Assessing the Available Landslide Susceptibility Map and Inventory for the Municipality of Rio de Janeiro, Brazil

Potentials and Challenges for Data-Driven Applications

Datos Bibliográficos

ID7207265
AutoresPedro Lima (0000-0003-2429-3752, General Electric (Austria)), Luiz Carlos Teixeira Coelho Filho (0000-0002-4466-9772, Centro Universitário da Cidade, autor de correspondencia), Guilherme Damasceno Raposo (0009-0005-0145-4594, Universidade do Estado do Rio de Janeiro), Irving Da Silva Badolato (0000-0002-4058-4392, Universidade do Estado do Rio de Janeiro), Raquel Fonseca (0000-0002-6454-6622), Raquel Batista Medeiros da Fonseca (0000-0002-0095-3827, Institute of Religious Studies), Sonia Maria Lima Silva (0000-0002-2414-1516, Universidade do Estado do Rio de Janeiro), Jonatas Goulart Marinho Falcão (0009-0007-8515-7179, Universidade Federal do Rio de Janeiro)
Año2025
Volumen14
Número9
Páginas330-330
Fecha de publicación2025-08-26
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaISPRS International Journal of Geo-Information (JOURNAL)
Identificadores de la revistaISSN: 2220-9964 • E-ISSN: 2220-9964
EditorialMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijgi14090330
OpenAlexW4413641257
IdiomaEN
Citas recibidas1
Referencias citadas55

This study presents an initial evaluation of the heuristic landslide susceptibility map for the Municipality of Rio de Janeiro by comparing it with the official landslide inventory. The objective is to provide a first analysis of the accuracy of the current map (Reference Map), which was developed using heuristic methods, in contrast with a basic predictive model based on Generalized Additive Models (GAMs). The study includes a critical review of the existing inventory and examines landslide records from 2010 to 2016, using georeferenced data provided by the GeoRio Foundation. Data from 2017 and 2018 are used for a preliminary test of the model. Rather than proposing a replacement, this study suggests that even simple data-driven models can offer useful insights into potential improvements in the reference susceptibility map. The results are exploratory and intended to inform future, more detailed analyses. While limited in scope, this work illustrates how quantitative approaches may complement existing methods in landslide prediction assessment

Archaeology · Cartography · Environmental planning · Environmental resource management · Geography · Geomorphology · Landslide · Environmental Science · Flood Risk Assessment and Management · Geotechnical Engineering and Analysis · Landslides and related hazards · Geology

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