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

The NextBus route list

The tag attribute is the ID for Thunder Bay that we need for the other NextBus API commands. The other attributes are human readable metadata. The next piece of information that we need is the details about the Route 2 bus route. To get this information, we'll use the agency ID and the REST routeList command to get another XML document by pasting the URL to our web browser. Note that the agency ID is set to the a parameter in the REST URL:

When we call this URL in a browser, we get the following XML document:

<?xml version="1.0" encoding="utf-8" ?>
<body copyright="All data copyright Los Angeles Metro 2015.">
<route tag="2" title="2 Downtown LA - Pacific Palisades Via"/>
<route tag="4" title="4 Downtown LA - Santa Monica Via Santa"/>
<route tag="10" title="10 W Hollywood-Dtwn LA -Avalon Sta Via"/>
<route tag="901" title="901 Metro Orange Line"/&gt...