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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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 Westra Westra
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Westra
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Table of Contents (20) Chapters Close

Python Geospatial Development Third Edition
Credits
About the Author
About the Reviewer
www.PacktPub.com
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

Summary


In this chapter, we surveyed a number of sources of freely-available geospatial data. For vector-format data, we looked at OpenStreetMap, a collaborative site where people can create and edit vector maps worldwide; TIGER, which is a service of the US Census Bureau; the Natural Earth Data web site; the GSHHG high-resolution shoreline database; and the simple but effective World Borders Dataset.

For geospatial data in raster format, we looked at Landsat imagery, the GLOBE digital elevation model, and the high-resolution National Elevation Dataset for the US and its protectorates.

We then looked at two sources of place name data: the GEOnet Names Server, which provides information about official place names for every country other than the US and Antarctica, and GNIS, which provides official place names for the United States.

This completes our survey of geospatial data sources. In the next chapter, we will use the Python toolkits described in Chapter 3, Python Libraries for Geospatial...

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