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

Using GPS data

The most common type of GPS data these days is the Garmin GPX format. We covered this XML format in Chapter 4, Geospatial Python Toolbox, which has become an unofficial industry standard. Because it is an XML format, all of the well documented rules of XML apply. However, there is another type of GPS data that pre-dates XML and GPX called National Marine Electronics Association (NMEA). These data are ASCII text sentences designed to be streamed. You occasionally bump into this format from time to time because even though it is older and esoteric, it is still very much alive and well especially to communicate ship locations via the Automated Identification System (AIS), which tracks ships globally. But as usual, you have a good option in pure Python. The pynmea module is available on PyPI.

Take a look at the following small sample of NMEA sentences: