Book Image

PostGIS Cookbook - Second Edition

By : Pedro Wightman, Bborie Park, Stephen Vincent Mather, Thomas Kraft, Mayra Zurbarán
Book Image

PostGIS Cookbook - Second Edition

By: Pedro Wightman, Bborie Park, Stephen Vincent Mather, Thomas Kraft, Mayra Zurbarán

Overview of this book

PostGIS is a spatial database that integrates the advanced storage and analysis of vector and raster data, and is remarkably flexible and powerful. PostGIS provides support for geographic objects to the PostgreSQL object-relational database and is currently the most popular open source spatial databases. If you want to explore the complete range of PostGIS techniques and expose related extensions, then this book is for you. This book is a comprehensive guide to PostGIS tools and concepts which are required to manage, manipulate, and analyze spatial data in PostGIS. It covers key spatial data manipulation tasks, explaining not only how each task is performed, but also why. It provides practical guidance allowing you to safely take advantage of the advanced technology in PostGIS in order to simplify your spatial database administration tasks. Furthermore, you will learn to take advantage of basic and advanced vector, raster, and routing approaches along with the concepts of data maintenance, optimization, and performance, and will help you to integrate these into a large ecosystem of desktop and web tools. By the end, you will be armed with all the tools and instructions you need to both manage the spatial database system and make better decisions as your project's requirements evolve.
Table of Contents (18 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Calculating the driving distance/service area


Driving distance (pgr_drivingDistance) is a query that calculates all nodes within the specified driving distance of a starting node. This is an optional function compiled with pgRouting; so if you compile pgRouting yourself, make sure that you enable it and include the CGAL library, an optional dependency for pgr_drivingDistance.

Driving distance is useful when user sheds are needed that give realistic driving distance estimates, for example, for all customers with five miles driving, biking, or walking distance. These estimates can be contrasted with buffering techniques, which assume no barrier to travelling and are useful for revealing the underlying structures of our transportation networks relative to individual locations.

Getting ready

We will load the same dataset that we used in the Startup – Dijkstra routing recipe. Refer to this recipe to import data.

How to do it...

In the following example, we will look at all users within a distance...