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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
Authors (3):
Silas Toms Silas Toms
Profile icon Silas Toms
Paul Crickard Paul Crickard
Profile icon Paul Crickard
Eric van Rees Eric van Rees
Profile icon 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 1. Other Books You May Enjoy Index

Chapter 6. Raster Data Processing

Geographic information systems (GIS) are often comprised of points, lines, and polygons. These data types are called vector data. There is, however, another data type in GIS—rasters. In this chapter, you will learn the basics of working with raster data. You will learn how to:

  • Use the Geospatial Data Abstraction Library (GDAL) to load and query rasters
  • Use GDAL to modify and save rasters
  • Use GDAL to create rasters
  • Load rasters into PostgreSQL
  • Perform queries on rasters using PostgreSQL

Note

Installing GDAL can be difficult. By using virtual environments and running Anaconda, you can simplify this process by using the GUI of the environment.

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