Python Sentinel SNAP – Retrieve Array of Pixel Values from Snappy Product

pythonsentinel-snap

I am using snappy for processing SAR data, but it seems that snappy uses its own 'product' objects for storing raster data. But i only need the resulting array of pixel values after I finish working with it. How can I retrieve such array from speckle variable in the code below?

import snappy
import pathlib
from configparser import ConfigParser
import os

config = ConfigParser()
config.read('config.ini')
projLibPath = config['PATHS']['proj_lib']
gdalDataPath = config['PATHS']['gdal_data']
os.environ['PROJ_LIB'] = projLibPath
os.environ['GDAL_DATA'] = gdalDataPath

def Filter (inputRasterPath):
    print('------------Filter------------')
    print('Reading the image file..')
    read = snappy.ProductIO.readProduct(inputRasterPath)
    outputRasterPath = './Filter/Filter'+  pathlib.Path(inputRasterPath).suffix
    print(read)

    parameters = snappy.HashMap()
    parameters.put('filter', 'Lee')
    parameters.put('filterSizeX',3)
    parameters.put('filterSizeY',3)
    print('Filtering...')
    speckle = snappy.GPF.createProduct('Speckle-Filter', parameters, read)
    print('Filter successfully', speckle)

    print('Writing the filtered image...')
    snappy.ProductIO.writeProduct(speckle, outputRasterPath, 'GeoTIFF')
    print('Done')

Best Answer

Thanks to user2856 i resolved this problem by adding

band = speckle.getBand('band_1')
w = band.getRasterWidth()
h = band.getRasterHeight()
band_data = np.zeros(w * h, np.float32)
band.readPixels(0, 0, w, h, band_data)
speckle.dispose()
band_data.shape = h, w.

I have a little problem with np.float32: when i change data type to, for example, np.uint16 i have an error :

    band.readPixels(0, 0, w, h, band_data)
RuntimeError: no matching Java method overloads found

So i decided to change the data type of a raster later, using band_data.astype(src.dtypes[0])

The final code looks like this:

import numpy as np
import rasterio
import snappy
import pathlib
from configparser import ConfigParser
import os



config = ConfigParser()
config.read('config.ini')
projLibPath = config['PATHS']['proj_lib']
gdalDataPath = config['PATHS']['gdal_data']
os.environ['PROJ_LIB'] = projLibPath
os.environ['GDAL_DATA'] = gdalDataPath

def Filter (inputRasterPath):
    print('------------Filter------------')
    print('Reading the image file..')
    read = snappy.ProductIO.readProduct(inputRasterPath)
    outputRasterPath = './Filter/Filter'+  pathlib.Path(inputRasterPath).suffix
    print(read)

    parameters = snappy.HashMap()
    parameters.put('filter', 'Lee')
    parameters.put('filterSizeX',3)
    parameters.put('filterSizeY',3)
    print('Filtering...')
    speckle = snappy.GPF.createProduct('Speckle-Filter', parameters, read)
    print('Filter successfully', speckle)

    band = speckle.getBand('band_1')
    w = band.getRasterWidth()
    h = band.getRasterHeight()
    band_data = np.zeros(w * h, np.uint16)
    band.readPixels(0, 0, w, h, band_data)
    speckle.dispose()
    band_data.shape = h, w

    print(band_data)
    print(band_data.shape)

    src = rasterio.open(inputRasterPath)

    profile = {
        'driver': 'GTiff', 
        'dtype': src.dtypes[0], # np.uint8, np.uint16 etc.
        'nodata': src.nodata, 
        'width': src.shape[1], 
        'height': src.shape[0],
        'count': 1, # bands count
        'crs': src.crs, 
        'transform': src.transform, 
        'tiled': False,
        'compress': None,
        }

    print('Saving the output...')
    with rasterio.open(outputRasterPath,'w',**profile) as dst: 
        dst.write(band_data.astype(src.dtypes[0]),1) # (np.array, number of bands?)
    src = None
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