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

Point cloud data

Point cloud data is any data collected as the (x, y, z) location of a surface point based on some sort of focused energy return. Point cloud data can be created using lasers, radar waves, acoustic soundings, or other waveform generation devices. The spacing between points is arbitrary and dependent on the type and position of the sensor collecting the data. In this book, we will primarily be concerned with LIDAR data and radar data. Radar point cloud data is typically collected on space missions while LIDAR is typically collected by terrestrial or airborne vehicles. Conceptually, both the types of data are similar.

LIDAR uses powerful laser range-finding systems to model the world with very high precision. The term LIDAR or LiDAR is a combination of the words light and radar. Some people claim it also stands for Light Detection and Ranging. LIDAR sensors can be mounted on aerial platforms including satellites, airplanes, or helicopters. They can also be mounted on vehicles...