In this chapter you learned the hierarchy of geospatial analysis software including the following key elements:
Hundreds of geospatial software packages and libraries exist
All geospatial software can be categorized as:
Data access
Computational geometry
Raster processing
Desktop tools
Metadata management
Nearly all significant geospatial software is dependent on four libraries
GDAL – raster data access
OGR – vector data access
PROJ.4 – geospatial data reprojection
GEOS – computational geometry
Raster processing software is very fragmented with many packages and frequent custom solutions
If you come across new software trace it to the four core libraries and ask "what is the value added?"
If you can't trace the software to one of the four core libraries then ask "Is this a well maintained new solution or is it destined for obscurity?"
Python was only mentioned a few times in this chapter to avoid any distraction in understanding the geospatial software landscape. But, as we will see, Python is interwoven...