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

Introducing the ArcGIS API for Python and ArcGIS Online

Esri, the geospatial software company known for its ArcGIS platform, adopted and integrated Python into their ArcGIS desktop software, as well as its successor ArcGIS Pro. The first Python site package developed by Esri was the ArcPy site package, which is a collection of Python modules that offers all existing, as well as extended, ArcMap and ArcGIS Pro functionality. Python can now be used as a scripting and programming language to automate repetitive tasks that involve a lot of interaction with the Graphical User Interface (GUI). With ArcPy, these tasks could be carried out through a Python script, add-on, or toolbox.

Python was introduced successfully with ArcGIS desktop, while GIS itself was moving into the cloud—not only geospatial data but also the software itself. Esri offered organizations the possibility to do this through a variety of cloud environment offerings, using either public, private, or hybrid cloud services. In this...