ANÁLISIS BIBLIOMÉTRICO DEL USO DE HERRAMIENTAS SIG EN ESCENARIOS DE DESLIZAMIENTOS EN BRASIL

This research consists of a systematic review of articles that used Geographic Information Systems (GIS) as a way to map landslide-prone areas in Brazil or that experienced this situation. Data available for analysis in the Web Of Science and Scopus search collections were used, and the VOSViewer software was used. A methodology based on exclusion filters was applied, which allowed us to perceive a multidisciplinary approach to the theme and a concentration of published works in areas close to Serra do Mar. The results indicate a remarkable growth in this topic, with more than 60% of the papers published in the last 5 years and which were driven by the growth of research involving landslide predictions through Artificial Intelligence (AI) tools.

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Publication Details

Journal
Revista Geográfica de América Central
Published
2025-01-28
DOI
https://doi.org/10.15359/rgac.74-1.16
Primary Topic
Tailings Management and Properties
Type
article
Field-Weighted Citation Impact
0.00
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article

ANÁLISIS BIBLIOMÉTRICO DEL USO DE HERRAMIENTAS SIG EN ESCENARIOS DE DESLIZAMIENTOS EN BRASIL

Luis De Oro Arenas, Roberto Wágner Lourenço, Darllan Collins da Cunha e Silva, Arthur Pereira dos Santos
Revista Geográfica de América Central
Tailings Management and Properties
article

ANÁLISIS BIBLIOMÉTRICO DEL USO DE HERRAMIENTAS SIG EN ESCENARIOS DE DESLIZAMIENTOS EN BRASIL

Luis De Oro Arenas, Roberto Wágner Lourenço, Darllan Collins da Cunha e Silva, Arthur Pereira dos Santos
article en

Abstract

This research consists of a systematic review of articles that used Geographic Information Systems (GIS) as a way to map landslide-prone areas in Brazil or that experienced this situation. Data available for analysis in the Web Of Science and Scopus search collections were used, and the VOSViewer software was used. A methodology based on exclusion filters was applied, which allowed us to perceive a multidisciplinary approach to the theme and a concentration of published works in areas close to Serra do Mar. The results indicate a remarkable growth in this topic, with more than 60% of the papers published in the last 5 years and which were driven by the growth of research involving landslide predictions through Artificial Intelligence (AI) tools.

Revista Geográfica de América CentralVol. 1(74)
Universidade Estadual Paulista (Unesp) (BR)
Openalex Percentile: Top 96%
Tailings Management and Properties
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