Book Image

Mastering Geospatial Analysis with Python

By : Silas Toms, Paul Crickard, Eric van Rees
Book Image

Mastering Geospatial Analysis with Python

By: Silas Toms, Paul Crickard, Eric van Rees

Overview of this book

Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis. You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API.
Table of Contents (23 chapters)
Title Page
Copyright and Credits
Packt Upsell
Geoprocessing with Geodatabases


This introductory chapter discussed how to install and manage the code libraries that will be used in this book. We'll be working mainly with Anaconda, a freemium open source distribution of the Python programming language that aims to simplify package management and deployment. We discussed how to install Anaconda, and the options for Python package management using Anaconda Navigator, Anaconda Cloud, conda, and pip. Finally, we discussed virtual environments and how to manage these using Anaconda, conda, and virtualenv.

The recommended installation for this book is the Anaconda3 version, that will install not only a working Python environment, but also a large repository of local Python packages, the Jupyter Notebook application, as well as the conda package manager, Anaconda Navigator, and Cloud. In the next chapter, we will introduce the major code libraries used to process and analyze geospatial data.