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


Real-time data is an exciting way to do new types of geospatial analysis, which has been made possible only recently by the advances in several different technologies, including web mapping, GPS, and wireless communications. In this chapter, you learned how to access raw feeds for real-time location data, how to acquire a subset of a real-time raster data, how to combine different types of real-time data into a custom map analysis product using only Python, and how to build client-server geospatial applications to update a GIS in real time.

As with the previous chapters, these examples contain building blocks that will let you build new types of applications using Python that go far beyond the typical popular and ubiquitous JavaScript-based mash-up.

In the final chapter, we will combine everything that you've learned so far into a complete geospatial application, which applies the algorithms and concepts to a realistic scenario.