HUBDSM API: provide Raster.saveAsVrt methode for storing the Raster specification as VRT Raster

[Andreas Janz]

(requested by @Benjamin Jakimow )

[Andreas Janz]

@Benjamin Jakimow the GDAL Mask Band concept is too restrictive, because it only supports a single mask for all the bands.

MaskBand: (GDAL >= 1.8.0) This element represents a mask band that is shared between all bands on the dataset (see GMF_PER_DATASET in RFC 15). It must contain a single VRTRasterBand child element, that is the description of the mask band itself.

So, for now, I will skip band masks when saving as VRT.

[Andreas Janz]

HUBDSM Raster specification can now be saved as GDAL VRT.

So let’s for example use some EnMAP and HyMap bands:

# use first three bands of EnMAP and the tree RGB bands from HyMap
enmapRaster = Raster.open(enmap).select([1,2,3])
hiresRaster = Raster.open(hires)

Do some stuff with them, e.g. i) stack bands together, ii) reverse the order and iii) use 10m resolution instead of EnMAP’s 30m:

# stack bands together
stack = enmapRaster.addBands(hiresRaster)

# reverse bands
stack = stack[::-1]

# use EnMAP grid at 10m resolution
grid = enmapRaster.grid.withResolution(resolution=Resolution(x=10, y=10))
stack = stack.withGrid(grid=grid)

Finally, save it as a VRT to disk:

# save as VRT
vrt = stack.saveAsVrt(filename=r'stack.vrt')

Check if VRT has all the specified infos:

# print some infos
print(vrt.grid.resolution)
for band in vrt.bands:
    print(band.name)
    print(f'  NoDataValue: {band.noDataValue}')
    print(f'  NumpyDataType: {GDALTypeCodeToNumericTypeCode(band.gdalBand.gdalDataType)}')

Print:

Resolution(x=10.0, y=10.0)
Blue
  NoDataValue: 0.0
  NumpyDataType: <class 'numpy.uint8'>
Green
  NoDataValue: 0.0
  NumpyDataType: <class 'numpy.uint8'>
Red
  NoDataValue: 0.0
  NumpyDataType: <class 'numpy.uint8'>
band 10 (0.470000 Micrometers)
  NoDataValue: -99.0
  NumpyDataType: <class 'numpy.int16'>
band 9 (0.465000 Micrometers)
  NoDataValue: -99.0
  NumpyDataType: <class 'numpy.int16'>
band 8 (0.460000 Micrometers)
  NoDataValue: -99.0
  NumpyDataType: <class 'numpy.int16'>

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