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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

Changing datums and projections


In Chapter 2, GIS, we saw that a datum is a mathematical model of the earth's shape, while a projection is a way of translating points on the earth's surface into points on a two-dimensional map. There are a large number of available datums and projections—whenever you are working with geospatial data, you must know which datum and which projection (if any) your data uses. If you are combining data from multiple sources, you will often have to change your geospatial data from one datum to another or from one projection to another.

Task – changing projections to combine shapefiles using geographic and UTM coordinates

In this recipe, we will work with two shapefiles that have different projections. We haven't yet encountered any geospatial data that uses a projection—all the data we've seen so far used geographic (unprojected) latitude and longitude values. So, let's start by downloading some geospatial data in the Universal Transverse Mercator (UTM) projection...

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