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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

Introducing PostGIS


In this book, we will be working with PostGIS. PostGIS is one of the most popular and powerful geospatial databases and has the bonus of being open source and freely available. PostGIS itself is actually an extension to the PostgreSQL relational database system—to use PostGIS from your Python programs, you first have to install and set up PostgreSQL, then install the PostGIS extension, and then finally install the psycopg2 database adapter for Python. The following illustration shows how all these pieces fit together:

Tip

Note that PostgreSQL is often referred to as Postgres. We will regularly use this more colloquial name throughout this book.

PostGIS allows you to store and query against various types of spatial data, including points, lines, polygons, and geometry collections. PostGIS provides two different types of spatial fields that can be used to store spatial data:

  • The geometry field holds spatial data that is assumed to be in a projected coordinate system. All calculations...

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