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

Importance of geospatial analysis


Geospatial analysis helps people make better decisions. It doesn't make the decision for you, but it can answer critical questions which are at the heart of the choice to be made and often cannot be answered any other way. Until recently geospatial technology and data were tools available only to governments, and well-funded researchers. But in the last decade data have become much more widely available and software much more accessible to anyone.

In addition to freely available government satellite imagery, many local governments now conduct aerial photo surveys and make the data available online. The ubiquitous Google Earth provides a cross-platform spinning globe view of the Earth with satellite and aerial data, streets, points of interest, photographs, and much more. Google Earth users can create custom KML files, which are XML files to load and style data onto the globe. This program and similar tools are often called geographic exploration tools, because they are excellent data viewers but provide very limited data analysis capability.

The ambitious OpenStreetMap project (http://openstreetmap.org) is a crowd-sourced, worldwide, geographic basemap containing most layers commonly found in a GIS. Nearly every mobile phone contains a GPS now, along with mobile apps to collect GPS tracks as points, lines, or polygons. Most phones will also tag photos taken with the phone's camera with a GPS coordinate. In short, anyone can be a geospatial analyst.

The global population has reached seven billion people. And the world is changing faster than ever before. The planet is undergoing environmental changes never seen before in recorded history. Faster communication and faster transportation increase the interaction between us and the environment in which we live. Managing people and resources safely and responsibly is more challenging than ever. Geospatial analysis is the best approach to understanding our world more efficiently and deeply. The more politicians, activists, relief workers, parents, teachers, first responders, medical professionals, and small businesses harness the power of geospatial analysis the more our potential for a better, healthier, safer, fairer world will be realized.