frame_prediction), all_error), axis=-1)
states = r + c + e
if self.extrap_start_time is not None:
states += [frame_prediction, t + 1]
return output, states
def get_config(self):
config = {'stack_sizes': self.stack_sizes,
'R_stack_sizes': self.R_stack_sizes,
'A_filt_sizes': self.A_filt_sizes,
'Ahat_filt_sizes': self.Ahat_filt_sizes,
'R_filt_sizes': self.R_filt_sizes,
'pixel_max': self.pixel_max,
'error_activation': self.error_activation.__name__,
'A_activation': self.A_activation.__name__,
'LSTM_activation': self.LSTM_activation.__name__,
'LSTM_inner_activation': self.LSTM_inner_activation.__name__,
'data_format': self.data_format,
'extrap_start_time': self.extrap_start_time,
'output_mode': self.output_mode}
base_config = super(PredNet, self).get_config()
return dict(list(base_config.items()) + list(config.items()))

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{"class_name": "Model", "config": {"name": "model_1", "layers": [{"name": "input_1", "class_name": "InputLayer", "config": {"batch_input_shape": [null, 24, 20, 40, 12], "dtype": "float32", "sparse": false, "name": "input_1"}, "inbound_nodes": []}, {"name": "pred_net_1", "class_name": "PredNet", "config": {"name": "pred_net_1", "trainable": true, "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "implementation": 0, "stack_sizes": [12, 48, 96], "R_stack_sizes": [12, 48, 96], "A_filt_sizes": [3, 3], "Ahat_filt_sizes": [3, 3, 3], "R_filt_sizes": [3, 3, 3], "pixel_max": 1.0, "error_activation": "relu", "A_activation": "relu", "LSTM_activation": "tanh", "LSTM_inner_activation": "hard_sigmoid", "data_format": "channels_last", "extrap_start_time": null, "output_mode": "error"}, "inbound_nodes": [[["input_1", 0, 0, {}]]]}, {"name": "time_distributed_1", "class_name": "TimeDistributed", "config": {"name": "time_distributed_1", "trainable": false, "layer": {"class_name": "Dense", "config": {"name": "dense_1", "trainable": false, "units": 1, "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"scale": 1.0, "mode": "fan_avg", "distribution": "uniform", "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}}}, "inbound_nodes": [[["pred_net_1", 0, 0, {}]]]}, {"name": "flatten_1", "class_name": "Flatten", "config": {"name": "flatten_1", "trainable": true, "data_format": "channels_last"}, "inbound_nodes": [[["time_distributed_1", 0, 0, {}]]]}, {"name": "dense_2", "class_name": "Dense", "config": {"name": "dense_2", "trainable": false, "units": 1, "activation": "linear", "use_bias": true, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"scale": 1.0, "mode": "fan_avg", "distribution": "uniform", "seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "inbound_nodes": [[["flatten_1", 0, 0, {}]]]}], "input_layers": [["input_1", 0, 0]], "output_layers": [["dense_2", 0, 0]]}, "keras_version": "2.2.0", "backend": "tensorflow"}

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,STATION_ID,LAT_SCALED,LON_SCALED
0,WBAN:00184,16,22
1,WBAN:14929,3,18
2,WBAN:13962,14,17
3,WBAN:94975,5,17
4,WBAN:14813,7,30
5,WBAN:53864,14,26
6,WBAN:23061,10,13
7,WBAN:54921,6,18
8,WBAN:00258,12,12
9,WBAN:24044,6,15
10,WBAN:03049,16,14
11,WBAN:94299,6,2
12,WBAN:53933,10,18
13,WBAN:23047,12,16
14,WBAN:63811,12,28
15,WBAN:00137,11,13
16,WBAN:04864,3,24
17,WBAN:12832,17,27
18,WBAN:93730,8,35
19,WBAN:53932,12,19
20,WBAN:14605,4,38
21,WBAN:94281,3,1
22,WBAN:54817,4,29
23,WBAN:53138,8,7
24,WBAN:24130,3,4
25,WBAN:23155,12,3
26,WBAN:14606,3,39
27,WBAN:14616,4,39
28,WBAN:54833,5,24
30,WBAN:00282,2,14
31,WBAN:94947,7,19
32,WBAN:00127,18,18
33,WBAN:00224,4,2
34,WBAN:54781,5,36
35,WBAN:03044,14,16
36,WBAN:24033,3,11
37,WBAN:04725,6,34
38,WBAN:23157,10,4
39,WBAN:24011,2,16
40,WBAN:00286,4,23
41,WBAN:53881,10,31
42,WBAN:03036,10,10
43,WBAN:94793,7,37
44,WBAN:23225,8,2
45,WBAN:03859,10,30
46,WBAN:23158,13,6
47,WBAN:00263,17,18
48,WBAN:24131,5,5
49,WBAN:63871,16,27
50,WBAN:14739,6,37
51,WBAN:00310,0,5
52,WBAN:93808,10,26
53,WBAN:00353,5,11
54,WBAN:24132,3,9
55,WBAN:00451,10,21
56,WBAN:00435,18,20
57,WBAN:00433,9,3
58,WBAN:24180,6,8
59,WBAN:94946,6,17
60,WBAN:94902,4,19
61,WBAN:03721,13,32
62,WBAN:23159,10,8
63,WBAN:94037,3,14
64,WBAN:94054,4,12
65,WBAN:03068,9,14
66,WBAN:04866,5,25
67,WBAN:94282,0,1
68,WBAN:14742,4,36
69,WBAN:14817,4,27
70,WBAN:54743,7,35
72,WBAN:12986,17,19
73,WBAN:23136,13,3
74,WBAN:54923,3,19
75,WBAN:00285,0,17
76,WBAN:93729,12,34
77,WBAN:93810,10,24
78,WBAN:03177,14,4
80,WBAN:24089,5,12
81,WBAN:00465,6,32
82,WBAN:00283,0,18
83,WBAN:53887,9,24
84,WBAN:24017,5,15
85,WBAN:04114,4,7
86,WBAN:94943,4,17
87,WBAN:13880,14,31
88,WBAN:13866,9,30
89,WBAN:00143,8,15
90,WBAN:93203,8,1
91,WBAN:13301,8,22
92,WBAN:53916,8,21
93,WBAN:93104,11,4
94,WBAN:94605,2,38
95,WBAN:23051,11,14
97,WBAN:14820,6,30
98,WBAN:03027,12,13
99,WBAN:00222,9,21
100,WBAN:23008,13,14
101,WBAN:12867,18,30
102,WBAN:24045,4,10
103,WBAN:24136,1,5
104,WBAN:00276,15,17
105,WBAN:53129,10,7
107,WBAN:03945,9,22
109,WBAN:13812,8,29
110,WBAN:13984,8,18
111,WBAN:94057,5,13
113,WBAN:04141,5,0
114,WBAN:00234,11,23
115,WBAN:04908,7,20
116,WBAN:94977,0,22
117,WBAN:24286,6,0
118,WBAN:04915,7,21
119,WBAN:03073,15,20
120,WBAN:00287,0,14
121,WBAN:03847,11,27
123,WBAN:93798,9,32
124,WBAN:00316,3,22
125,WBAN:94032,4,14
126,WBAN:24137,0,8
127,WBAN:23161,12,5
128,WBAN:24219,3,2
129,WBAN:54734,6,35
130,WBAN:94704,5,32
131,WBAN:04223,0,2
133,WBAN:04871,6,25
134,WBAN:53925,13,21
135,WBAN:03976,16,21
136,WBAN:53964,13,18
137,WBAN:04916,5,23
138,WBAN:22001,17,16
139,WBAN:00315,7,29
140,WBAN:23162,8,8
141,WBAN:23078,14,11
142,WBAN:00445,14,25
143,WBAN:04139,6,3
144,WBAN:14933,6,21
145,WBAN:03104,13,5
146,WBAN:53853,16,26
147,WBAN:24138,3,8
148,WBAN:00444,7,11
149,WBAN:04978,4,22
150,WBAN:13985,10,17
151,WBAN:93026,15,10
152,WBAN:13707,8,34
153,WBAN:54786,7,34
154,WBAN:54844,2,28
155,WBAN:04787,7,32
156,WBAN:00443,5,10
158,WBAN:03070,11,15
159,WBAN:14747,5,31
160,WBAN:00298,5,29
161,WBAN:03809,11,24
164,WBAN:00254,18,22
165,WBAN:14991,3,23
166,WBAN:23114,12,4
167,WBAN:93816,8,25
168,WBAN:93992,14,22
169,WBAN:23044,15,12
170,WBAN:00182,2,20
171,WBAN:13786,11,34
172,WBAN:00210,11,29
173,WBAN:93076,10,15
174,WBAN:03733,8,31
176,WBAN:24220,1,2
177,WBAN:24006,4,15
178,WBAN:14748,6,33
180,WBAN:13989,9,19
181,WBAN:53986,11,18
182,WBAN:24141,1,3
183,WBAN:94853,3,26
184,WBAN:94971,5,20
185,WBAN:00304,18,23
186,WBAN:24221,4,0
189,WBAN:04111,7,9
190,WBAN:24114,1,4
191,WBAN:00220,13,30
192,WBAN:04925,7,22
193,WBAN:94056,3,15
194,WBAN:00270,18,17
196,WBAN:94957,8,20
197,WBAN:94969,4,21
198,WBAN:23090,10,11
199,WBAN:93996,10,23
200,WBAN:03707,10,32
201,WBAN:53922,11,21
202,WBAN:13762,10,34
203,WBAN:94966,2,19
204,WBAN:00326,16,30
205,WBAN:00237,2,22
206,WBAN:14825,7,28
207,WBAN:04780,5,37
209,WBAN:53889,9,25
210,WBAN:13829,14,27
211,WBAN:00449,6,9
212,WBAN:13806,11,26
214,WBAN:94933,5,21
216,WBAN:00162,7,14
217,WBAN:63847,12,27
218,WBAN:12895,19,31
219,WBAN:53988,15,22
220,WBAN:13947,8,19
221,WBAN:53861,15,27
222,WBAN:13964,12,21
223,WBAN:03875,15,30
224,WBAN:23091,16,15
225,WBAN:14827,7,27
226,WBAN:04929,1,20
227,WBAN:53841,9,27
228,WBAN:54818,4,26
229,WBAN:00152,3,36
230,WBAN:94868,6,31
231,WBAN:03981,13,17
232,WBAN:93947,16,17
233,WBAN:03706,9,33
234,WBAN:04876,6,24
235,WBAN:04924,6,19
236,WBAN:04836,1,39
237,WBAN:93193,10,3
238,WBAN:94276,0,0
240,WBAN:54772,4,37
241,WBAN:00265,7,26
242,WBAN:03896,13,27
243,WBAN:13975,11,17
244,WBAN:03056,14,15
245,WBAN:93764,8,33
246,WBAN:94959,7,23
247,WBAN:12993,17,24
248,WBAN:23081,12,10
249,WBAN:23064,9,16
250,WBAN:94041,1,16
251,WBAN:04807,6,26
252,WBAN:53870,12,30
253,WBAN:04854,3,28
254,WBAN:00391,13,31
255,WBAN:13764,9,34
256,WBAN:53982,14,20
257,WBAN:94008,0,12
258,WBAN:00361,10,27
260,WBAN:24087,1,13
261,WBAN:14750,5,35
262,WBAN:00135,9,1
263,WBAN:53893,13,25
264,WBAN:03708,12,32
265,WBAN:23065,8,16
266,WBAN:04994,0,20
267,WBAN:14829,6,27
268,WBAN:53977,14,18
269,WBAN:03195,11,8
270,WBAN:14916,1,19
271,WBAN:23066,8,11
272,WBAN:94992,1,24
273,WBAN:94919,1,21
274,WBAN:04999,3,20
275,WBAN:00481,9,8
276,WBAN:00387,4,3
277,WBAN:93057,12,11
278,WBAN:24201,1,1
279,WBAN:53967,13,19
280,WBAN:24143,1,9
281,WBAN:04880,7,25
282,WBAN:24051,7,13
283,WBAN:14898,4,25
284,WBAN:13723,11,31
285,WBAN:13939,13,23
286,WBAN:63874,15,26
287,WBAN:94626,3,38
288,WBAN:13926,14,19
289,WBAN:53874,13,29
291,WBAN:24048,4,11
293,WBAN:14976,6,22
294,WBAN:03870,12,29
295,WBAN:54819,6,29
296,WBAN:53941,11,20
298,WBAN:53913,11,19
299,WBAN:03030,11,16
300,WBAN:94836,2,26
301,WBAN:00150,2,18
302,WBAN:00221,12,8
303,WBAN:00186,16,25
304,WBAN:93706,8,32
305,WBAN:94161,5,7
306,WBAN:00231,11,33
307,WBAN:53938,12,18
308,WBAN:53855,8,28
309,WBAN:00357,15,18
310,WBAN:03908,16,23
311,WBAN:00154,10,33
312,WBAN:14858,1,25
313,WBAN:53119,11,3
315,WBAN:00455,8,23
316,WBAN:04884,3,27
317,WBAN:04936,6,20
318,WBAN:00159,9,12
319,WBAN:14751,7,33
320,WBAN:13971,11,22
321,WBAN:00431,14,21
322,WBAN:14752,6,36
323,WBAN:00219,12,31
324,WBAN:00322,1,17
326,WBAN:94012,0,10
327,WBAN:03167,13,4
328,WBAN:94025,7,12
330,WBAN:93228,10,1
331,WBAN:94973,2,23
332,WBAN:53973,16,19
333,WBAN:00337,14,29
334,WBAN:04998,7,18
335,WBAN:24144,2,8
336,WBAN:53886,10,25
337,WBAN:03711,11,32
338,WBAN:00250,15,28
340,WBAN:04113,3,3
341,WBAN:94038,2,15
342,WBAN:94931,1,22
343,WBAN:03810,11,30
344,WBAN:00306,17,21
345,WBAN:00260,18,21
346,WBAN:93990,8,17
347,WBAN:53972,15,19
348,WBAN:63837,14,30
349,WBAN:93986,12,17
350,WBAN:93034,14,14
352,WBAN:00392,10,2
353,WBAN:23002,14,12
355,WBAN:00163,7,15
356,WBAN:00128,15,29
357,WBAN:12962,17,17
358,WBAN:00429,9,11
359,WBAN:94225,2,0
360,WBAN:00225,16,18
361,WBAN:03962,13,22
362,WBAN:93757,9,31
363,WBAN:14609,2,39
364,WBAN:12927,17,23
365,WBAN:12918,17,20
366,WBAN:04887,5,28
367,WBAN:00484,4,13
368,WBAN:53896,9,26
369,WBAN:03860,9,29
370,WBAN:63804,12,26
371,WBAN:53903,16,20
372,WBAN:14936,4,18
373,WBAN:13986,9,18
374,WBAN:04933,3,21
375,WBAN:00291,0,19
376,WBAN:94720,6,38
377,WBAN:53990,13,20
378,WBAN:00452,2,5
379,WBAN:24145,5,8
380,WBAN:93115,14,5
381,WBAN:03144,14,6
382,WBAN:24091,7,16
383,WBAN:00141,10,20
385,WBAN:64706,7,31
386,WBAN:93819,8,26
387,WBAN:14918,0,21
388,WBAN:00377,17,29
389,WBAN:00240,5,27
390,WBAN:14937,6,23
391,WBAN:54941,5,22
392,WBAN:94926,2,24
393,WBAN:04997,2,21
394,WBAN:04781,7,36
395,WBAN:94761,5,33
396,WBAN:00464,3,25
397,WBAN:00216,4,28
399,WBAN:24166,4,9
401,WBAN:03889,10,29
402,WBAN:03811,11,25
403,WBAN:04946,4,20
404,WBAN:14833,6,28
405,WBAN:93753,12,33
1 STATION_ID LAT_SCALED LON_SCALED
2 0 WBAN:00184 16 22
3 1 WBAN:14929 3 18
4 2 WBAN:13962 14 17
5 3 WBAN:94975 5 17
6 4 WBAN:14813 7 30
7 5 WBAN:53864 14 26
8 6 WBAN:23061 10 13
9 7 WBAN:54921 6 18
10 8 WBAN:00258 12 12
11 9 WBAN:24044 6 15
12 10 WBAN:03049 16 14
13 11 WBAN:94299 6 2
14 12 WBAN:53933 10 18
15 13 WBAN:23047 12 16
16 14 WBAN:63811 12 28
17 15 WBAN:00137 11 13
18 16 WBAN:04864 3 24
19 17 WBAN:12832 17 27
20 18 WBAN:93730 8 35
21 19 WBAN:53932 12 19
22 20 WBAN:14605 4 38
23 21 WBAN:94281 3 1
24 22 WBAN:54817 4 29
25 23 WBAN:53138 8 7
26 24 WBAN:24130 3 4
27 25 WBAN:23155 12 3
28 26 WBAN:14606 3 39
29 27 WBAN:14616 4 39
30 28 WBAN:54833 5 24
31 30 WBAN:00282 2 14
32 31 WBAN:94947 7 19
33 32 WBAN:00127 18 18
34 33 WBAN:00224 4 2
35 34 WBAN:54781 5 36
36 35 WBAN:03044 14 16
37 36 WBAN:24033 3 11
38 37 WBAN:04725 6 34
39 38 WBAN:23157 10 4
40 39 WBAN:24011 2 16
41 40 WBAN:00286 4 23
42 41 WBAN:53881 10 31
43 42 WBAN:03036 10 10
44 43 WBAN:94793 7 37
45 44 WBAN:23225 8 2
46 45 WBAN:03859 10 30
47 46 WBAN:23158 13 6
48 47 WBAN:00263 17 18
49 48 WBAN:24131 5 5
50 49 WBAN:63871 16 27
51 50 WBAN:14739 6 37
52 51 WBAN:00310 0 5
53 52 WBAN:93808 10 26
54 53 WBAN:00353 5 11
55 54 WBAN:24132 3 9
56 55 WBAN:00451 10 21
57 56 WBAN:00435 18 20
58 57 WBAN:00433 9 3
59 58 WBAN:24180 6 8
60 59 WBAN:94946 6 17
61 60 WBAN:94902 4 19
62 61 WBAN:03721 13 32
63 62 WBAN:23159 10 8
64 63 WBAN:94037 3 14
65 64 WBAN:94054 4 12
66 65 WBAN:03068 9 14
67 66 WBAN:04866 5 25
68 67 WBAN:94282 0 1
69 68 WBAN:14742 4 36
70 69 WBAN:14817 4 27
71 70 WBAN:54743 7 35
72 72 WBAN:12986 17 19
73 73 WBAN:23136 13 3
74 74 WBAN:54923 3 19
75 75 WBAN:00285 0 17
76 76 WBAN:93729 12 34
77 77 WBAN:93810 10 24
78 78 WBAN:03177 14 4
79 80 WBAN:24089 5 12
80 81 WBAN:00465 6 32
81 82 WBAN:00283 0 18
82 83 WBAN:53887 9 24
83 84 WBAN:24017 5 15
84 85 WBAN:04114 4 7
85 86 WBAN:94943 4 17
86 87 WBAN:13880 14 31
87 88 WBAN:13866 9 30
88 89 WBAN:00143 8 15
89 90 WBAN:93203 8 1
90 91 WBAN:13301 8 22
91 92 WBAN:53916 8 21
92 93 WBAN:93104 11 4
93 94 WBAN:94605 2 38
94 95 WBAN:23051 11 14
95 97 WBAN:14820 6 30
96 98 WBAN:03027 12 13
97 99 WBAN:00222 9 21
98 100 WBAN:23008 13 14
99 101 WBAN:12867 18 30
100 102 WBAN:24045 4 10
101 103 WBAN:24136 1 5
102 104 WBAN:00276 15 17
103 105 WBAN:53129 10 7
104 107 WBAN:03945 9 22
105 109 WBAN:13812 8 29
106 110 WBAN:13984 8 18
107 111 WBAN:94057 5 13
108 113 WBAN:04141 5 0
109 114 WBAN:00234 11 23
110 115 WBAN:04908 7 20
111 116 WBAN:94977 0 22
112 117 WBAN:24286 6 0
113 118 WBAN:04915 7 21
114 119 WBAN:03073 15 20
115 120 WBAN:00287 0 14
116 121 WBAN:03847 11 27
117 123 WBAN:93798 9 32
118 124 WBAN:00316 3 22
119 125 WBAN:94032 4 14
120 126 WBAN:24137 0 8
121 127 WBAN:23161 12 5
122 128 WBAN:24219 3 2
123 129 WBAN:54734 6 35
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