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Learning Geospatial Analysis with Python

You're reading from   Learning Geospatial Analysis with Python If you know Python and would like to use it for Geospatial Analysis this book is exactly what you've been looking for. With an organized, user-friendly approach it covers all the bases to give you the necessary skills and know-how.

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Product type Paperback
Published in Oct 2013
Publisher Packt
ISBN-13 9781783281138
Length 364 pages
Edition 1st Edition
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Author (1):
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Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
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Table of Contents (12) Chapters Close

Preface 1. Learning Geospatial Analysis with Python 2. Geospatial Data FREE CHAPTER 3. The Geospatial Technology Landscape 4. Geospatial Python Toolbox 5. Python and Geographic Information Systems 6. Python and Remote Sensing 7. Python and Elevation Data 8. Advanced Geospatial Python Modelling 9. Real-Time Data 10. Putting It All Together Index

Creating elevation contours


Now let's look at another way to better visualize elevation using contours. A contour is an isoline along the same elevation in a data set. Contours are usually stepped at intervals to create an intuitive way to represent elevation data, both visually and numerically, using a resource efficient vector data set.

The input for generating contours is our DEM and the output is a shapefile. The algorithm for generating contours is fairly complex and very difficult to implement using NumPy's linear algebra. So our solution in this case is to fall back on the GDAL library, which has a contouring method available through the Python API. In fact, the majority of this script is just setting up the OGR library code needed to output shapefile. The actual contouring is a single method call named gdal.ContourGenerate() . Just before that call, there are comments defining the method's arguments. The most important ones are as follows:

  • contourInterval: It is the distance in data...

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