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

Common raster data concepts

As we mentioned earlier, remotely sensed raster data is a matrix of numbers. Remote sensing contains thousands of operations that can be performed on data. This field changes on almost a daily basis as new satellites are put into space and computer power increases.

Despite its decade-long history, we haven't even scratched the surface of the knowledge that this field can provide to the human race. Once again, similar to the common GIS processes, this minimal list of operations allows you to evaluate any technique that's used in remote sensing.

Band math

Band math is multidimensional array mathematics. In array math, arrays are treated as single units, which are added, subtracted, multiplied...