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Part I - Python essentials

Overview and learning goals
1. Getting started
2. Basic programming concepts
3. Introduction to data analysis
4. Introduction to data visualization

Part II - Introduction to GIS with Python

Overview and learning goals
5. Getting started
6. Vector data processing
7. Raster data processing
8. Geographic data visualization
9. Using online geographic data sources

Part III - Case studies

10. Spatial interpolation
11. Spatial network analysis
12. Terrain analysis
13. Conclusions

Appendices

A. Working effectively in Python
B. Spatial index efficiency
- Spatial index - How to boost spatial queries?
C. Solutions to questions and exercises
- Question solutions
- Exercise solutions

Back matter

Acknowledgements
Glossary
References
About the authors

Datasets

Overview
NOAA Weather data

.rst

9. Using online geographic data sources

9. Using online geographic data sources#

Sections:

Learning objectives
9.1 Retrieving OpenStreetMap data
9.2 Retrieving data from Web Feature Service (WFS)
9.3 Retrieving data from Web Coverage Service (WCS)
9.4 Reading data from spatial databases
Exercises

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Exercises

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Learning objectives

By Henrikki Tenkanen, Vuokko Heikinheimo, David Whipp

© Copyright 2020-2023, Henrikki Tenkanen, Vuokko Heikinheimo, David Whipp.