def open_subset(self, geo_extent, copymetadata="true"):
""" Create a subset of a given SNAP product.
From a given set of coordinates defining a region of interest create
a subset product containing all the bands from the original product.
Args:
inprod: ESA SNAP product object
geo_extent (wkt): BoundingBox in WKT format
copymetadata (bool): Copy all bands to subset product
Returns:
(self.product): ESA SNAP product object
"""
# Empty HashMap
parameters = HashMap()
# Subset parameters
geo = WKTReader().read(geo_extent)
parameters.put("geoRegion", geo)
parameters.put("subSamplingX", "1")
parameters.put("subSamplingY", "1")
parameters.put("copyMetadata", copymetadata)
# Create subset using operator
prod_subset = GPF.createProduct("Subset", parameters, self.product)
# Update product
self.product = prod_subset
# Close dataset
prod_subset = None
def subset(product, shpPath):
parameters = HashMap()
wkt = shpToWKT(shpPath)
SubsetOp = jpy.get_type('org.esa.snap.core.gpf.common.SubsetOp')
geometry = WKTReader().read(wkt)
parameters.put('copyMetadata', True)
parameters.put('geoRegion', geometry)
return GPF.createProduct('Subset', parameters, product)
def make_subset(product, wkt):
print("Making subset")
SubsetOp = snappy.jpy.get_type('org.esa.snap.core.gpf.common.SubsetOp')
geom = WKTReader().read(wkt)
op = SubsetOp()
op.setSourceProduct(product)
op.setGeoRegion(geom)
sub_product = op.getTargetProduct()
return sub_product
def get_subset_config(wkt, bands=None):
parameters = HashMap()
if bands is not None:
parameters.put("sourceBands", bands)
if wkt is not None:
geom = WKTReader().read(wkt)
parameters.put("geoRegion", geom)
parameters.put("copyMetadata", True)
parameters.put("outputImageScaleInDb", False)
return parameters
def preprocesado():
##Aplicar correccion orbital
global product
global product_calibrated
global HashMap
print(product)
parameters = HashMap()
GPF.getDefaultInstance().getOperatorSpiRegistry().loadOperatorSpis()
parameters.put('orbitType', 'Sentinel Precise (Auto Download)')
parameters.put('polyDegree', '3')
parameters.put('continueOnFail', 'false')
apply_orbit_file = GPF.createProduct('Apply-Orbit-File', parameters,
product)
##Recortar la imagen
r = shapefile.Reader(archivo_shape)
g = []
for s in r.shapes():
g.append(pygeoif.geometry.as_shape(s))
m = pygeoif.MultiPoint(g)
wkt = str(m.wkt).replace("MULTIPOINT", "POLYGON(") + ")"
#Usar el shapefile para cortar la imagen
SubsetOp = snappy.jpy.get_type('org.esa.snap.core.gpf.common.SubsetOp')
bounding_wkt = wkt
geometry = WKTReader().read(bounding_wkt)
HashMap = snappy.jpy.get_type('java.util.HashMap')
GPF.getDefaultInstance().getOperatorSpiRegistry().loadOperatorSpis()
parameters = HashMap()
parameters.put('copyMetadata', True)
parameters.put('geoRegion', geometry)
product_subset = snappy.GPF.createProduct('Subset', parameters,
apply_orbit_file)
#Mostrar las dimensiones de la imagen
width = product_subset.getSceneRasterWidth()
print("Width: {} px".format(width))
height = product_subset.getSceneRasterHeight()
print("Height: {} px".format(height))
band_names = product_subset.getBandNames()
print("Band names: {}".format(", ".join(band_names)))
band = product_subset.getBand(band_names[0])
print(band.getRasterSize())
#plotBand(product_subset, "Intensity_VV", 0, 100000)
##Aplicar la calibracion de la imagen
parameters = HashMap()
parameters.put('outputSigmaBand', True)
parameters.put('sourceBands', 'Intensity_VV')
parameters.put('selectedPolarisations', "VV")
parameters.put('outputImageScaleInDb', False)
product_calibrated = GPF.createProduct("Calibration", parameters,
product_subset)
#plotBand(product_calibrated, "Sigma0_VV", 0, 1)
print("PREPROCESAMIENTO HECHO EXITOSAMENTE")
def subsetProduct(product, pol):
# if pol.area<1000:
buff = pol.buffer((pol.area)**0.5)
# else:
# buff=pol.buffer((pol.area)**0.5)
bb = getBoundingBoxWM(buff)
bb_ll = utils.utm2wgs(bb)
geom = WKTReader().read(bb_ll.wkt)
parameters = HashMap()
parameters.put('copyMetadata', True)
parameters.put('geoRegion', geom)
product_subset = GPF.createProduct('Subset', parameters, product)
return (product_subset)
import snappy
from snappy import ProductIO, WKTReader
SubsetOp = snappy.jpy.get_type('org.esa.snap.core.gpf.common.SubsetOp')
if len(sys.argv) != 3:
print("usage: %s <file> <geometry-wkt>" % sys.argv[0])
print(
" %s ./TEST.N1 \"POLYGON((15.786082 45.30223, 11.798364 46.118263, 10.878688 43.61961, 14.722727"
"42.85818, 15.786082 45.30223))\"" % sys.argv[0])
sys.exit(1)
file = sys.argv[1]
wkt = sys.argv[2]
geom = WKTReader().read(wkt)
print("Reading...")
product = ProductIO.readProduct(file)
op = SubsetOp()
op.setSourceProduct(product)
op.setGeoRegion(geom)
op.setCopyMetadata(True)
sub_product = op.getTargetProduct()
print("Writing...")
ProductIO.writeProduct(sub_product, "snappy_subset_output.dim", "BEAM-DIMAP")
print("Done.")
WKTReader, ProductIO, PlainFeatureFactory,
SimpleFeatureBuilder, DefaultGeographicCRS,
ListFeatureCollection, FeatureUtils)
if len(sys.argv) != 3:
print("usage: %s <inputProduct> <wkt>" % sys.argv[0])
sys.exit(1)
input = sys.argv[1]
inputFileName = input[input.rfind('/')+1:]
wellKnownText = sys.argv[2]
try:
geometry = WKTReader().read(wellKnownText)
except:
geometry = None
print('Failed to convert WKT into geometry')
sys.exit(2)
product = ProductIO.readProduct(input)
wktFeatureType = PlainFeatureFactory.createDefaultFeatureType(DefaultGeographicCRS.WGS84)
featureBuilder = SimpleFeatureBuilder(wktFeatureType)
wktFeature = featureBuilder.buildFeature('shape')
wktFeature.setDefaultGeometry(geometry)
newCollection = ListFeatureCollection(wktFeatureType)
newCollection.add(wktFeature)
import shapefile
import pygeoif
shp_file_path = "E:\Sentinel 1 SAR Processing\Sentinel_Mosaic\Data\Spatial Data\NPL_adm0.shp"
shp_file = shapefile.Reader(shp_file_path)
g = []
for s in shp_file.shapes():
g.append(pygeoif.geometry.as_shape(s))
m = pygeoif.MultiPoint(g)
wkt = str(m.wkt).replace("MULTIPOINT", "POLYGON(") + ")"
geometry = WKTReader().read(wkt)
SRTM1SEC = "SRTM 1Sec HGT"
UTM_WGS84 = "GEOGCS[\"WGS84(DD)\",DATUM[\"WGS84\",SPHEROID[\"WGS84\", 6378137.0, 298.257223563]]," \
"PRIMEM[\"Greenwich\", 0.0],UNIT[\"degree\", 0.017453292519943295],AXIS[\"Geodetic longitude\", EAST]," \
"AXIS[\"Geodetic latitude\", NORTH]] "
def TOPSAR_Split_config(subswath, firstBurstIndex, lastBurstIndex,
polarizations):
"""
This function ....
"""
parameters = HashMap()
parameters.put('subswath', subswath)
def preproceso(product, wkt):
global HashMap
parameters = HashMap()
GPF.getDefaultInstance().getOperatorSpiRegistry().loadOperatorSpis()
parameters.put('orbitType', 'Sentinel Precise (Auto Download)')
parameters.put('polyDegree', '3')
parameters.put('continueOnFail', 'false')
global apply_orbit_file
apply_orbit_file = GPF.createProduct('Apply-Orbit-File', parameters,
product)
#Usar el shapefile para cortar la imagen
#def CorteUsandoShapefile(product, apply_orbit_file, wkt):
# global HashMap
SubsetOp = snappy.jpy.get_type('org.esa.snap.core.gpf.common.SubsetOp')
bounding_wkt = wkt
geometry = WKTReader().read(bounding_wkt)
HashMap = snappy.jpy.get_type('java.util.HashMap')
GPF.getDefaultInstance().getOperatorSpiRegistry().loadOperatorSpis()
parameters = HashMap()
parameters.put('copyMetadata', True)
parameters.put('geoRegion', geometry)
product_subset = snappy.GPF.createProduct('Subset', parameters,
apply_orbit_file)
#Mostrar las dimensiones de la imagen
width = product_subset.getSceneRasterWidth()
print("Width: {} px".format(width))
height = product_subset.getSceneRasterHeight()
print("Height: {} px".format(height))
band_names = product_subset.getBandNames()
print("Band names: {}".format(", ".join(band_names)))
band = product_subset.getBand(band_names[0])
print(band.getRasterSize())
plotBand(product_subset, "Intensity_VV", 0, 100000)
#return product_subset
#def CalibracionImagen(product_subset):
##Aplicar la calibracion de la imagen
parameters = HashMap()
parameters.put('outputSigmaBand', True)
parameters.put('sourceBands', 'Intensity_VV')
parameters.put('selectedPolarisations', "VV")
parameters.put('outputImageScaleInDb', False)
product_calibrated = GPF.createProduct("Calibration", parameters,
product_subset)
plotBand(product_calibrated, "Sigma0_VV", 0, 1)
#def filtroSpeckle(product_calibrated):
##Aplicar el filtro Speckle
filterSizeY = '5'
filterSizeX = '5'
parameters = HashMap()
parameters.put('sourceBands', 'Sigma0_VV')
parameters.put('filter', 'Lee')
parameters.put('filterSizeX', filterSizeX)
parameters.put('filterSizeY', filterSizeY)
parameters.put('dampingFactor', '2')
parameters.put('estimateENL', 'true')
parameters.put('enl', '1.0')
parameters.put('numLooksStr', '1')
parameters.put('targetWindowSizeStr', '3x3')
parameters.put('sigmaStr', '0.9')
parameters.put('anSize', '50')
speckle_filter = snappy.GPF.createProduct('Speckle-Filter', parameters,
product_calibrated)
plotBand(speckle_filter, 'Sigma0_VV', 0, 1)
#def CorreccionTerreno(speckle_filter):
##Aplicar la correccion del terremo
parameters = HashMap()
parameters.put('demName', 'SRTM 3Sec')
parameters.put('pixelSpacingInMeter', 10.0)
parameters.put('sourceBands', 'Sigma0_VV')
global speckle_filter_tc
speckle_filter_tc = GPF.createProduct("Terrain-Correction", parameters,
speckle_filter)
plotBand(speckle_filter_tc, 'Sigma0_VV', 0, 0.1)