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Python Geospatial Analysis Cookbook

You're reading from   Python Geospatial Analysis Cookbook Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781783555079
Length 310 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (15) Chapters Close

Preface 1. Setting Up Your Geospatial Python Environment FREE CHAPTER 2. Working with Projections 3. Moving Spatial Data from One Format to Another 4. Working with PostGIS 5. Vector Analysis 6. Overlay Analysis 7. Raster Analysis 8. Network Routing Analysis 9. Topology Checking and Data Validation 10. Visualizing Your Analysis 11. Web Analysis with GeoDjango A. Other Geospatial Python Libraries
B. Mapping Icon Libraries
Index

Creating a hillshade raster from your DEM with ogr


Our DEM can be the basis for many types of derived raster datasets. One of these derivatives is the so called hillshade raster dataset. A hillshade raster represents a 2D view of 3D elevation data, assigning gray raster shades and giving them a 3D effect by enabling you to see the highs and lows of your terrain. The hillshade is a pure visualization helper to create a nice looking map and show relief on a 2D map.

The pure Python solution to creating a hillshade is written by Roger Veciana i Rovira and you can find it at http://geoexamples.blogspot.co.at/2014/03/shaded-relief-images-using-gdal-python.html. There is also a nice solution by Joel Lawhead in Chapter 7, Python and Elevation Data of Learning Geospatial Analysis with Python. For those of you looking for a detailed description of the hillshade from ESRI, check this page out at http://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?TopicName=How%20Hillshade%20works. The gdaldem hillshade...

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