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

Simplifying geometries


There will be many times when you will need to generate a less detailed and lighter version of a vector dataset, as you may not need very detailed features for several reasons. Think about a case where you are going to publish the dataset to a website and performance is a concern, or maybe you need to deploy the dataset to a colleague who does not need too much detail because they are using it for a large-area map. In all these cases, GIS tools include implementations of simplification algorithms that reduce unwanted details from a given dataset. Basically, these algorithms reduce the vertex numbers comprised in a certain tolerance, which is expressed in units measuring distance.

For this purpose, PostGIS provides you with the ST_Simplify and ST_SimplifyPreserveTopology functions. In many cases, they are the right solutions for simplification tasks, but in some cases, especially for polygonal features, they are not the best option out there and you will need a different...