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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

Core GIS concepts

Working with geospatial data is complicated because you are dealing with mathematical models of the Earth's surface. In many ways, it is easy to think of the Earth as a sphere on which you can place your data. That might be easy, but it isn't accurate—the Earth is more like an oblate spheroid than a perfect sphere. This difference, as well as other mathematical complexities that we won't get into here, means that representing points, lines, and areas on the surface of the Earth is a rather complicated process.

Let's take a look at some of the key GIS concepts you will have to become familiar with as you work with geospatial data.

Location

Locations represent points on the surface of the Earth. One of the most common ways of measuring location is through the use of latitude and longitude coordinates. For example, my current location (as measured by a GPS receiver) is 38.167446 degrees south and 176.234436 degrees east. What do these numbers mean...

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