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August 15, 2025Environmental Research Letters3 citationsOpen Access

Assessing Disasters in East Kalimantan: Machine Learning Approaches for Sustainable Urban Development

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SHSujung HeoDLDong Kun Lee

Key Points

  • High-probability zones for floods and landslides show significant risk in southern and central East Kalimantan, while forest fire and drought risks dominate the northern and western areas.
  • Risk maps produced from a Random Forest analysis reveal overlapping vulnerabilities in disaster-prone regions, guiding future urban planning.
  • Empirical threshold values and bootstrap-based uncertainty analysis enhance the reliability of multi-hazard assessments in this study.
  • The findings underpin the need for region-specific mitigation strategies, aiding disaster management and sustainable development efforts.

Abstract

Abstract East Kalimantan, the designated site for Indonesia’s new capital, faces rising disaster risks due to rapid urban expansion, deforestation, and ecological degradation. These changes increase the likelihood of multiple, co-occurring hazards—posing serious challenges to sustainable development and disaster management. In response, this study developed a multi-hazard probability assessment using a Random Forest (RF) algorithm, focusing on four major disasters: floods, landslides, forest fires, and droughts. By applying hazard-specific environmental variables, empirical threshold values, and bootstrap-based uncertainty analysis, the study produced spatially differentiated risk maps and identified areas with overlapping vulnerabilities. The results show that high-probability zones for floods and landslides are concentrated in the southern and central regions, while forest fire and drought risks are more prominent in the northern and western areas. Overlapping hazard zones, though relatively small in spatial extent, highlight critical regions where compound disaster risks may arise. These patterns suggest the need for region-specific mitigation strategies that reflect the dominant hazard characteristics in each area. Overall, the study provides baseline spatial information that can inform land-use planning and disaster management. The identification of environmental thresholds and uncertainty ranges supports more transparent and evidence-based decision-making.

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Cite This Study

Heo et al. (2025) studied this question.

synapsesocial.com/papers/68a365740a429f797332bb49https://doi.org/10.1088/1748-9326/adf97c
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