Book Image

Learning Geospatial Analysis with Python

By : Joel Lawhead
Book Image

Learning Geospatial Analysis with Python

By: Joel Lawhead

Overview of this book

Geospatial Analysis is used in almost every field you can think of from medicine, to defense, to farming. This book will guide you gently into this exciting and complex field. It walks you through the building blocks of geospatial analysis and how to apply them to influence decision making using the latest Python software. Learning Geospatial Analysis with Python, 2nd Edition uses the expressive and powerful Python 3 programming language to guide you through geographic information systems, remote sensing, topography, and more, while providing a framework for you to approach geospatial analysis effectively, but on your own terms. We start by giving you a little background on the field, and a survey of the techniques and technology used. We then split the field into its component specialty areas: GIS, remote sensing, elevation data, advanced modeling, and real-time data. This book will teach you everything you need to know about, Geospatial Analysis from using a particular software package or API to using generic algorithms that can be applied. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you don’t become bogged down in just getting ready to do analysis. This book will round out your technical library through handy recipes that will give you a good understanding of a field that supplements many a modern day human endeavors.
Table of Contents (17 chapters)
Learning Geospatial Analysis with Python Second Edition
About the Author
About the Reviewers

Working with

The name of our program is As we saw in the Tag-based and markup-based formats section, in Chapter 2, Geospatial Data, the GPX format is the most common way to store GPS route information. Nearly every program and device relying on GPS data can convert to and from GPX.

For this example, you can download a sample GPX file from at

You will also need to install a few Python libraries from PyPI. If you've worked through the rest of this book, you'll have most of them already:

  • PIL: The Python Imaging Library

  • Numpy: The multidimensional, array-processing library

  • Pygooglechart: A Python wrapper for the excellent Google Chart API

  • Fpdf: A simple, pure python PDF writer

Simply use easy_install or pip to install these tools. We will also be using a module called This module is a utility to work with near-global elevation data collected during the 11-day Shuttle Radar Topography Mission in 2000 by the Space Shuttle, Endeavor. However...