Data access
As described in Chapter 2, Geospatial Data, geospatial datasets are typically large, complex, and varied. This challenge makes libraries, which efficiently read and in some cases, write this data essential to geospatial analysis. These libraries are also the most important. Without access to data, geospatial analysis doesn't begin. Furthermore, accuracy and precision are key factors in geospatial analysis. An image library that resamples data without permission, or a computational geometry library that rounds a coordinate even a couple of decimal places, can adversely affect the quality of analysis. Also, these libraries must manage memory efficiently. A complex geospatial process can last for hours or even days. If a data access library has a memory fault, it can delay an entire project or even an entire workflow involving dozens of people dependent on the output of that analysis.
GDAL
The Geospatial Data Abstraction Library (GDAL) does the most heavy lifting task in the geospatial...
