Landslide Risk Analysis with ArcGIS Desktop (AHP method)

Learn how to make Landslide Risk Analyse for any of the area in this world

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Landslide Risk Analysis with ArcGIS Desktop (AHP method)

What You Will Learn!

  • AHP Method
  • Risk Analysis with ArcGIS
  • Weighted Overlay Analysis
  • Calculating Risk Areas

Description

Hello,


The weights and effects of 10 different layers were calculated for the landslide risk analysis with the AHP multiple decision making method. The use of Geographic Information Systems (GIS) in risk analysis studies is increasing day by day.

Geographic Information Systems are used to collect, process and analyze existing data in order to identify potential risk areas. In this study, landslide susceptibility areas of the city of Pithoragarh were determined by GIS techniques.

In the modeling phase, the Weighted Overlay Analysis method was applied and digital maps such as elevation, slope, aspect, curvature shape, precipitation, NDVI Analysis, Land Use, Relative Relief, distance to stream, distance to highway maps were used.

All these maps were  superimposed  by processing the degrees of gravity, and as a result, the (risky) areas in the region that would be affected by the landslide were obtained.

You will learn from where and how the data to be used in the analysis is downloaded, what geographical processes it goes through and how it is prepared for analysis. Raster and vector data how to be prepared one by one, projection conversion operations, adding fields and the shortcuts that will speed up your process when converting from raster to vector and from vector to raster will be especially useful for you. Based on this study, it has been prepared as a resource for you to do a similar study about any part of the world. By sharing the data I used throughout the study with you, I allow you to practice.

Who Should Attend!

  • Surveying Engineers
  • Planners
  • Geological Engineers
  • Hydrology Engineers
  • Forestry
  • Land Managers
  • Students who related with GIS

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Subscribers

64

Lectures

34

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