Using GIS to assess landslide risk areas: comparing results of AHP-based methodology and Logistic Regression

Authors: Erica Goto*, UCSB
Topics: Hazards, Risks, and Disasters, Hazards and Vulnerability, Environment
Keywords: landslide, risk, vulnerability, landslide assessment, geographic information, logistic regression, AHP
Session Type: Paper
Day: 4/7/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Cleveland 1, Marriott, Mezzanine Level
Presentation File: No File Uploaded


Landslide risk areas are common in urban areas in Brazil, and they are a combination of both hazard and vulnerability. These at-risk areas, in many cases, are a consequence of accelerated and disorganized urbanization, which resulted in many informal settlements and precarious or no basic infrastructure. As a result, we often observe in these informal areas self-engineering dwellings with precarious techniques and material, wastewater and garbage onto the hill, pipes leaking and cut and fill. During the rainy season, intense rainfall can trigger landslides. Mapping these risk areas and their degree is a most, and this information can be used to support municipalities decisions related to disaster risk management, such as monitoring and prioritizing high risk dwellings removal. In this study, we compared two methodologies to assess landslide risk areas by evaluating the degree of risk based on meaningful parameters. The first methodology is based on Brazilian government methodology and Analytical Hierarchical Process (AHP), and we computed specific weights for parameters and sub-parameters and calibrated dataset with existing landslide risk mapping. The second methodology we use logistic regression model in the dataset with geographic information to find weights for parameters. These results are going to be validated, discussed and compared.

Abstract Information

This abstract is already part of a session. View the session here.

To access contact information login