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

Dealing with projections


One of the challenges of working with geospatial data is that geodetic locations (points on the Earth's surface) are often mapped onto a two-dimensional Cartesian plane using a cartographic projection. We looked at projections in the previous chapter: whenever you have some geospatial data, you need to know which projection that data uses. You also need to know the datum (model of the Earth's shape) assumed by the data.

A common challenge when dealing with geospatial data is that you have to convert data from one projection or datum to another. Fortunately, there is a Python library that makes this task easy: pyproj.

pyproj

pyproj is a Python "wrapper" around another library called PROJ.4. PROJ.4 is an abbreviation for version 4 of the PROJ library. PROJ was originally written by the US Geological Survey for dealing with map projections and has been widely used in geospatial software for many years. The pyproj library makes it possible to access the functionality of...