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 with demographics


In the Using polygon overlays for proportional census estimates recipe in Chapter 2, Structures That Work, we employed a simple buffer around a trail alignment in conjunction with the census data to get estimates of what the demographics were of the people within walking distance of the trail, estimated as a mile long. The problem with this approach, of course, is that it assumes that it is an "as the crow flies" estimate. In reality, rivers, large roads, and roadless stretches serve as real barriers to people's movement through space. Using pgRouting's pgr_drivingDistance function, we can realistically simulate people's movement on the routable networks and get better estimates. For our use case, we'll keep the simulation a bit simpler than a trail alignment—we'll consider the demographics of a park facility, say, the Cleveland Metroparks Zoo, and potential bike users within 4 miles of it, which adds up approximately to a 15-minute bike...