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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
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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

Sources of geospatial data in raster format


One of the most enthralling aspects of programs such as Google Earth is the ability to "see" the Earth as you appear to fly above it. This is achieved by displaying satellite and aerial photographs carefully stitched together to provide the illusion that you are viewing the Earth's surface from above.

While writing your own version of Google Earth would be an almost impossible task, it is possible to obtain free satellite imagery in the form of raster-format geospatial data, which you can then use in your own geospatial applications.

Raster data is not just limited to images of the Earth's surface, however; other useful information can be found in raster format—for example, digital elevation maps (DEMs) contain the height of each point on the Earth's surface, which can then be used to calculate the elevation of any desired point. DEM data can also be used to generate two-dimensional images that represent different heights using different shades or...

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