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

Sources of other types of geospatial data


The vector and raster geospatial data we have looked at so far is generally used to provide images or information about the Earth itself. However, geospatial applications often have to place data onto the surface of the Earth, that is, georeference something such as a place or event. In this section, we will look at two additional databases that provide information about the location of cities, towns, natural features, and points of interest on the surface of the Earth.

This data can be used in two important ways. First, it can be used to label features, for example, to place the label "London" onto a georeferenced image of southern England. Secondly, this data can be used to locate something by name, for example, by allowing the user to choose a city from a drop-down list and then draw a map centered around that city.

The GEOnet Names Server

The GEOnet Names Server provides a large database of place names. It is an official repository of non-American...