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landsat.vrt
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landsat.vrt
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<VRTDataset rasterXSize="3671" rasterYSize="3671">
<SRS>PROJCS["UTM Zone 31, Northern Hemisphere",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",3],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AUTHORITY["EPSG","32631"]]</SRS>
<GeoTransform> 3.0015019161584723e+05, 2.9982920084303917e+01, 0.0000000000000000e+00, 4.8707528290257305e+06, 0.0000000000000000e+00, -2.9982920084303917e+01</GeoTransform>
<VRTRasterBand dataType="Int16" band="1" subClass="VRTDerivedRasterBand">
<PixelFunctionType>time_average</PixelFunctionType>
<PixelFunctionLanguage>Python</PixelFunctionLanguage>
<PixelFunctionCode><![CDATA[
import numpy as np
def time_average(in_ar, out_ar, xoff, yoff, xsize, ysize, raster_xsize, raster_ysize, buf_radius, gt, **kwargs):
# Average along the first dimension, i.e. across time
out_ar[:] = np.average(in_ar, axis = 0)
]]>
</PixelFunctionCode>
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</VRTDataset>