def computeMosaicId(year, cloudThresh, zShadowThresh):
start = datetime.date(year, 1, 1).isoformat()
end = datetime.date(year, 12, 1).isoformat()
# A mapping from a common name to the sensor-specific bands.
LC8_BANDS = ['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B10']
STD_NAMES = [
'blue', 'green', 'red', 'nir', 'swir1', 'swir2', 'temp'
]
area1 = ee.Geometry.Polygon(
[[[-54.95086669921875, -4.387490398371425],
[-54.7833251953125, -4.852890820110559],
[-53.9813232421875, -4.598327203100916],
[-54.1241455078125, -4.099890260666389]]])
#Compute a cloud score. This expects the input image to have the common
#band names: ["red", "blue", etc], so it can work across sensors.
def addCloudThreshold(img):
return img.addBands(
ee.Image(cloudThresh).select([0], ['cloudThresh']))
def addShadowThreshold(img):
return img.addBands(
ee.Image(zShadowThresh).select([0], ['zShadowThresh']))
#Filter the TOA collection to a time-range and area, add the cloud threshold band and filter clouds
collection = ee.ImageCollection('LC8_L1T_TOA').select(LC8_BANDS, STD_NAMES).\
filterDate(start,end).\
map(addCloudThreshold).\
map(addShadowThreshold).\
map(maskingTools.maskCloudsAndSuch)
collection_masked_shadows = maskingTools.maskShadows(collection)
img = collection_masked_shadows.median().select(
['swir1', 'nir', 'red'])
#compute last value (can be useful for monitoring once SR imagens are available)
#col_sorted = collection_masked_shadows.select(['swir1','nir','red']).sort('system:time_start', False) #Order adquisition by date
#img1= col_sorted.mosaic()
mapid = img.getMapId({'min': 0.0, 'max': 0.5})
return mapid
def computeMosaicId(year,cloudThresh,zShadowThresh):
start = datetime.date(year,1,1).isoformat()
end = datetime.date(year,12,1).isoformat()
# A mapping from a common name to the sensor-specific bands.
LC8_BANDS = ['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B10']
STD_NAMES = ['blue', 'green', 'red', 'nir', 'swir1', 'swir2', 'temp']
area1=ee.Geometry.Polygon(
[[[-54.95086669921875, -4.387490398371425],
[-54.7833251953125, -4.852890820110559],
[-53.9813232421875, -4.598327203100916],
[-54.1241455078125, -4.099890260666389]]])
#Compute a cloud score. This expects the input image to have the common
#band names: ["red", "blue", etc], so it can work across sensors.
def addCloudThreshold (img):
return img.addBands(ee.Image(cloudThresh).select([0],['cloudThresh']))
def addShadowThreshold (img):
return img.addBands(ee.Image(zShadowThresh).select([0],['zShadowThresh']))
#Filter the TOA collection to a time-range and area, add the cloud threshold band and filter clouds
collection = ee.ImageCollection('LC8_L1T_TOA').select(LC8_BANDS, STD_NAMES).\
filterDate(start,end).\
map(addCloudThreshold).\
map(addShadowThreshold).\
map(maskingTools.maskCloudsAndSuch)
collection_masked_shadows=maskingTools.maskShadows(collection)
img=collection_masked_shadows.median().select(['swir1','nir','red'])
#compute last value (can be useful for monitoring once SR imagens are available)
#col_sorted = collection_masked_shadows.select(['swir1','nir','red']).sort('system:time_start', False) #Order adquisition by date
#img1= col_sorted.mosaic()
mapid=img.getMapId({'min':0.0,'max': 0.5})
return mapid
def get(self): # pylint: disable=g-bad-name
"""Request an image from Earth Engine and render it to a web page."""
ee.Initialize(config.EE_CREDENTIALS)
start = datetime.date(2015, 1, 1).isoformat()
end = datetime.date(2015, 12, 1).isoformat()
# A mapping from a common name to the sensor-specific bands.
LC8_BANDS = ['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B10']
STD_NAMES = ['blue', 'green', 'red', 'nir', 'swir1', 'swir2', 'temp']
area1 = ee.Geometry.Polygon([[[-54.95086669921875, -4.387490398371425],
[-54.7833251953125, -4.852890820110559],
[-53.9813232421875, -4.598327203100916],
[-54.1241455078125,
-4.099890260666389]]])
#Compute a cloud score. This expects the input image to have the common
#band names: ["red", "blue", etc], so it can work across sensors.
def addCloudThreshold(img):
return img.addBands(
ee.Image(cloudThresh).select([0], ['cloudThresh']))
def addShadowThreshold(img):
return img.addBands(
ee.Image(zShadowThresh).select([0], ['zShadowThresh']))
#Filter the TOA collection to a time-range and area, add the cloud threshold band and filter clouds
collection = ee.ImageCollection('LC8_L1T_TOA').select(LC8_BANDS, STD_NAMES).\
filterDate(start,end).\
map(addCloudThreshold).\
map(addShadowThreshold).\
map(maskingTools.maskCloudsAndSuch)
collection_masked_shadows = maskingTools.maskShadows(collection)
#collection_masked_shadows=collection
# Display the image normally.
#mapid=collection.qualityMosaic('cloudscore').getMapId({'bands': ['B6', 'B5', 'B4'], 'max': 1.0, 'gamma': 1.0})
#compute median value (for mosaics)
img1 = collection_masked_shadows.median().select(
['swir1', 'nir', 'red'])
#compute last value (for monitoring)
#col_sorted = collection_masked_shadows.select(['swir1','nir','red']).sort('system:time_start', False) #Order adquisition by date
#img1= col_sorted.mosaic()
#img1=collection.qualityMosaic('cloudscore').select(['swir1','nir','red'])
#mapid=img1.getMapId({'bands': ['swir1', 'nir', 'red'], 'max': 1.0, 'gamma': 1.0})
mapid = img1.getMapId({'min': 0.0, 'max': 0.5})
debugtext = ''
# These could be put directly into template.render, but it
# helps make the script more readable to pull them out here, especially
# if this is expanded to include more variables.
template_values = {
'mapid': mapid['mapid'],
'token': mapid['token'],
'debugtext': debugtext
}
template = jinja_environment.get_template('index.html')
self.response.out.write(template.render(template_values))
