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

Dot density calculations

A dot density map shows concentrations of subjects within a given area. If an area is divided into polygons containing statistical information, you can model that information using randomly distributed dots within that area using a fixed ratio across the dataset. This type of map is commonly used for population density maps. The cat map in Chapter 1, Learning Geospatial Analysis with Python, is a dot density map. Let's create a dot density map from scratch using pure Python. Pure Python allows you to work with much lighter weight libraries that are generally easier to install and are more portable. For this example, we'll use a U.S. Census Bureau Tract shapefile along the U.S. Gulf Coast, which contains population data. We'll also use the point in polygon algorithm to ensure that the randomly distributed points are within the proper census tract. Finally, we'll use the PNGCanvas module to write out our image.

The PNGCanvas module is excellent and fast. However, it...