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


This chapter introduced several new topics, including the tweepy module used to monitor live Twitter data feeds and the use of the Windows Task Scheduler to automate the process of monitoring Twitter activity. Although only about 2% of tweets include location information, we can still get a good understanding of the spatial patterns of social media when monitoring large events over an extended period of time. In this chapter, the live tweets were written to a local feature class and then mapped to the Hot Spot Analysis tool found in the Spatial Statistics Tools toolbox.

In the next chapter, you'll learn how to use Python to extract the geographic coordinates from smartphone photos, reverse geocode the coordinates to retrieve the nearest address, and create an ArcGIS Online application to display the results.