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Python Geospatial Development

You're reading from   Python Geospatial Development Develop sophisticated mapping applications from scratch using Python 3 tools for geospatial development

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Product type Paperback
Published in May 2016
Publisher
ISBN-13 9781785288937
Length 446 pages
Edition 3rd Edition
Languages
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Author (1):
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Erik Westra Erik Westra
Author Profile Icon Erik Westra
Erik Westra
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Table of Contents (15) Chapters Close

Preface 1. Geospatial Development Using Python FREE CHAPTER 2. GIS 3. Python Libraries for Geospatial Development 4. Sources of Geospatial Data 5. Working with Geospatial Data in Python 6. Spatial Databases 7. Using Python and Mapnik to Generate Maps 8. Working with Spatial Data 9. Improving the DISTAL Application 10. Tools for Web-based Geospatial Development 11. Putting It All Together – a Complete Mapping System 12. ShapeEditor – Importing and Exporting Shapefiles 13. ShapeEditor – Selecting and Editing Features 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 library and its Python bindings so that you can read the necessary data files

Obtaining the data

Let's use the US Census Bureau's web site to download a set of vector maps for the various US states. The main site for obtaining GIS data from the US Census Bureau can be found at http://www.census.gov/geo/www/tiger.

To make things simpler, though, let's bypass the web site and directly download the file we need from http://www2.census.gov/geo/tiger/TIGER2014/STATE/tl_2014_us_state.zip.

The file, tl_2014_us_state.zip, should be a ZIP-format archive. After uncompressing the archive, you should have a directory containing the following files:

  • tl_2014_us_state.dbf
  • tl_2014_us_state.prj
  • tl_2014_us_state.shp
  • tl_2014_us_state.shx

These files make up a shapefile containing the outlines of all...

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