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

Measuring distance


The essence of geospatial analysis is discovering the relationships of objects on the Earth. Items which are closer together tend to have a stronger relationship than those which are farther apart. Therefore measuring distance is a critical function of geospatial analysis.

As we have learned, every map is a model of the Earth and they are all wrong to some degree. For this reason, measuring accurate distance between two points on the Earth while sitting in front of a computer is impossible. Even professional land surveyors who go out in the field with both traditional sighting equipment and very precise GPS equipment fail to account for every anomaly in the Earth's surface between point A and point B. So in order to measure distance, we must look at what we are measuring, how much we are measuring, and how much accuracy we need.

There are three models of the Earth we can use to calculate distance:

  • Flat plane

  • Spherical

  • Ellipsoid

In the flat plane model, standard Euclidean geometry...