Spatial Interpolation with GDAL in Python 1 Nearest Neighbor and Moving Average

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In this tutorial, I will give an introduction to the spatial interpolation algorithms nearest neighbor and moving average. We will use gdal.Grid() from the geospatial data abstraction library GDAL to create a regular grid from scattered point data in Python. • gdal_grid documentation: https://gdal.org/programs/gdal_grid.html • GDAL Grid Tutorial: https://gdal.org/tutorials/gdal_grid_... • GDAL/OGR Python API: https://gdal.org/python/ • Chapters: • 0:00 Introduction • 1:33 Nearest Neighbor • 14:14 Moving Average • Code: • from osgeo import gdal • from osgeo import ogr • pts = ogr.Open( points.shp , 0) • layer = pts.GetLayer() • for field in layer.schema: • print(field.name) • dem = gdal.Open( dem.tif ) • gt = dem.GetGeoTransform() • ulx = gt[0] • uly = gt[3] • res = gt[1] • xsize = dem.RasterXSize • ysize = dem.RasterYSize • lrx = ulx + xsize * res • lry = uly - ysize * res • dem = None • nearest neighbor interpolation • pts = layer = None • nn = gdal.Grid( nearest.tif , points.shp , zfield= elevation , • algorithm = nearest , outputBounds = [ulx,uly,lrx,lry], • width = xsize, height = ysize) • nn = None • moving average • ma = gdal.Grid( average.tif , points.shp , zfield= elevation , • algorithm = average:radius1=1000:radius2=800:angle=20 , • outputBounds = [ulx,uly,lrx,lry], • width = xsize, height = ysize) • ma = None

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