I am trying to find out how to use GDAL & numpy modules to average a set of rasters....which are Sigma0 values from satellite passes at different times within a year.
Each raster has been mosaicked from a number of smaller images using GDAL_merge. Because the orbits differ each time they pass over the area of interest the merged datasets are different extents and not regular squares.
So I want to average the values from each pass....baring in mind that when theoretically stacked on top of one another, there is sometimes overlaps of one/two/three images.
I imagine the best way of me getting around this is making all rasters the same extent ... and using a 'no data' value for areas of the raster where there is no data...and then ignoring these values during the calc of the average...
If this indeed the best way, how do I go about making them all the same extent when they are not regular (rectangle)? ...or is there a better way than this?
I am new to using GDAL/numpy ....my impression is that calculations using multiple rasters is best done in numpy arrays? again, is this correct.
Thank you in advance