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

Summary


This chapter covered the critical components of GIS analysis including:

  • The challenges of measuring on the curved surface of the Earth and solutions

  • The basics of coordinate conversion between the geographic and UTM reference systems

  • Reprojection using OGR (pretty much the only game in town worthwhile!)

  • Details about editing shapefiles in pure Python using PyShp

  • Performing spatial selections on data using geometry or attributes

  • Creating thematic maps from scratch using only Python

  • Importing data from spreadsheets

  • Parsing GPS data from NMEA or GPX

As a geospatial analyst, you may be familiar with both GIS and remote sensing, but most analysts specialize in one field or the other. That is why this book approaches the fields in separate chapters, to focus on their differences. In Chapter 6, Python and Remote Sensing, we'll tackle remote sensing. In GIS, we have been able to explore the field using pure Python modules. In remote sensing, we'll become more dependent on bindings to compiled modules...