Geoprocessing
Selected python scripts for geoprocessing using open source geospatial resources
binned_statistics_2d_XYZ_csv_to_geotiff.py
-- Rasterization of 2d point data (x,y) with an attribute z into a grid of arbitrary cellsize and spatial reference system, using a user-specified summary statistic f(z) applied at the grid-cell level.
-- Input: CSV file holding (x,y,z) data
-- Output: A GeoTIFF containing a gridded surface, with f(z) in each grid cell.
-- f(z) can be the mean, median, count, diversity, etc.
This script generates a gridded surface in GeoTiff format, based on one or more CSV files holding marked points (i.e., [x,y,z] with x and y being geospatial coordinates and z being a variable of interest to be summarized), using scipy.stats.binned_statistic_2d() and GDAL.
Suitable for country and continental scale data processing. The output .tif will be LZW-compressed. Each CSV file may hold the data for a geographic sub-region within the total area of interest. However, the content of the CSV files may not overlap spatially, as f(z) is added cell-by-cell to a zero raster for each CSV file. This strategy is very efficient, but may produce inaccurate results at "overlapping" grid cells (e.g., at the edge between two adjacebt sub-regions). A template GeoTiff is required that dictates the target grid.
Johannes H. Uhl, University of Colorado Boulder, USA