Book Image

ArcGIS Blueprints

By : Donald Eric Pimpler, Eric Pimpler
Book Image

ArcGIS Blueprints

By: Donald Eric Pimpler, Eric Pimpler

Overview of this book

This book is an immersive guide to take your ArcGIS Desktop application development skills to the next level It starts off by providing detailed description and examples of how to create ArcGIS Desktop Python toolboxes that will serve as containers for many of the applications that you will build. We provide several practical projects that involve building a local area/community map and extracting wildfire data. You will then learn how to build tools that can access data from ArcGIS Server using the ArcGIS REST API. Furthermore, we deal with the integration of additional open source Python libraries into your applications, which will help you chart and graph advanced GUI development; read and write JSON, CSV, and XML format data sources; write outputs to Google Earth Pro, and more. Along the way, you will be introduced to advanced ArcPy Mapping and ArcPy Data Access module techniques and use data-driven Pages to automate the creation of map books. Finally, you will learn advanced techniques to work with video and social media feeds. By the end of the book, you will have your own desktop application without having spent too much time learning sophisticated theory.
Table of Contents (18 chapters)
ArcGIS Blueprints
About the Author
About the Reviewers


Let's spend a little time going over the design of what we're going to build in this chapter. This application, like the one we built in the Chapter 1, Extracting Wildfire Data from an ArcGIS Server Map Service with the ArcGIS REST API, will include the creation of an ArcGIS Desktop Python Toolbox. The toolbox, MigrationPatterns.pyt, will include two tools: ImportCollarData and VisualizeMigration. The ImportCollarData tool will import GPS data from a collar that was attached to an elk in northern California. The GPS data will have been extracted to a comma-delimited text file (csv format), that will be read using the Python csv module and then imported into a local feature class stored in a file geodatabase using the arcpy.da which is a data access module. We'll then need to do a little manual work inside ArcMap. First, we'll make the feature class that was created as a result of the ImportCollarData tool time-enabled, and then we'll save the time-enabled data in a map document file...