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

Introduction


Unlike prior chapters, this chapter does not discuss the capabilities or applications of PostGIS. Instead, it focuses on the techniques for organizing the database, improving the query performance, and ensuring the long-term viability of the spatial data.

These techniques are frequently ignored by most PostGIS users until it is too late - for example, when data has already been lost because of users' actions or the performance has already decreased as the volume of data or number of users increased.

Such neglect is often due to the amount of time required to learn about each technique, as well as the time it takes implement them. This chapter attempts to demonstrate each technique in a distilled manner that minimizes the learning curve and maximizes the benefits.