Book Image

Learning Geospatial Analysis with Python

By : Joel Lawhead
Book Image

Learning Geospatial Analysis with Python

By: Joel Lawhead

Overview of this book

Geospatial Analysis is used in almost every field you can think of from medicine, to defense, to farming. This book will guide you gently into this exciting and complex field. It walks you through the building blocks of geospatial analysis and how to apply them to influence decision making using the latest Python software. Learning Geospatial Analysis with Python, 2nd Edition uses the expressive and powerful Python 3 programming language to guide you through geographic information systems, remote sensing, topography, and more, while providing a framework for you to approach geospatial analysis effectively, but on your own terms. We start by giving you a little background on the field, and a survey of the techniques and technology used. We then split the field into its component specialty areas: GIS, remote sensing, elevation data, advanced modeling, and real-time data. This book will teach you everything you need to know about, Geospatial Analysis from using a particular software package or API to using generic algorithms that can be applied. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you don’t become bogged down in just getting ready to do analysis. This book will round out your technical library through handy recipes that will give you a good understanding of a field that supplements many a modern day human endeavors.
Table of Contents (17 chapters)
Learning Geospatial Analysis with Python Second Edition
About the Author
About the Reviewers

Python networking libraries for acquiring data

The vast majority of geospatial data sharing is accomplished via the Internet. And Python is well equipped when it comes to networking libraries for almost any protocol. Automated data downloads are often an important step in automating a geospatial process. Data is typically retrieved from a website Uniform Resource Locator (URL) or a File Transfer Protocol (FTP) server. And because geospatial datasets often contain multiple files, data is often distributed as ZIP files.

A nice feature of Python is its concept of a file-like object. Most Python libraries which read and write data use a standard set of methods which allow you to access data from all different types of resources as if you were writing a simple file on disk. The networking modules in the Python standard library use this convention as well. The benefit of this approach is that it allows you to pass file-like objects to other libraries and methods, which recognize the convention...