Hydro-Meteorological Landslide Inventory for Sustainable Urban Management in a Coastal Region of Brazil

Comprehensive, standardised, multi-temporal inventories of rainfall-induced landslides linked to soil moisture remain scarce, especially in tropical regions. Addressing this gap, we present a multi-source urban inventory for Brazil’s Baixada Santista region (1988–2024). A key advance is the introduction of geographical and temporal confidence classifications, which indicates precisely how each landslide’s location and occurrence date are known, thereby addressing a previously overlooked criterion in Brazil’s landslide data treatment. The inventory comprises 2534 records categorised by spatial (G1–G3) and temporal (T1–T3) confidence. Notable findings include the following: (i) confidence classifications enhance inventory reliability for research and early warning, though precise temporal data remains challenging; (ii) multi-source integration with UAV validation is key to robust inventories in urban tropical regions; (iii) soil moisture complements rainfall-based warnings, but requires local calibration for satellite-derived estimates; (iv) data gaps and biases underscore the need for standardised landslide documentation; and (v) the framework is transferable, providing a scalable model for Brazil and worldwide. Despite limitations, the inventory provides a foundation for (i) susceptibility and hazard modelling; (ii) empirical thresholds for early warning; and (iii) climate-related trend analyses. Overall, the framework offers a sustainable, practical, transferable method for worldwide and contributes to strengthening disaster information systems and early warning capacities.

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Publication Details

Journal
Sustainability
Published
2025-08-19
DOI
https://doi.org/10.3390/su17167487
Primary Topic
Landslides and related hazards
Type
article
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article

Hydro-Meteorological Landslide Inventory for Sustainable Urban Management in a Coastal Region of Brazil

Isabela Taici Lopes Gonçalves Horta, Paulo Rodolpho Pereira Hader, Clemente Irigaray, Victor Arroyo da Silva do Valle
Sustainability
Landslides and related hazards
article

Hydro-Meteorological Landslide Inventory for Sustainable Urban Management in a Coastal Region of Brazil

Isabela Taici Lopes Gonçalves Horta, Paulo Rodolpho Pereira Hader, Clemente Irigaray, Victor Arroyo da Silva do Valle
article en

Abstract

Comprehensive, standardised, multi-temporal inventories of rainfall-induced landslides linked to soil moisture remain scarce, especially in tropical regions. Addressing this gap, we present a multi-source urban inventory for Brazil’s Baixada Santista region (1988–2024). A key advance is the introduction of geographical and temporal confidence classifications, which indicates precisely how each landslide’s location and occurrence date are known, thereby addressing a previously overlooked criterion in Brazil’s landslide data treatment. The inventory comprises 2534 records categorised by spatial (G1–G3) and temporal (T1–T3) confidence. Notable findings include the following: (i) confidence classifications enhance inventory reliability for research and early warning, though precise temporal data remains challenging; (ii) multi-source integration with UAV validation is key to robust inventories in urban tropical regions; (iii) soil moisture complements rainfall-based warnings, but requires local calibration for satellite-derived estimates; (iv) data gaps and biases underscore the need for standardised landslide documentation; and (v) the framework is transferable, providing a scalable model for Brazil and worldwide. Despite limitations, the inventory provides a foundation for (i) susceptibility and hazard modelling; (ii) empirical thresholds for early warning; and (iii) climate-related trend analyses. Overall, the framework offers a sustainable, practical, transferable method for worldwide and contributes to strengthening disaster information systems and early warning capacities.

SustainabilityVol. 17(16)
Universidad de Granada (ES), Universidade de São Paulo (BR), Universidade Católica de Santos (BR), Universidade Metropolitana de Santos (BR)
Openalex Percentile: Top 71%
Landslides and related hazards
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