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Mastering Geospatial Analysis with Python

You're reading from Mastering Geospatial Analysis with Python

Product type Book

Published in Apr 2018

Publisher Packt

ISBN-13 9781788293334

Pages 440 pages

Edition 1st Edition

Languages

Concepts

Geospatial Analysis

Authors (3):

Silas Toms

Paul Crickard

Eric van Rees

View More author details

Table of Contents (23) Chapters

Title Page

Copyright and Credits

Packt Upsell

Contributors

Preface

1. Package Installation and Management

2. Introduction to Geospatial Code Libraries

3. Introduction to Geospatial Databases

4. Data Types, Storage, and Conversion

5. Vector Data Analysis

6. Raster Data Processing

7. Geoprocessing with Geodatabases

8. Automating QGIS Analysis

9. ArcGIS API for Python and ArcGIS Online

10. Geoprocessing with a GPU Database

11. Flask and GeoAlchemy2

12. GeoDjango

13. Geospatial REST API

14. Cloud Geodatabase Analysis and Visualization

15. Automating Cloud Cartography

16. Python Geoprocessing with Hadoop

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Index

Cloud geodatabase solutions

Cloud storage of geospatial data has become a common part of many GIS architectures. Whether it is used as a backup to an on-premises solution, replaces an on-premises solution, or is combined with a local solution to provide internet support for an intranet-based system, the cloud is a big part of the future of GIS.

With ArcGIS Online, CARTO, MapBox, and now MapD, the options for a cloud data store that support geospatial data are more numerous than ever. Each offers a visualization component and a different type of data storage and each will integrate with your data and software in different ways.

ArcGIS Online, while also offering stand-alone options (that is, direct data upload), integrates with ArcGIS Enterprise (formerly ArcGIS Server) to consume enterprise REpresentational State Transfer (REST) web services that are stored on a local geodatabase. ArcGIS Online is built on top of Amazon Web Services (AWS) and all of the server architecture is hidden from...

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Authors (3)

Silas Toms

Silas Toms is a long-time geospatial professional and author who has previously published ArcPy and ArcGIS and Mastering Geospatial Analysis with Python. His career highlights include developing the real-time common operational picture used at Super Bowl 50, building geospatial software for autonomous cars, designing computer vision for next-gen insurance, and developing mapping systems for Zillow. He now works at Volta Charging, predicting the future of electric vehicle adoption and electric charging infrastructure.

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Paul Crickard

Paul Crickard authored a book on the Leaflet JavaScript module. He has been programming for over 15 years and has focused on GIS and geospatial programming for 7 years. He spent 3 years working as a planner at an architecture firm, where he combined GIS with Building Information Modeling (BIM) and CAD. Currently, he is the CIO at the 2nd Judicial District Attorney's Office in New Mexico.

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Eric van Rees

Eric van Rees was first introduced to Geographical Information Systems (GIS) when studying Human Geography in the Netherlands. For 9 years, he was the editor-in-chief of GeoInformatics, an international GIS, surveying, and mapping publication and a contributing editor of GIS Magazine. During that tenure, he visited many geospatial user conferences, trade fairs, and industry meetings. He focuses on producing technical content, such as software tutorials, tech blogs, and innovative new use cases in the mapping industry.

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