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
1
Section 1: The History and the Present of the Industry
5
Section 2: Geospatial Analysis Concepts
10
Section 3: Practical Geospatial Processing Techniques

Python virtualenv

Python geospatial analysis requires that we use a variety of modules with many dependencies. These modules often build on each other using specific versions of C or C++ libraries. You often run into version conflicts as you add Python modules to your system. Sometimes, when you upgrade a particular module, it might break your existing Python program due to changes in the API – or maybe you are running both Python 2 and Python 3 to take advantage of libraries written for each version. What you need is a way to safely install new modules without corrupting a working system or code. The solution to that issue is to use Python virtual environments through the virtualenv module.

The Python virtualenv module creates isolated, individual Python environments for each project so that you can avoid conflicting modules polluting your main Python installation. You...