Monitoring Geological Risk Areas in the City of São Paulo Based on Multi-Temporal High-Resolution 3D Models

Monitoring Geological Risk Areas in the City of São Paulo Based on Multi-Temporal High-Resolution 3D Models

This paper presents a multi-temporal comparison of high-resolution 3D digital models from two urban areas susceptible to landslides in three time periods. The study areas belong to the São Paulo landslide risk mapping database and are named “CEU Paz” (CP) and “Parque Santa Madalena I” (PSM). For eac...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2023-06, Vol.15 (12), p.3028
Main Authors: de Sousa, Amanda Mendes, Viana, Camila Duelis, Garcia, Guilherme Pereira Bento, Grohmann, Carlos Henrique
Format: Article
Language:eng
Subjects:
Brazil
Climate change
Comparative analysis
Developing countries
Digital imaging
Disasters
Emergency preparedness
Environmental risk
Fieldwork
geological risk
Geology
High resolution
landslide
Landslides
Landslides & mudslides
LDCs
Lidar
Mapping
Monitoring
Optical radar
Photogrammetry
Prevention
Remote sensing
Risk
risk monitoring
RPA
slums
structure-from-motion multi-view stereo
Sustainable development
Three dimensional models
Urban areas
Vegetation cover
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Summary:This paper presents a multi-temporal comparison of high-resolution 3D digital models from two urban areas susceptible to landslides in three time periods. The study areas belong to the São Paulo landslide risk mapping database and are named “CEU Paz” (CP) and “Parque Santa Madalena I” (PSM). For each area, a lidar digital surface model (DSM) (2017) and two structure-from-motion multi-view stereo DSMs (2019 and 2022) built from drone imagery were combined using raster algebra to generate three digital surface models of differences (DoDs). The DoDs were able to highlight changes in vegetation cover and buildings, which are important characteristics for evaluating geological risks in an urban context. Still, they were unable to highlight changes in the ground surface. The results demonstrate that the method greatly supports monitoring, allowing for greater detail and ease of detecting large-scale changes. Even with promising results, this technique should be understood as one more tool for mapping risk areas without replacing fieldwork.
ISSN:2072-4292
2072-4292