Book Image

Learning Geospatial Analysis with Python - Fourth Edition

By : Joel Lawhead
4 (1)
Book Image

Learning Geospatial Analysis with Python - Fourth Edition

4 (1)
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. In this special 10th anniversary edition, you'll embark on an exhilarating geospatial analysis adventure using Python. This fourth edition starts with the fundamental concepts, enhancing your expertise in geospatial analysis processes with the help of illustrations, basic formulas, and pseudocode for real-world applications. As you progress, you’ll explore the vast and intricate geospatial technology ecosystem, featuring thousands of software libraries and packages, each offering unique capabilities and insights. This book also explores practical Python GIS geospatial applications, remote sensing data, elevation data, and the dynamic world of geospatial modeling. It emphasizes the predictive and decision-making potential of geospatial technology, allowing you to visualize complex natural world concepts, such as environmental conservation, urban planning, and disaster management to make informed choices. You’ll also learn how to leverage Python to process real-time data and create valuable information products. By the end of this book, you'll have acquired the knowledge and techniques needed to build a complete geospatial application that can generate a report and can be further customized for different purposes.
Table of Contents (18 chapters)
1
Part 1:The History and the Present of the Industry
5
Part 2:Geospatial Analysis Concepts
11
Part 3:Practical Geospatial Processing Techniques

To get the most out of this book

This book assumes you have basic knowledge of the Python programming language. You will require the Anaconda 2.4.0 or higher with Python (3.10 or higher); a minimum hardware requirement of a 300-MHz processor, 128 MB of RAM, and 1.5 GB of available hard disk; and a Windows, Linux, or macOS X operating system.

Software/hardware covered in the book

Operating system requirements

Anaconda 2.4.0 or higher

Windows – 64-bit x86; macOS – 64-bit x86 and M1; or Linux – 64-bit x86, 64-bit aarch64 (AWS Graviton2), 64-bit Power8/Power9, or s390x (Linux on IBM Z and LinuxONE)

Python 3.10 or higher

8 GB of RAM

ECMAScript 11

6 GB of disk space or more

Follow the instructions for the latest Anaconda installation. All scripts in this book assume you will run the code from the command line within an Anaconda Python environment. If you try to use Jupyter Notebooks, you may get unpredictable results.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

The GitHub repository contains folders for each chapter that include all code in the book, as well as color images and geospatial data files needed for the examples.