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| # Automation with QGIS | ||
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| As you progress in your GIS career and hone your analysis skills, you will realise that spatial and data analysis can involve a multitude of complex steps. Additionally, you might need to perform an analysis several times for different areas, or because you need to adjust parameters to get the correct result, or because you need to update an outdated analysis. In these cases, you will want to __automate__ the analysis process. This can be achieved with the  `Graphical Modeler` in QGIS. Using models also ensures the __reproducibility__ of your analysis. | ||
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| ## Content | ||
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| | __Chapter__ | __Competences & Objectives__ | | ||
| | ----------- | ---------------------------- | | ||
| | [Chapter 1: Automation Theory](/content/Modul_7/en_qgis_automation_theory.md) | At the end of this chapter, you should know the value of reproducibility in data analysis, know how to use the model builder in QGIS | | ||
| | [Exercise 1: Automation](/content/Modul_7/en_qgis_modul_7_ex1.md) | | | ||
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| # Remote Sensing and Raster Data | ||
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| Working with raster data is inherently different from working with vector data. Instead of an attribute table associated with geometric features, raster data is a grid of squares, where each square holds a value. Spatial analyses frequently use raster data, as it is useful format to describe discrete phenomena, such as elevation, slope, temperature, etc. A common type of raster data all of us have come worked with or seen is satellite imagery. The benefit of satellite imagery is that you can perform analyses remotely. The first chapter in this module introduces raster data in depth and presents the basic workflow when using raster data in QGIS and humanitarian work. The second chapter introduces the concept of remote sensing and how it can be used to gain information from satellite imagery. | ||
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| __Chapter__ | __Competences & Objectives__ | | ||
| | ----------- | ---------------------------- | | ||
| | __[Chapter 1: Raster Theory](/content/Modul_8/en_qgis_raster_theory.md)__ | Understand how to work with raster data; know what to keep in mind when working with raster data; Know practical tools to work with raster data in QGIS. | | ||
| | __[Chapter 2: Remote Sensing](/content/Modul_8/en_qgis_remote_sensing_theory.md)__ | Know about remote sensing; Understand the basics about the interaction of electromagnetic radiation and the earths surface; Understand how different frequency bands can be combined to generate new information (e.g., NDVI). | | ||
| | __[Exercise 1: Basic Assessment of Flood Exposure in the Indus Basin in Pakistan](/content/Modul_8/en_qgis_modul_8_ex1.md)__ | | | ||
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| # Exercises Network Analysis | ||
| # Exercises Module 9: Network Analysis | ||
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| __🔙[Back to Homepage](/content/intro.md)__ | ||
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| <!-- | ||
| The exercises for module 9 comprise one full network analysis from start to finish. Each exercise deals with one step of the analysis process. | ||
| --> | ||
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| ## Visualisation | ||
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| | Exercise | Description | Estimated time | | ||
| | :-------------------- | :----------------- |:----------------- | | ||
| | __[Task 1: Assess water distribution access](/content/Modul_9/en_qgis_modul_9_ex1.md)__ | | | | ||
| | __[Task 2: Access healthcare - avoid areas](/content/Modul_9/en_qgis_modul_9_ex2.md)__ | | | | ||
| | __[Task 3: Larger scale accessibility analyses](/content/Modul_9/en_qgis_modul_9_ex3.md)__ | | | | ||
| | __[Task 4](/content/Modul_9/en_qgis_modul_9_ex4.md)__ | | | | ||
| | __[Task 5: Identifying critical road segments](/content/Modul_9/en_qgis_modul_9_ex5.md)__ | | | | ||
| | __[Task 6: West Germany / Ahrtal flood logistics](/content/Modul_9/en_qgis_modul_9_ex6.md)__ | | | | ||
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| Overview of exercises within this module |