Hydro-Meteorological Landslide Inventory for Sustainable Urban Management in a Coastal Region of Brazil
Metadatos
Mostrar el registro completo del ítemAutor
Pereira Hader, Paulo Rodolpho; Lopes Gonçalves Horta, Isabela Taici; Arroyo da Silva do Valle, Victor; Irigaray Fernández, ClementeEditorial
MDPI
Materia
Landslide catalogue Rainfall Soil moisture
Fecha
2025-08-19Referencia bibliográfica
Hader, P.R.P.; Horta, I.T.L.G.; da Silva do Valle, V.A.; Irigaray, C. Hydro-Meteorological Landslide Inventory for Sustainable Urban Management in a Coastal Region of Brazil. Sustainability 2025, 17, 7487. https://doi.org/10.3390/su17167487
Resumen
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.





