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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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Toc

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

Summary


This chapter introduced the brand new ArcGIS API for Python, which is built on Python 3.5. You learned how to make use of the API, Jupyter Notebooks, and data processing with data stored in the cloud-based ArcGIS Online system. We covered how the API is organized into different modules, how to install the API, how to use the map widget, how to log in to ArcGIS Online using different user accounts, and working with vector and raster data. Using some of the API modules, we learned how to use the API for Python to perform basic geospatial analysis and to create ArcGIS Online web maps.

The next chapter will introduce Python tools for interacting with cloud-based data for search and fast data processing. In particular, it focuses on the use of Elasticsearch and MapD GPU databases, both of which are based on the AWS cloud infrastructure. The reader will learn to create cloud services for geospatial search, geolocated data processing, geolocated data, and learn how to use Python libraries...

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