KMarkert

import os
import glob
import urllib2
import numpy as np

outFolder = "J:/africa_srtm/org_zip/" #change output path

lats = np.arange(-35,33)#change lat bounds
lons = np.arange(-18,52)#change lon bounds

KMarkert

import datetime
import xmltodict
import numpy as np
import pandas as pd

"""
XML metata data file is take from https://landsat.usgs.gov/landsat-bulk-metadata-service
"""

# Define input files

KMarkert

#*****************************************************************************
# FILE: grid_amsrL2Swath.py
# AUTHOR: Kel Markert
# EMAIL: kel.markert@uah.edu
# MODIFIED BY: N/A
# ORGANIZATION: UAH/ESSC
# CREATION DATE: 02/10/2017
# LAST MOD DATE: 02/11/2017
# PURPOSE: This scripts takes LANCE L2 swath AMSR2 data from GHRC, grids the
#           data, and outputs a geotiff

KMarkert

import numpy as np

def dd2meters(inPt,scale=0.1):
    """Function to convert decimal degrees to meters based on the approximation
    given by: https://en.wikipedia.org/wiki/Geographic_coordinate_system
    
    Args:
        inPt (list or array): A Y,X point provided in geographic coordinates
        in that order.

KMarkert

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
vrg2timeseries.py, SERVIR-Mekong (2017-07-26)

Downloads data from SERVIR-Mekong's Virtual Rain and Stream Gauge (VRSG) 
(vrsg-servir.adpc.net) and calculates a time series of the daily data over 
an area
______________________________________________________________________

KMarkert

import math

def dd2dms(dd):
  if dd < 0:
    degrees = math.ceil(dd)
  else:
   degrees = math.floor(dd)

  minutes = 60 * (dd%1)
  seconds = 60 * (minutes%1)

KMarkert

import os
import fire
import h5py
import glob
import tqdm
import numpy as np
import pandas as pd
# requires h5py, tqdm, fire, numpy, and pandas to run

KMarkert

import os
import fire
import h5py
import glob
import tqdm
import numpy as np
import pandas as pd
import geopandas as gpd
# requires fire, h5py, tqdm, numpy, pandas, and geopandas

KMarkert

KMarkert

import os
import fire
import numpy as np
from osgeo import gdal
from scipy import ndimage
import dask.array as da

import tensorflow as tf
from tensorflow.python import keras
from tensorflow.python.keras import layers