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<p>The Kulon Progo Mountains, located in southern Java, Indonesia, exhibit complex geological characteristics that contribute to a high susceptibility to landslides, posing significant risks to infrastructure and human safety. This study delineates landslide susceptibility zones to mitigate these hazards using grid and slope units. The widely recognized weight of evidence (WoE) and frequency ratio (FR) methods were applied to assess and compare model performance. Nine factors controlling landslides were analyzed: slope, aspect, elevation, slope material, lineament density, normalized difference vegetation index (NDVI), distance to rivers, roads, and rainfall. Results indicate that slopes steeper than 40° and a high lineament density greater than 1.61&#xa0;km/km² influence landslide susceptibility. Model validation, using the area under the curve (AUC), reveals that the slope unit-based WoE method achieves higher accuracy, with AUC values of 0.812 (success rate) and 0.827 (prediction rate). The study produced four landslide susceptibility zonation maps, classifying areas from very low to high susceptibility, with the most susceptible zones concentrated in the northern part of the study area.</p>

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Statistical landslide susceptibility zonation: kulon progo mountains, Indonesia

  • 期刊论文

  • 发表日期：

    2025年10月17日

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  • Egy Erzagian,
  • Teuku Faisal Fathani,
  • Wahyu Wilopo

摘要

The Kulon Progo Mountains, located in southern Java, Indonesia, exhibit complex geological characteristics that contribute to a high susceptibility to landslides, posing significant risks to infrastructure and human safety. This study delineates landslide susceptibility zones to mitigate these hazards using grid and slope units. The widely recognized weight of evidence (WoE) and frequency ratio (FR) methods were applied to assess and compare model performance. Nine factors controlling landslides were analyzed: slope, aspect, elevation, slope material, lineament density, normalized difference vegetation index (NDVI), distance to rivers, roads, and rainfall. Results indicate that slopes steeper than 40° and a high lineament density greater than 1.61 km/km² influence landslide susceptibility. Model validation, using the area under the curve (AUC), reveals that the slope unit-based WoE method achieves higher accuracy, with AUC values of 0.812 (success rate) and 0.827 (prediction rate). The study produced four landslide susceptibility zonation maps, classifying areas from very low to high susceptibility, with the most susceptible zones concentrated in the northern part of the study area.