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
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Computer-aided drafting


Computer-aided drafting (CAD) is worth mentioning, though it does not directly relate to geospatial analysis. The history of CAD system development parallels and intertwines with the history of geospatial analysis. CAD is an engineering tool used to model two- and three-dimensional objects usually for engineering and manufacturing. The primary difference between a geospatial model and CAD model is that a geospatial model is referenced to the Earth, whereas a CAD model can possibly exist in abstract space. For example, a three-dimensional blueprint of a building in a CAD system would not have a latitude or longitude, but in a GIS, the same building model would have a location on the Earth. However, over the years, CAD systems have taken on many features of GIS systems and are commonly used for smaller GIS projects. Likewise, many GIS programs can import CAD data that has been georeferenced. Traditionally, CAD tools were designed primarily for the engineering of data that was not geospatial.

However, engineers who became involved with geospatial engineering projects, such as designing a city utility electric system, would use the CAD tools that they were familiar with in order to create maps. Over time, both the GIS software evolved to import the geospatial-oriented CAD data produced by engineers, and CAD tools evolved to support geospatial data creation and better compatibility with GIS software. AutoCAD by Autodesk and ArcGIS by Esri were the leading commercial packages to develop this capability and the Geospatial Data Abstraction Library (GDAL) OGR library developers added CAD support as well.