Book Image

Learning Geospatial Analysis with Python - Third Edition

By : Joel Lawhead
Book Image

Learning Geospatial Analysis with Python - Third Edition

By: Joel Lawhead

Overview of this book

Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. With this systematic guide, you'll get started with geographic information system (GIS) and remote sensing analysis using the latest features in Python. This book will take you through GIS techniques, geodatabases, geospatial raster data, and much more using the latest built-in tools and libraries in Python 3.7. You'll learn everything you need to know about using software packages or APIs and generic algorithms that can be used for different situations. Furthermore, you'll learn how to apply simple Python GIS geospatial processes to a variety of problems, and work with remote sensing data. By the end of the book, you'll be able to build a generic corporate system, which can be implemented in any organization to manage customer support requests and field support personnel.
Table of Contents (15 chapters)
Free Chapter
Section 1: The History and the Present of the Industry
Section 2: Geospatial Analysis Concepts
Section 3: Practical Geospatial Processing Techniques


Geospatial datasets are very large. Processing them can take time, which can be hours or sometimes even days. But there's a way you can speed processing up for certain operations. Python's built-in multiprocessing module can spawn multiple processes on your computer to take advantage of all of the available processors.

One operation that works really well with the multiprocessing module is geocoding. In this example, we'll geocode a list of cities and split that processing across all of the processors on your machine. We'll use the same geocoding technique as before, but this time, we'll add the multiprocessing module to increase the potential for greater speed and scalability. The following code will geocode a list of cities simultaneously across multiple processors:

  1. First, we import the modules we need:
# Import our geocoding module...