Book Image

ArcGIS Pro 2.x Cookbook

By : Tripp Corbin GISP
Book Image

ArcGIS Pro 2.x Cookbook

By: Tripp Corbin GISP

Overview of this book

ArcGIS is Esri's catalog of GIS applications with powerful tools for visualizing, maintaining, and analyzing data. ArcGIS makes use of the modern ribbon interface and 64-bit processing to increase the speed and efficiency of using GIS. It allows users to create amazing maps in both 2D and 3D quickly and easily. If you want to gain a thorough understanding of the various data formats that can be used in ArcGIS Pro and shared via ArcGIS Online, then this book is for you. Beginning with a refresher on ArcGIS Pro and how to work with projects, this book will quickly take you through recipes about using various data formats supported by the tool. You will learn the limits of each format, such as Shapefiles, Geodatabase, and CAD files, and learn how to link tables from outside sources to existing GIS data to expand the amount of data that can be used in ArcGIS. You'll learn methods for editing 2D and 3D data using ArcGIS Pro and how topology can be used to ensure data integrity. Lastly the book will show you how data and maps can be shared via ArcGIS Online and used with web and mobile applications.
Table of Contents (21 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Calculating the geographic dispersion of data


You can now determine the geographic center and central feature for a grouping of data. As you have seen, this can be a very powerful type of analysis. It can help you sight new locations, determine the focal point of a series of incidents, find the center of mass for a group of features, and more. But what if you need to know where the area of greatest concentration of features is, or how compact or spread out the data is around its geographic center? Such analysis can help you to locate clusters of data or see shifts in behavior.

ArcGIS Pro’s Standard Distance tool, located in the Spatial Statistics Tools toolbox, and the Measuring Geographic Distributions toolset allows you to do this. It measures the compactness of a distribution around the mean center of a group of features. The smaller the distance calculated, the less the data is dispersed. It is more compact. The larger the distance calculated, the more the data is dispersed, meaning it...