Using GDAL in Python for raster data processing

Data is the blood of software, especially in the spatial information industry. Massive data is the most obvious in the spatial information software industry. It is difficult to complete the integration and integration of heterogeneous data without a set of efficient data conversion models and libraries. With GDAL/OGR, all kinds of spatial information software tools built on it have a life.

GDAL is the abbreviation of Geospatial Data Abstraction Library. At first, GDAL was a class library for processing raster spatial data, while OGR was used for processing vector data. Later, the two libraries were merged into one library, which used the name GDAL when downloading and installing. In this book, in order to avoid this confusion, the combined library is called GDAL/OGR: using GDAL to represent the database for processing raster data and OGR to represent the database for processing vector data.

The library originated in 1998 and has evolved substantially. It supports its own data model and application program interface (API). From the origin of the initial single development, GDAL has developed into a distributed project with relatively large number of developers. GDAL/OGR is widely used in the open source geospatial world, including but not limited to software tools such as MapServer, GRASS, QGIS, MapGuide, OSSIM and OpenEV. GDAL/OGR is also used in many special software products, such as FME, ArcGIS and Adcorp SIS.

In the Python binding of GDAL/OGR, there are mainly five modules, namely gdal , ogr , osr , gdal_array , gdalconst. The specific functions and usages will be explained in the following sections.

This chapter focuses on using GDAL to process raster data, discussing GDAL design concepts, data models, and how to use them in Python. The GDAL used in this chapter generally refers only to the part that processes raster data.

The content will cover the following parts:

A brief introduction to GDAL, including instructions for its command-line tools

Read data sets

Reading Band Related Information and Data

Spatial reference of raster data

Raster data color table

Method of generating raster data

Interoperation between GDAL and other Python class libraries

• 1. Start using GDAL in Python
• 2. Get raster dataset information using GDAL in Python
• 3. Access pixel of raster data in Python using GDAL
• 4. Create and save raster dataset using GDAL in Python