updates .Rmd and .py

python/gee-collection-acre-l5.py

@@ -0,0 +1,71 @@
+#!/usr/bin/env python
+
+import time
+import oauth2client
+import ee
+
+ee.Initialize()
+
+## Polygon area for extraction
+## Polygon area for extraction
+geom=ee.Geometry.Polygon(
+       [[[-72.050, -9.128],
+          [-72.050, -9.235],
+          [-71.916, -9.235],
+          [-71.916, -9.128]]])
+
+## Landsat 5 Collection
+l5=ee.ImageCollection('LANDSAT/LT05/C01/T1_SR').filterDate('1998-01-01', '2011-11-30').filterBounds(geom)
+
+def exportCollectionToDrive (userCollection,folderName):
+    userCollection2=userCollection#.map(toals)
+    imageList = ee.List(userCollection2.toList(userCollection2.size().add(1)))
+    length = userCollection2.size().getInfo()
+    print(length)
+
+
+    def exportImage(img):
+        fileName = ee.String(img.get('system:index')).getInfo()
+        fileGeometry = geom.bounds().getInfo()['coordinates'][0]
+        band=ee.Image(img).bandNames().get(0)
+        sc=30  ##pixel size
+
+        ## Masking
+        cloud=img.select('pixel_qa').bitwiseAnd(32).neq(0)
+        img=img.updateMask(cloud.Not())
+        cloud_shadow = img.select('pixel_qa').bitwiseAnd(8).neq(0)
+        img=img.updateMask(cloud_shadow.Not())
+
+        ##Check overlap
+        area=ee.Feature(geom).geometry().area()
+        imgarea=ee.Image(img).multiply(0).add(1).clip(geom).reduceRegion(
+            reducer= ee.Reducer.sum().unweighted(),
+            geometry= geom,
+            maxPixels= 1e12,
+            tileScale= 1,
+            scale=30)
+        imgp=ee.Number(imgarea.get(band)).multiply(sc).multiply(sc).divide(area)
+
+        ##Check for overlap
+        if imgp.getInfo()>=0.8:
+            task = ee.batch.Export.image.toDrive(
+                image = img.normalizedDifference(['B4', 'B3']).rename('NDVI').toFloat(),
+                description = fileName,
+                folder = 'gee-collection-acre-landsat5',
+                maxPixels = 1e13,
+                region = fileGeometry,
+                scale = 30)
+            task.start()
+
+
+    index = 0
+    while index < length:
+        print("Export #: " + str(index+1))
+        img2export = ee.Image(imageList.get(index))
+        exportImage(img2export)
+        index = index + 1
+        time.sleep(1) # sleep for 1 seconds
+
+    print('Finished exporting data')
+    print('')
+exportCollectionToDrive(userCollection=l5, folderName="gee-collection-acre-landsat5")

python/gee-collection-acre-l7.py

@@ -0,0 +1,70 @@
+#!/usr/bin/env python
+
+import time
+import oauth2client
+import ee
+
+ee.Initialize()
+
+## Polygon area for extraction
+geom=ee.Geometry.Polygon(
+       [[[-72.050, -9.128],
+          [-72.050, -9.235],
+          [-71.916, -9.235],
+          [-71.916, -9.128]]])
+
+## Landsat 7 Collection
+l7=ee.ImageCollection('LANDSAT/LE07/C01/T1_SR').filterDate('1999-01-01', '2018-09-30').filterBounds(geom)
+
+def exportCollectionToDrive (userCollection,folderName):
+    userCollection2=userCollection#.map(toals)
+    imageList = ee.List(userCollection2.toList(userCollection2.size().add(1)))
+    length = userCollection2.size().getInfo()
+    print(length)
+
+
+    def exportImage(img):
+        fileName = ee.String(img.get('system:index')).getInfo()
+        fileGeometry = geom.bounds().getInfo()['coordinates'][0]
+        band=ee.Image(img).bandNames().get(0)
+        sc=30  ##pixel size
+
+        ## Masking
+        cloud=img.select('pixel_qa').bitwiseAnd(32).neq(0)
+        img=img.updateMask(cloud.Not())
+        cloud_shadow = img.select('pixel_qa').bitwiseAnd(8).neq(0)
+        img=img.updateMask(cloud_shadow.Not())
+
+        ##Check overlap
+        area=ee.Feature(geom).geometry().area()
+        imgarea=ee.Image(img).multiply(0).add(1).clip(geom).reduceRegion(
+            reducer= ee.Reducer.sum().unweighted(),
+            geometry= geom,
+            maxPixels= 1e12,
+            tileScale= 1,
+            scale=30)
+        imgp=ee.Number(imgarea.get(band)).multiply(sc).multiply(sc).divide(area)
+
+        ##Check for overlap
+        if imgp.getInfo()>=0.7:
+            task = ee.batch.Export.image.toDrive(
+                image = img.normalizedDifference(['B4', 'B3']).rename('NDVI').toFloat(),
+                description = fileName,
+                folder = 'gee-collection-acre-landsat7',
+                maxPixels = 1e13,
+                region = fileGeometry,
+                scale = 30)
+            task.start()
+
+
+    index = 0
+    while index < length:
+        print("Export #: " + str(index+1))
+        img2export = ee.Image(imageList.get(index))
+        exportImage(img2export)
+        index = index + 1
+        time.sleep(1) # sleep for 1 seconds
+
+    print('Finished exporting data')
+    print('')
+exportCollectionToDrive(userCollection=l7, folderName="gee-collection-acre-landsat7")

python/gee-collection-acre-l8.py

@@ -0,0 +1,46 @@
+#!/usr/bin/env python
+
+import time
+import oauth2client
+import ee
+
+ee.Initialize()
+
+## Polygon area for extraction
+geom=ee.Geometry.Polygon(
+       [[[-72.050, -9.128],
+          [-72.050, -9.235],
+          [-71.916, -9.235],
+          [-71.916, -9.128]]])
+
+l8=ee.ImageCollection('LANDSAT/LC08/C01/T1_SR').filterDate('2013-01-01', '2018-08-30').filterBounds(geom)
+
+def exportCollectionToDrive (userCollection,folderName):
+    userCollection2=userCollection#.map(toals)
+    imageList = ee.List(userCollection2.toList(userCollection2.size().add(1)))
+    length = userCollection2.size().getInfo()
+    print(length)
+
+    def exportImage(img):
+        fileName = ee.String(img.get('system:index')).getInfo()
+        fileGeometry = geom.bounds().getInfo()['coordinates'][0]
+        task = ee.batch.Export.image.toDrive(
+            image = img.normalizedDifference(['B5', 'B4']).rename('NDVI').toFloat(),
+            description = fileName,
+            folder = 'gee-collection-acre-landsat8',
+            maxPixels = 1e13,
+            region = fileGeometry,
+            scale = 30)
+        task.start()
+
+    index = 0
+    while index < length:
+        print("Export #: " + str(index+1))
+        img2export = ee.Image(imageList.get(index))
+        exportImage(img2export)
+        index = index + 1
+        time.sleep(5)
+
+    print('Finished exporting data')
+    print('')
+exportCollectionToDrive(userCollection=l8, folderName="gee-collection-acre-landsat8")

python/gee-collection-okavango-l5.py

@@ -0,0 +1,71 @@
+#!/usr/bin/env python
+
+import time
+import oauth2client
+import ee
+
+ee.Initialize()
+
+## Polygon area for extraction
+## Polygon area for extraction
+geom=ee.Geometry.Polygon(
+       [[[21.870, -18.730],
+          [21.870, -19.510],
+          [22.840, -19.510],
+          [22.840, -18.730]]])
+
+## Landsat 5 Collection
+l5=ee.ImageCollection('LANDSAT/LT05/C01/T1_SR').filterDate('1984-01-01', '1997-12-31').filterBounds(geom)
+
+def exportCollectionToDrive (userCollection,folderName):
+    userCollection2=userCollection#.map(toals)
+    imageList = ee.List(userCollection2.toList(userCollection2.size().add(1)))
+    length = userCollection2.size().getInfo()
+    print(length)
+
+
+    def exportImage(img):
+        fileName = ee.String(img.get('system:index')).getInfo()
+        fileGeometry = geom.bounds().getInfo()['coordinates'][0]
+        band=ee.Image(img).bandNames().get(0)
+        sc=30  ##pixel size
+
+        ## Masking
+        cloud=img.select('pixel_qa').bitwiseAnd(32).neq(0)
+        img=img.updateMask(cloud.Not())
+        cloud_shadow = img.select('pixel_qa').bitwiseAnd(8).neq(0)
+        img=img.updateMask(cloud_shadow.Not())
+
+        ##Check overlap
+        area=ee.Feature(geom).geometry().area()
+        imgarea=ee.Image(img).multiply(0).add(1).clip(geom).reduceRegion(
+            reducer= ee.Reducer.sum().unweighted(),
+            geometry= geom,
+            maxPixels= 1e12,
+            tileScale= 1,
+            scale=30)
+        imgp=ee.Number(imgarea.get(band)).multiply(sc).multiply(sc).divide(area)
+
+        ##Check for overlap
+        if imgp.getInfo()>=0.8:
+            task = ee.batch.Export.image.toDrive(
+                image = img.normalizedDifference(['B4', 'B3']).rename('NDVI').toFloat(),
+                description = fileName,
+                folder = 'gee-collection-okavango-landsat5',
+                maxPixels = 1e13,
+                region = fileGeometry,
+                scale = 30)
+            task.start()
+
+
+    index = 0
+    while index < length:
+        print("Export #: " + str(index+1))
+        img2export = ee.Image(imageList.get(index))
+        exportImage(img2export)
+        index = index + 1
+        time.sleep(1) # sleep for 1 seconds
+
+    print('Finished exporting data')
+    print('')
+exportCollectionToDrive(userCollection=l5, folderName="gee-collection-okavango-landsat5")

python/gee-collection-okavango-l7.py

@@ -0,0 +1,70 @@
+#!/usr/bin/env python
+
+import time
+import oauth2client
+import ee
+
+ee.Initialize()
+
+## Polygon area for extraction
+geom=ee.Geometry.Polygon(
+       [[[21.870, -18.730],
+          [21.870, -19.510],
+          [22.840, -19.510],
+          [22.840, -18.730]]])
+
+## Landsat 7 Collection
+l7=ee.ImageCollection('LANDSAT/LE07/C01/T1_SR').filterDate('1999-01-01', '2018-09-30').filterBounds(geom)
+
+def exportCollectionToDrive (userCollection,folderName):
+    userCollection2=userCollection#.map(toals)
+    imageList = ee.List(userCollection2.toList(userCollection2.size().add(1)))
+    length = userCollection2.size().getInfo()
+    print(length)
+
+
+    def exportImage(img):
+        fileName = ee.String(img.get('system:index')).getInfo()
+        fileGeometry = geom.bounds().getInfo()['coordinates'][0]
+        band=ee.Image(img).bandNames().get(0)
+        sc=30  ##pixel size
+
+        ## Masking
+        cloud=img.select('pixel_qa').bitwiseAnd(32).neq(0)
+        img=img.updateMask(cloud.Not())
+        cloud_shadow = img.select('pixel_qa').bitwiseAnd(8).neq(0)
+        img=img.updateMask(cloud_shadow.Not())
+
+        ##Check overlap
+        area=ee.Feature(geom).geometry().area()
+        imgarea=ee.Image(img).multiply(0).add(1).clip(geom).reduceRegion(
+            reducer= ee.Reducer.sum().unweighted(),
+            geometry= geom,
+            maxPixels= 1e12,
+            tileScale= 1,
+            scale=30)
+        imgp=ee.Number(imgarea.get(band)).multiply(sc).multiply(sc).divide(area)
+
+        ##Check for overlap
+        if imgp.getInfo()>=0.7:
+            task = ee.batch.Export.image.toDrive(
+                image = img.normalizedDifference(['B4', 'B3']).rename('NDVI').toFloat(),
+                description = fileName,
+                folder = 'gee-collection-okavango-landsat7',
+                maxPixels = 1e13,
+                region = fileGeometry,
+                scale = 30)
+            task.start()
+
+
+    index = 0
+    while index < length:
+        print("Export #: " + str(index+1))
+        img2export = ee.Image(imageList.get(index))
+        exportImage(img2export)
+        index = index + 1
+        time.sleep(1) # sleep for 1 seconds
+
+    print('Finished exporting data')
+    print('')
+exportCollectionToDrive(userCollection=l7, folderName="gee-collection-okavango-landsat7")

python/gee-collection-okavango-l8.py

@@ -0,0 +1,45 @@
+#!/usr/bin/env python
+
+import time
+import oauth2client
+import ee
+
+ee.Initialize()
+
+geom=ee.Geometry.Polygon(
+        [[[21.870, -18.730],
+          [21.870, -19.510],
+          [22.840, -19.510],
+          [22.840, -18.730]]])
+
+l8=ee.ImageCollection('LANDSAT/LC08/C01/T1_SR').filterDate('2013-01-01', '2018-08-30').filterBounds(geom)
+
+def exportCollectionToDrive (userCollection,folderName):
+    userCollection2=userCollection#.map(toals)
+    imageList = ee.List(userCollection2.toList(userCollection2.size().add(1)))
+    length = userCollection2.size().getInfo()
+    print(length)
+
+    def exportImage(img):
+        fileName = ee.String(img.get('system:index')).getInfo()
+        fileGeometry = geom.bounds().getInfo()['coordinates'][0]
+        task = ee.batch.Export.image.toDrive(
+            image = img.normalizedDifference(['B5', 'B4']).rename('NDVI').toFloat(),
+            description = fileName,
+            folder = 'gee-collection-okavango-landsat8',
+            maxPixels = 1e13,
+            region = fileGeometry,
+            scale = 30)
+        task.start()
+
+    index = 0
+    while index < length:
+        print("Export #: " + str(index+1))
+        img2export = ee.Image(imageList.get(index))
+        exportImage(img2export)
+        index = index + 1
+        time.sleep(5)
+
+    print('Finished exporting data')
+    print('')
+exportCollectionToDrive(userCollection=l8, folderName="gee-collection-okavango-landsat8")

python/gee-collection-usmex-l5.py

@@ -15,7 +15,7 @@
           [-110.700, 31.429]]])
 
 ## Landsat 5 Collection
-l5=ee.ImageCollection('LANDSAT/LT05/C01/T1_SR').filterDate('1984-05-01', '2011-11-30').filterBounds(geom)
+l5=ee.ImageCollection('LANDSAT/LT05/C01/T1_SR').filterDate('1998-01-01', '2011-11-30').filterBounds(geom)
 
 def exportCollectionToDrive (userCollection,folderName):
     userCollection2=userCollection#.map(toals)
@@ -47,7 +47,7 @@ def exportImage(img):
         imgp=ee.Number(imgarea.get(band)).multiply(sc).multiply(sc).divide(area)
 
         ##Check for overlap
-        if imgp.getInfo()>=0.7:
+        if imgp.getInfo()>=0.8:
             task = ee.batch.Export.image.toDrive(
                 image = img.normalizedDifference(['B4', 'B3']).rename('NDVI').toFloat(),
                 description = fileName,