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

Creating the application

This application will perform geospatial analysis using the geometry fields of database tables. To make this possible, we have to create and populate the database tables using shapefiles and a built-in method called LayerMapping.

The completed application will need URL pattern matching to link URLs with the views that will process the requests and return the response. Templates will be used to pass processed data to the browser. Views will be written to be able to handle both POST and GET requests and to redirect to other views.

Now that GeoDjango is configured, the NBA Arenas application can be created using the Django project management script called

The script performs a number of jobs to help set up and manage the project. For testing purposes, it can create a local web server (using runserver as the argument); it manages database schema migrations, generating tables from data models (using makemigration and migrate); it even has a...