Scholarlink

<p>Landslides are among the most recurrent and damaging natural hazards in Costa Rica’s mountainous and tectonically active regions. This study focuses on the municipality of Atenas, where complex interactions between environmental and anthropogenic factors exacerbate susceptibility to mass movement processes. By integrating principles of environmental geomorphology with socio-spatial analysis, this research develops a comprehensive landslide risk zoning model. The methodology is based on an extensive literature review, drone-based imagery, field surveys, and geospatial analysis using GIS tools. A series of thematic maps were generated, including geology, slope, soil types, geomorphology, susceptibility, exposure, vulnerability, and final risk. The analytical framework combines morphometric parameters—such as slope gradient, terrain roughness, LS factor, and drainage and contour densities—with morphogenetic criteria, including erosional landforms, lithological formations, and soil weathering characteristics. The risk model was constructed in four stages: (1) methodological input layers, (2) hazard assessment, (3) exposure and vulnerability estimation using population data and the Social Development Index, and (4) final risk mapping. Results reveal that while high-risk zones correspond to steep volcanic hillslopes and unstable lithologies, some medium- and low-risk areas have also experienced landslide events triggered by intensive rainfall events such as tropical cyclones, underscoring the need for caution in all urban and rural planning efforts. The study emphasizes that risk is not only a product of natural susceptibility but also of land use, infrastructure placement, and social resilience. Recommendations highlight the importance of integrating hazard information into municipal land-use planning, coupled with community-based early warning systems and targeted mitigation strategies for effective risk reduction.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Integrating geomorphological and socio-spatial factors for landslide risk zonation in Atenas, Costa Rica

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月23日

查看全文
  • Andreina Mondragón-Rodríguez,
  • Adolfo Quesada-Román

摘要

Landslides are among the most recurrent and damaging natural hazards in Costa Rica’s mountainous and tectonically active regions. This study focuses on the municipality of Atenas, where complex interactions between environmental and anthropogenic factors exacerbate susceptibility to mass movement processes. By integrating principles of environmental geomorphology with socio-spatial analysis, this research develops a comprehensive landslide risk zoning model. The methodology is based on an extensive literature review, drone-based imagery, field surveys, and geospatial analysis using GIS tools. A series of thematic maps were generated, including geology, slope, soil types, geomorphology, susceptibility, exposure, vulnerability, and final risk. The analytical framework combines morphometric parameters—such as slope gradient, terrain roughness, LS factor, and drainage and contour densities—with morphogenetic criteria, including erosional landforms, lithological formations, and soil weathering characteristics. The risk model was constructed in four stages: (1) methodological input layers, (2) hazard assessment, (3) exposure and vulnerability estimation using population data and the Social Development Index, and (4) final risk mapping. Results reveal that while high-risk zones correspond to steep volcanic hillslopes and unstable lithologies, some medium- and low-risk areas have also experienced landslide events triggered by intensive rainfall events such as tropical cyclones, underscoring the need for caution in all urban and rural planning efforts. The study emphasizes that risk is not only a product of natural susceptibility but also of land use, infrastructure placement, and social resilience. Recommendations highlight the importance of integrating hazard information into municipal land-use planning, coupled with community-based early warning systems and targeted mitigation strategies for effective risk reduction.