Book Image

Learning Geospatial Analysis with Python

By : Joel Lawhead
4 (1)
Book Image

Learning Geospatial Analysis with Python

4 (1)
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. It is an approach to use statistical analysis and other informational engineering to data which has a geographical or geospatial aspect. And this typically involves applications capable of geospatial display and processing to get a compiled and useful data. "Learning Geospatial Analysis with Python" uses the expressive and powerful Python programming language to guide you through geographic information systems, remote sensing, topography, and more. It explains how to use a framework in order to approach Geospatial analysis effectively, but on your own terms. "Learning Geospatial Analysis with Python" starts with a background of the field, a survey of the techniques and technology used, and then splits the field into its component speciality areas: GIS, remote sensing, elevation data, advanced modelling, and real-time data. This book will teach you everything there is to know, from using a particular software package or API to using generic algorithms that can be applied to Geospatial analysis. 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. "Learning Geospatial Analysis with Python" will round out your technical library with handy recipes and a good understanding of a field that supplements many a modern day human endeavors.
Table of Contents (17 chapters)
Learning Geospatial Analysis with Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Desktop tools


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 data in any way. The second category allows you to perform those items as well but also edit data. 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 analysis category...