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

Creating elevation contours

Now, let's look at another way to visualize the elevation better using contours. A contour is an isoline along the same elevation in a dataset. Contours are usually stepped at intervals to create an intuitive way to represent elevation data, both visually and numerically, using a resource-efficient vector dataset.

The input to generate contours is our DEM and the output is a shapefile. The algorithm to generate contours is fairly complex and very difficult to implement using NumPy's linear algebra. So, our solution in this case is to fall back on the GDAL library, which has a contouring method available through the Python API. In fact, the majority of this script is just setting up the OGR library code that is needed to output a shapefile. The actual contouring is a single method call named gdal.ContourGenerate(). Just before this call, there are comments defining the method's arguments. The most important ones are as follows:

  • contourInterval: It is the distance...