Configuring a Minimal Docker Image for Spatial Analysis with Python

Learn how to install the basic geospatial dependencies, such as GDAL and XArray, and deploy them as a container

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Introduction

Newcomers to the Python programming language quickly understand the significance of utilizing virtual environments and package management tools. The vast number of packages available presents a challenge in maintaining compatibility among dependencies, making virtual environments and package management critical components of a well-organized Python environment.

This complexity of managing dependencies is exacerbated when working with geospatial analysis. In addition to the numerous packages utilized in data science, it is necessary to incorporate specialized libraries such as GDAL, Rasterio, and STAC to support this type of analysis. Besides, it is widely known that GDAL can be particularly difficult to install, regardless of the operating system architecture, be it Windows, Linux, or Mac.