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Python Geospatial Development

Python Geospatial Development - Third Edition

By : Westra
4.3 (4)
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Python Geospatial Development

Python Geospatial Development

4.3 (4)
By: Westra

Overview of this book

Geospatial development links your data to locations on the surface of the Earth. Writing geospatial programs involves tasks such as grouping data by location, storing and analyzing large amounts of spatial information, performing complex geospatial calculations, and drawing colorful interactive maps. In order to do this well, you’ll need appropriate tools and techniques, as well as a thorough understanding of geospatial concepts such as map projections, datums, and coordinate systems. This book provides an overview of the major geospatial concepts, data sources, and toolkits. It starts by showing you how to store and access spatial data using Python, how to perform a range of spatial calculations, and how to store spatial data in a database. Further on, the book teaches you how to build your own slippy map interface within a web application, and finishes with the detailed construction of a geospatial data editor using the GeoDjango framework. By the end of this book, you will be able to confidently use Python to write your own geospatial applications ranging from quick, one-off utilities to sophisticated web-based applications using maps and other geospatial data.
Table of Contents (15 chapters)
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14
Index

Chapter 6. Spatial Databases

In this chapter, we will look at how you can use a PostGIS database to store and work with spatial data. In particular, we will cover:

  • The concept of a spatially enabled database
  • Spatial indexes and how they work
  • How PostGIS acts as an extension to the PostgreSQL relational database
  • How to install PostgreSQL, PostGIS, and the psycopg2 Python database adapter onto your computer
  • How to set up and configure a spatial database using PostGIS
  • How to use the psycopg2 database adapter to access a spatial database from your Python code
  • How to create, import, and query against spatial data using Python
  • Recommended best practices for storing spatial data in a database

This chapter is intended to be an introduction to using databases in a geospatial application. Chapter 8, Working with Spatial Data, will build on this to perform powerful spatial queries not possible using shapefiles and other geospatial data files.

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