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Learning Geospatial Analysis with Python

Learning Geospatial Analysis with Python

By : Joel Lawhead
4.1 (8)
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Learning Geospatial Analysis with Python

Learning Geospatial Analysis with Python

4.1 (8)
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. It is an approach to use statistical analysis and other informational engineering to data which has a geographical or geospatial aspect. And this typically involves applications capable of geospatial display and processing to get a compiled and useful data. "Learning Geospatial Analysis with Python" uses the expressive and powerful Python programming language to guide you through geographic information systems, remote sensing, topography, and more. It explains how to use a framework in order to approach Geospatial analysis effectively, but on your own terms. "Learning Geospatial Analysis with Python" starts with a background of the field, a survey of the techniques and technology used, and then splits the field into its component speciality areas: GIS, remote sensing, elevation data, advanced modelling, and real-time data. This book will teach you everything there is to know, from using a particular software package or API to using generic algorithms that can be applied to Geospatial analysis. 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. "Learning Geospatial Analysis with Python" will round out your technical library with handy recipes and a good understanding of a field that supplements many a modern day human endeavors.
Table of Contents (12 chapters)
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11
Index

Chapter 4. Geospatial Python Toolbox

The first three chapters of this book covered the history of geospatial analysis, the types of geospatial data used by analysts, and the major software and libraries found within the geospatial industry. We used some simple Python examples here and there to illustrate certain points but we focused mainly on the field of geospatial analysis independent of any specific technology.

Starting here, we will be using Python to conquer geospatial analysis and we will continue with that approach for the rest of the book. In this chapter, we'll discover the Python libraries used to access the different types of data found in the Vector data and Raster data sections of Chapter 2, Geospatial Data. Some of these libraries are pure Python and some are bindings to the different software packages found in Chapter 3, The Geospatial Technology Landscape.

We will examine pure Python solutions whenever possible. Python is a very capable programming language...

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