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Learning Geospatial Analysis with Python - Third Edition

You're reading from  Learning Geospatial Analysis with Python - Third Edition

Product type Book
Published in Sep 2019
Publisher Packt
ISBN-13 9781789959277
Pages 456 pages
Edition 3rd Edition
Languages
Author (1):
Joel Lawhead Joel Lawhead
Profile icon Joel Lawhead
Toc

Table of Contents (15) Chapters close

Preface 1. Section 1: The History and the Present of the Industry
2. Learning about Geospatial Analysis with Python 3. Learning Geospatial Data 4. The Geospatial Technology Landscape 5. Section 2: Geospatial Analysis Concepts
6. Geospatial Python Toolbox 7. Python and Geographic Information Systems 8. Python and Remote Sensing 9. Python and Elevation Data 10. Section 3: Practical Geospatial Processing Techniques
11. Advanced Geospatial Python Modeling 12. Real-Time Data 13. Putting It All Together 14. Other Books You May Enjoy

Routing along streets

Routing along streets uses a connected network of lines, which is called a graph. The lines in the graph can have impedance values, which discourage a routing algorithm from including them in a route. Examples of impedance values often include traffic volume, speed limit, or even distance. A key requirement for a routing graph is that all of the lines, known as edges, must be connected. Road datasets that are created for mapping will often have lines whose nodes do not intersect.

In this example, we'll calculate the shortest route through a graph by distance. We'll use a start and end point, which are not nodes in the graph, meaning we'll have to first find the graph nodes that are the closest to our start and destination points.

To calculate the shortest route, we'll use a powerful pure Python graph library called NetworkX. NetworkX is...

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