blogs/landsat/ndvi.py

#!/usr/bin/env python

"""
Copyright Google Inc. 2016
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""

import sys
import osgeo.gdal as gdal
import os
import os.path
import subprocess
import struct
import numpy as np
import tempfile

class LandsatReader():
   def __init__(self, gsdir, band, destdir):
      basename = os.path.basename(gsdir)
      self.gsfile = '{0}/{1}_{2}.TIF'.format(gsdir, basename, band)
      self.dest = os.path.join(destdir, os.path.basename(self.gsfile))

   def __enter__(self):
      print 'Getting {0} to {1} '.format(self.gsfile, self.dest)
      ret = subprocess.check_call(['gsutil', 'cp', self.gsfile, self.dest])
      if ret == 0:
         dataset = gdal.Open( self.dest, gdal.GA_ReadOnly )
         return dataset
      else:
         return None

   def __exit__(self, exc_type=None, exc_val=None, exc_tb=None):
      os.remove( self.dest ) # cleanup


def computeNdvi(gs_baseurl, outdir, instrument):
  if instrument is 'LANDSAT_7':
     band1 = 'B3'
     band2 = 'B4'
  else:
     band1 = 'B4'
     band2 = 'B5'

  with LandsatReader(gs_baseurl, band1, '.') as red_ds, \
     LandsatReader(gs_baseurl, band2, '.') as nir_ds :

     outdtype = gdal.GDT_Float32  # gdal.GDT_Byte

     tmpfilename = os.path.join(tempfile.gettempdir(), '{0}_ndvi.TIF'.format(os.path.basename(gs_baseurl)) )
     driver = gdal.GetDriverByName('GTiff')
     outds = driver.Create(tmpfilename, red_ds.RasterXSize, red_ds.RasterYSize, 1, outdtype)
     outds.SetGeoTransform(red_ds.GetGeoTransform())
     outds.SetProjection(red_ds.GetProjection())

     red = red_ds.GetRasterBand(1)
     nir = nir_ds.GetRasterBand(1)
     packformat = 'f' * red.XSize
     for line in xrange(0, red.YSize):
         red_data = struct.unpack(packformat, red.ReadRaster(0, line, red.XSize, 1, red.XSize, 1, gdal.GDT_Float32)) 
         nir_data = struct.unpack(packformat, nir.ReadRaster(0, line, nir.XSize, 1, nir.XSize, 1, gdal.GDT_Float32))
         ndvi_scaled = np.array([255] * red.XSize, dtype=np.float32)   # mask value

         for i in xrange(0, len(red_data)):
             ndvi_denom = nir_data[i] + red_data[i]
             ndvi_num = nir_data[i] - red_data[i]
             if ndvi_denom != 0:
                ndvi = (ndvi_num/ndvi_denom)  # -1 to 1
                ndvi_scaled[i] = int(0.5 + 100*ndvi) if ndvi > 0 else 0  # 0-100
         outline = struct.pack(packformat, *ndvi_scaled)
         outds.GetRasterBand(1).WriteRaster(0, line, red.XSize, 1, outline, buf_xsize=red.XSize, buf_ysize=1, buf_type=outdtype)
         del outline
     outds = None # close

     outfilename = os.path.join(outdir, '{0}_ndvi.TIF'.format(os.path.basename(gs_baseurl)) )
     ret = subprocess.check_call(['gsutil', 'mv', tmpfilename, outfilename])
     print 'Wrote {0} ...'.format(outfilename)

if __name__ == '__main__':
   computeNdvi('gs://gcp-public-data-landsat/LE07/PRE/198/057/LE71980572015351ASN00', 'gs://cloud-training-demos/landsat/', 'LANDSAT_7') # cape palmas
   computeNdvi('gs://gcp-public-data-landsat/LC08/PRE/153/075/LC81530752015348LGN00', 'gs://cloud-training-demos/landsat/', 'LANDSAT_8') # reunion