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Mastering Geospatial Analysis with Python

You're reading from   Mastering Geospatial Analysis with Python Explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788293334
Length 440 pages
Edition 1st Edition
Languages
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Authors (3):
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Silas Toms Silas Toms
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Silas Toms
Paul Crickard Paul Crickard
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Paul Crickard
Eric van Rees Eric van Rees
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Eric van Rees
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Table of Contents (18) Chapters Close

Preface 1. Package Installation and Management 2. Introduction to Geospatial Code Libraries FREE CHAPTER 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 17. Other Books You May Enjoy

Esri GIS tools for Hadoop

With your environment set up and some basic knowledge of Ambari, HDFS, and Hive, you will now learn how to add a spatial component to your queries. To do so, we will use the Esri GIS tools for Hadoop.

The first step is to download the files located at the GitHub repository, which is located at: https://github.com/Esri/gis-tools-for-hadoop. You will be using Ambari to move the files to HDFS not the container, so download these files to your local machine.

Esri has a tutorial for downloading the files by using ssh to connect to the container and then using git to clone the repository. You can follow these instructions here: https://github.com/Esri/gis-tools-for-hadoop/wiki/GIS-Tools-for-Hadoop-for-Beginners.

You can download the files by using the GitHub Clone or download button on the right-hand side of the repository. To unzip the archive, use...

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