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

Desktop tools (including visualization)

Geospatial analysis requires the ability to visualize output in order to be complete. This fact makes tools, which can visualize data absolutely critical to the field. There are two categories of geospatial visualization tools. The first is geospatial viewers and the second is geospatial analysis software. The first category—geospatial viewers, allows you to access, query, and visualize data but not edit it in any way. The second category allows you to perform those items and edit data too. The main advantage of viewers is that they are typically lightweight pieces of software that launch and load data quickly. Geospatial analysis software requires far more resources to be able to edit complex geospatial data, so it loads slower and often renders data more slowly to provide dynamic editing functionality.

Quantum GIS

Quantum GIS, more commonly known as QGIS, is a complete open source geographic information system. QGIS falls well within the geospatial...