Book Image

Python Geospatial Development - Third Edition

By : Erik Westra
Book Image

Python Geospatial Development - Third Edition

By: Erik 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 (20 chapters)
Python Geospatial Development Third Edition
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
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...