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Learning geospatial analysis with Python

Author: Joel Lawhead
Publisher: Birmingham : Packt Publishing, 2013.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Genre/Form: Electronic books
Geospatial data
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Joel Lawhead
ISBN: 9781783281145 1783281146 9781783281138 1783281138
OCLC Number: 867907285
Language Note: English.
Notes: Includes index.
Description: 1 online resource (364 pages) : illustrations
Responsibility: Joel Lawhead.

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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 dont 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.

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