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)
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Section 1: The History and the Present of the Industry
Section 2: Geospatial Analysis Concepts
Section 3: Practical Geospatial Processing Techniques

Geospatial Python Toolbox

The first three chapters of this book covered the history of geospatial analysis, the types of geospatial data that are used by analysts, and the major software and libraries found within the geospatial industry. We used some simple Python examples here and there to illustrate certain points, but we mainly focused on the field of geospatial analysis, independent of any specific technology. Starting here, we will be using Python to conquer geospatial analysis and we will continue with that approach for the rest of this book. This chapter explains the software you will need in your toolbox to do just about anything you want in the geospatial field.

We'll discover the Python libraries that are used to access the different types of data that were found in the vector data and raster data sections of Chapter 2, Learning Geospatial Data. Some of these libraries...