Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788293334
Length 440 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Silas Toms Silas Toms
Author Profile Icon Silas Toms
Silas Toms
Paul Crickard Paul Crickard
Author Profile Icon Paul Crickard
Paul Crickard
Eric van Rees Eric van Rees
Author Profile Icon Eric van Rees
Eric van Rees
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Preface 1. Package Installation and Management FREE CHAPTER 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 17. Other Books You May Enjoy

Introduction to Geospatial Databases

In the previous chapters, you learned how to set up your Python environment and learned about the different libraries available for working with geospatial data using Python. In this chapter, you will start working with data.

Databases provide one of the most popular ways to store large amounts of data, and one of the most popular open source databases is PostgreSQL. PostGIS extends PostgreSQL, adding geographic objects and the ability to query records spatially. When PostgreSQL and PostGIS are combined, they create a powerful geospatial data repository.

Geospatial databases improve on basic relational database queries by allowing you to query your data by location or by location to other features in the database. You can also perform geospatial operations such as measurements of features, distances between features, and converting between...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image