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


There are several ways to write PostGIS programs, and in this chapter we will see a few of them. You will mainly use the Python language throughout this chapter. Python is a fantastic language with a plethora of GIS and scientific libraries that can be combined with PostGIS to write awesome geospatial applications.

If you are new to Python, you can quickly get productive with these excellent web resources:

You can combine Python with some excellent and popular libraries, such as:

  • Psycopg: This is the most complete and popular Python DB API implementation for PostgreSQL; see http://initd.org/psycopg/
  • GDAL: Used to unchain the powerful GDAL library in your Python scripts; see http://www.gdal.org/gdal_tutorial.html
  • requests: This is a handy Python standard library to manage HTTP stuff, such as opening URLs
  • simplejson: This is a simple and fast JSON encoder...