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
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


In this chapter, we covered the foundations of remote sensing including band swapping, histograms, image classification, feature extraction, and change detection. As in the other chapters, we stayed as close to pure Python as possible, and where we compromised on this goal for the processing speed, we limited the software libraries as much as possible to keep things simple. However, if you have the tools from this chapter installed, you really have a complete remote sensing package that is limited only by your desire to learn.

Tip

The authors of GDAL have a set of Python examples, which cover some advanced topics that may be of interest:

https://svn.osgeo.org/gdal/trunk/gdal/swig/python/samples/

In the next chapter, we'll investigate elevation data. Elevation data doesn't fit squarely in GIS or remote sensing as it has elements of both types of processing.