def getCloudFreeModis(bounds, targetDate, maxRangeDays=10, maxCloudPercentage=0.05,
searchMethod='spiral'):
'''Search for the closest cloud-free MODIS image near the target date.
The result preference is determined by searchMethod and can be set to:
spiral, increasing, or decreasing'''
# Get the date range to search
if searchMethod == 'spiral':
dateStart = targetDate.advance(-1*maxRangeDays, 'day')
dateEnd = targetDate.advance( maxRangeDays, 'day')
else:
dateStart = targetDate
dateEnd = targetDate.advance( maxRangeDays, 'day')
# Get a list of candidate images
imageCollection = get_image_collection_modis(bounds, dateStart, dateEnd)
imageList = imageCollection.toList(100)
imageInfo = imageList.getInfo()
# Find the first image with a low cloud percentage
numFound = len(imageInfo)
if searchMethod == 'spiral':
searchIndices = miscUtilities.getExpandingIndices(numFound)
elif searchMethod == 'increasing':
searchIndices = range(0,numFound)
else:
searchIndices = range(numFound-1, -1, -1)
for i in searchIndices:
thisImage = ee.Image(imageList.get(i)).resample('bicubic')
cloudPercentage = cmt.modis.modis_utilities.getCloudPercentage(thisImage, bounds)
print 'Detected MODIS cloud percentage: ' + str(cloudPercentage)
if cloudPercentage < maxCloudPercentage:
return thisImage
raise Exception('Could not find a nearby cloud-free MODIS image for date ' + str(targetDate.getInfo()))
def getCloudFreeLandsat(bounds,
targetDate,
maxRangeDays=10,
maxCloudPercentage=0.05,
searchMethod='spiral'):
'''Search for the closest cloud-free Landsat image near the target date.
The result preference is determined by searchMethod and can be set to:
spiral, increasing, or decreasing'''
# Get the date range to search
if searchMethod == 'spiral':
dateStart = targetDate.advance(-1 * maxRangeDays, 'day')
dateEnd = targetDate.advance(maxRangeDays, 'day')
else:
dateStart = targetDate
dateEnd = targetDate.advance(maxRangeDays, 'day')
# Try each of the satellites in decreasing order of quality
collectionNames = ['LC8_L1T_TOA', 'LT5_L1T_TOA', 'LE7_L1T_TOA']
for name in collectionNames:
# Get candidate images for this sensor
imageCollection = get_image_collection_landsat(bounds, dateStart,
dateEnd, name)
imageList = imageCollection.toList(100)
imageInfo = imageList.getInfo()
# Find the first image with a low cloud percentage
numFound = len(imageInfo)
if searchMethod == 'spiral':
searchIndices = miscUtilities.getExpandingIndices(numFound)
elif searchMethod == 'increasing':
searchIndices = range(0, numFound)
else:
searchIndices = range(numFound - 1, -1, -1)
for i in searchIndices:
thisImage = ee.Image(imageList.get(i)).resample('bicubic')
cloudPercentage = cmt.util.landsat_functions.getCloudPercentage(
thisImage, bounds)
print 'Detected Landsat cloud percentage: ' + str(cloudPercentage)
if cloudPercentage < maxCloudPercentage:
return thisImage
# If we got here this satellite did not produce a good image, try the next satellite.
raise Exception(
'Could not find a nearby cloud-free Landsat image for date ' +
str(targetDate.getInfo()))
def getCloudFreeModis(bounds, targetDate, maxRangeDays=10, maxCloudPercentage=0.05,
minCoverage=0.8, searchMethod='spiral'):
'''Search for the closest cloud-free MODIS image near the target date.
The result preference is determined by searchMethod and can be set to:
spiral, increasing, or decreasing'''
# Get the date range to search
if searchMethod == 'spiral':
dateStart = targetDate.advance(-1*maxRangeDays, 'day')
dateEnd = targetDate.advance( maxRangeDays, 'day')
else:
dateStart = targetDate
dateEnd = targetDate.advance( maxRangeDays, 'day')
# Get a list of candidate images
imageCollection = get_image_collection_modis(bounds, dateStart, dateEnd)
imageList = imageCollection.toList(100)
imageInfo = imageList.getInfo()
#print 'Modis dates:'
#print dateStart.format().getInfo()
#print dateEnd.format().getInfo()
#print imageInfo
# Find the first image that meets the requirements
numFound = len(imageInfo)
if searchMethod == 'spiral':
searchIndices = miscUtilities.getExpandingIndices(numFound)
elif searchMethod == 'increasing':
searchIndices = range(0,numFound)
else:
searchIndices = range(numFound-1, -1, -1)
#print searchIndices
for i in searchIndices:
COVERAGE_RES = 250
thisImage = ee.Image(imageList.get(i)).resample('bicubic')
percentCoverage = thisImage.mask().reduceRegion(ee.Reducer.mean(), bounds, COVERAGE_RES).getInfo().values()[0]
#print 'percentCoverage = ' + str(percentCoverage)
if percentCoverage < minCoverage: # MODIS has high coverage, but there are gaps.
continue
cloudPercentage = cmt.modis.modis_utilities.getCloudPercentage(thisImage, bounds)
print 'Detected MODIS cloud percentage: ' + str(cloudPercentage)
if cloudPercentage < maxCloudPercentage:
return thisImage
raise Exception('Could not find a nearby cloud-free MODIS image for date ' + str(targetDate.getInfo()))
def getCloudFreeLandsat(bounds, targetDate, maxRangeDays=10, maxCloudPercentage=0.05,
minCoverage=0.8, searchMethod='spiral'):
'''Search for the closest cloud-free Landsat image near the target date.
The result preference is determined by searchMethod and can be set to:
spiral, increasing, or decreasing'''
# Get the date range to search
if searchMethod == 'spiral':
dateStart = targetDate.advance(-1*maxRangeDays, 'day')
dateEnd = targetDate.advance( maxRangeDays, 'day')
else:
dateStart = targetDate
dateEnd = targetDate.advance( maxRangeDays, 'day')
# Try each of the satellites in decreasing order of quality
collectionNames = ['LC8_L1T_TOA', 'LT5_L1T_TOA', 'LE7_L1T_TOA']
for name in collectionNames:
# Get candidate images for this sensor
imageCollection = get_image_collection_landsat(bounds, dateStart, dateEnd, name)
imageList = imageCollection.toList(100)
imageInfo = imageList.getInfo()
# Find the first image that meets the requirements
numFound = len(imageInfo)
if searchMethod == 'spiral':
searchIndices = miscUtilities.getExpandingIndices(numFound)
elif searchMethod == 'increasing':
searchIndices = range(0,numFound)
else:
searchIndices = range(numFound-1, -1, -1)
for i in searchIndices:
COVERAGE_RES = 60
thisImage = ee.Image(imageList.get(i)).resample('bicubic')
percentCoverage = thisImage.mask().reduceRegion(ee.Reducer.mean(), bounds, COVERAGE_RES).getInfo().values()[0]
if percentCoverage < minCoverage:
continue
cloudPercentage = cmt.util.landsat_functions.getCloudPercentage(thisImage, bounds)
print 'Detected Landsat cloud percentage: ' + str(cloudPercentage)
if cloudPercentage < maxCloudPercentage:
return thisImage
# If we got here this satellite did not produce a good image, try the next satellite.
raise Exception('Could not find a nearby cloud-free Landsat image for date ' + str(targetDate.getInfo()))
def getNearestSentinel1(bounds, targetDate, maxRangeDays=10, minCoverage=0.8, searchMethod='spiral'):
'''Search for the closest Sentinel1 image near the target date.
Sentinel1 images are radar and see through clouds!
The result preference is determined by searchMethod and can be set to:
spiral, increasing, or decreasing'''
# TODO: Some options to balance nearness and resolution preferences?
# Get the date range to search
if searchMethod == 'spiral':
dateStart = targetDate.advance(-1*maxRangeDays, 'day')
dateEnd = targetDate.advance( maxRangeDays, 'day')
else:
dateStart = targetDate
dateEnd = targetDate.advance( maxRangeDays, 'day')
# Get a list of candidate images
imageCollection = get_image_collection_sentinel1(bounds, dateStart, dateEnd)
imageList = imageCollection.toList(100)
imageInfo = imageList.getInfo()
if len(imageInfo) == 0:
raise Exception('Could not find a nearby Sentinel1 image for date ' + str(targetDate.getInfo()))
# Find the first image that meets the requirements
numFound = len(imageInfo)
if searchMethod == 'spiral':
searchIndices = miscUtilities.getExpandingIndices(numFound)
elif searchMethod == 'increasing':
searchIndices = range(0,numFound)
else:
searchIndices = range(numFound-1, -1, -1)
for i in searchIndices:
COVERAGE_RES = 30
thisImage = ee.Image(imageList.get(i)).resample('bicubic')
percentCoverage = thisImage.mask().reduceRegion(ee.Reducer.mean(), bounds, COVERAGE_RES).getInfo().values()[0]
print 'S1 Coverage = ' + str(percentCoverage)
if percentCoverage >= minCoverage: # MODIS has high coverage, but there are gaps.
return thisImage
raise Exception('Could not find a nearby Sentinel image with coverage for date ' + str(targetDate.getInfo()))
def getCloudFreeModis(bounds,
targetDate,
maxRangeDays=10,
maxCloudPercentage=0.05,
searchMethod='spiral'):
'''Search for the closest cloud-free MODIS image near the target date.
The result preference is determined by searchMethod and can be set to:
spiral, increasing, or decreasing'''
# Get the date range to search
if searchMethod == 'spiral':
dateStart = targetDate.advance(-1 * maxRangeDays, 'day')
dateEnd = targetDate.advance(maxRangeDays, 'day')
else:
dateStart = targetDate
dateEnd = targetDate.advance(maxRangeDays, 'day')
# Get a list of candidate images
imageCollection = get_image_collection_modis(bounds, dateStart, dateEnd)
imageList = imageCollection.toList(100)
imageInfo = imageList.getInfo()
# Find the first image with a low cloud percentage
numFound = len(imageInfo)
if searchMethod == 'spiral':
searchIndices = miscUtilities.getExpandingIndices(numFound)
elif searchMethod == 'increasing':
searchIndices = range(0, numFound)
else:
searchIndices = range(numFound - 1, -1, -1)
for i in searchIndices:
thisImage = ee.Image(imageList.get(i)).resample('bicubic')
cloudPercentage = cmt.modis.modis_utilities.getCloudPercentage(
thisImage, bounds)
print 'Detected MODIS cloud percentage: ' + str(cloudPercentage)
if cloudPercentage < maxCloudPercentage:
return thisImage
raise Exception(
'Could not find a nearby cloud-free MODIS image for date ' +
str(targetDate.getInfo()))
