Book Image

Python Geospatial Development

By : Erik Westra
Book Image

Python Geospatial Development

By: Erik Westra

Overview of this book

<p>Open Source GIS (Geographic Information System) is a growing area with the explosion of applications such as Google Maps, Google Earth, and GPS. The GIS market is growing rapidly and as a Python developer you will find yourself either wanting grounding in GIS or needing to get up to speed to do your job. In today's location-aware world, all commercial Python developers can benefit from an understanding of GIS development gained using this book.</p> <p>Working with geo-spatial data can get complicated because you are dealing with mathematical models of the Earth's surface. Since Python is a powerful programming language with high-level toolkits, it is well suited to GIS development. will familiarize you with the Python tools required for geo-spatial development such as Mapnik, which is used for mapping in Python. It introduces GIS at the basic level with a clear, detailed walkthrough of the key GIS concepts such as location, distance, units, projections, datums, and GIS data formats. We then examine a number of Python libraries and combine these with geo-spatial data to accomplish a variety of tasks. The book provides an in-depth look at the concept of storing spatial data in a database and how you can use spatial databases as tools to solve a variety of geo-spatial problems. <br /><br />It goes into the details of generating maps using the Mapnik map-rendering toolkit, and helps you to build a sophisticated web-based geo-spatial map-editing application using GeoDjango, Mapnik, and PostGIS. By the end of the book, you will be able to integrate spatial features into your applications and build a complete mapping application from scratch.</p>
Table of Contents (19 chapters)
Python Geospatial Development
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Working with GIS data manually


Let's take a brief look at the process of working with GIS data manually. Before we can begin, there are two things you need to do:

  • Obtain some GIS data

  • Install the GDAL Python library so that you can read the necessary data files

Let's use the U.S. Census Bureau's website to download a set of vector maps for the various U.S. states. The main site for obtaining GIS data from the U.S. Census Bureau can be found at:

http://www.census.gov/geo/www/tiger

To make things simpler, though, let's bypass the website and directly download the file we need:

http://www2.census.gov/geo/tiger/TIGER2009/tl_2009_us_state.zip

The resulting file, tl_2009_us_state.zip, should be a ZIP-format archive. After uncompressing the archive, you should have the following files:

tl_2009_us_state.dbf
tl_2009_us_state.prj
tl_2009_us_state.shp
tl_2009_us_state.shp.xml
tl_2009_us_state.shx

These files make up a Shapefile containing the outlines of all the U.S. states. Place these files together...