Scale-Dependent Controls on Landslide Susceptibility in Angra dos Reis (Brazil) Revealed by Spatial Regression and Autocorrelation Analyses

Landslides are a persistent and destructive hazard in Angra dos Reis, located in the highlands of Rio de Janeiro State, southeastern Brazil, where steep slopes, intense orographic rainfall, and unregulated urban expansion converge to trigger recurrent mass movements. In this study, we applied Multiscale Geographically Weighted Regression (MGWR) to examine the spatially varying relationships between landslide occurrence and topographic, hydrological, geological, and anthropogenic factors. A detailed inventory of 319 landslides was compiled using high-resolution PlanetScope imagery after the December 2023 rainfall event. Following multicollinearity testing and variable selection, thirteen predictors were retained, including slope, rainfall, lithology, NDVI, forest loss, and distance to roads. The MGWR achieved strong performance (R2 = 0.94; AICc = 134.99; AUC = 0.99) and demonstrated that each factor operates at a distinct spatial scale. Slope, rainfall, and lithology exerted broad-scale controls, while road proximity had a consistent global effect. In contrast, forest loss and land use showed localized significance. These findings indicate that landslide susceptibility in Angra dos Reis is primarily driven by the interaction of orographic rainfall, steep terrain, and geological substrate, intensified by human disturbances such as road infrastructure and vegetation removal. The study underscores the need for targeted adaptation strategies, including slope stabilization, restrictions on road expansion, and vegetation conservation in steep, rainfall-prone sectors.

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Publication Details

Journal
Geomatics
Published
2025-09-26
DOI
https://doi.org/10.3390/geomatics5040049
Citations
2
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
4.84

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article

Scale-Dependent Controls on Landslide Susceptibility in Angra dos Reis (Brazil) Revealed by Spatial Regression and Autocorrelation Analyses

Enner Alcântara, José Pedro Ferreira, Marcos Roberto de Mattos Fontes, Alexandre Gori Maia et al.
2 citations
Geomatics
Landslides and related hazards
4.84
article

Scale-Dependent Controls on Landslide Susceptibility in Angra dos Reis (Brazil) Revealed by Spatial Regression and Autocorrelation Analyses

Enner Alcântara, José Pedro Ferreira, Marcos Roberto de Mattos Fontes, Alexandre Gori Maia, Tulius Dias Nery, José Roberto Mantovani, José Antonio Marengo, Cheila Flávia de Praga Baião, Yasmim Carvalho Guimarães, André Luiz dos Santos Monte Ayres, Cristhy Satie Kanai, Nathalia Moraes Desani
article en
2 citations

Abstract

Landslides are a persistent and destructive hazard in Angra dos Reis, located in the highlands of Rio de Janeiro State, southeastern Brazil, where steep slopes, intense orographic rainfall, and unregulated urban expansion converge to trigger recurrent mass movements. In this study, we applied Multiscale Geographically Weighted Regression (MGWR) to examine the spatially varying relationships between landslide occurrence and topographic, hydrological, geological, and anthropogenic factors. A detailed inventory of 319 landslides was compiled using high-resolution PlanetScope imagery after the December 2023 rainfall event. Following multicollinearity testing and variable selection, thirteen predictors were retained, including slope, rainfall, lithology, NDVI, forest loss, and distance to roads. The MGWR achieved strong performance (R2 = 0.94; AICc = 134.99; AUC = 0.99) and demonstrated that each factor operates at a distinct spatial scale. Slope, rainfall, and lithology exerted broad-scale controls, while road proximity had a consistent global effect. In contrast, forest loss and land use showed localized significance. These findings indicate that landslide susceptibility in Angra dos Reis is primarily driven by the interaction of orographic rainfall, steep terrain, and geological substrate, intensified by human disturbances such as road infrastructure and vegetation removal. The study underscores the need for targeted adaptation strategies, including slope stabilization, restrictions on road expansion, and vegetation conservation in steep, rainfall-prone sectors.

GeomaticsVol. 5(4)
Centro Nacional de Monitoramento e Alertas de Desastres Naturais (BR), Department of Aerospace Science and Technology (BR), Korea University of International Studies (KR), Universidade Estadual Paulista (Unesp) (BR)
Universidade Estadual Paulista
Openalex Percentile: Top 5%
Landslides and related hazards
4.84
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