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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
Author Profile Icon Eric van Rees
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

Summary

In this chapter, we learned how to use the Flask MVC web framework and some of the available component modules that add extra functionality. These modules include the SQLAlchemy ORM, the GeoAlchemy2 ORM for geospatial queries, WTForms for processing of web data, and the Jinja2 templating system for creating web page templates. We created database tables, added data tables and tables relationships, and created a web application that utilized geospatial and relationship queries to generate dynamic web pages.

A fun challenge, building on the code reviewed here, would be to explore adding editing capabilities to the Arena application, allowing the user to move the arenas into their correct location if the data is out of date. Explore the GeoAlchemy2 ORM documentation for more advanced capabilities.

In the next chapter, we will review a similar MVC web framework, Django, and...

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