Supplemental Material underlying the publication: Optimizing multi-resolution topographic indicator combinations for debris flow susceptibility assessment based on factorial experiments and UMAP analysis

DOI:10.4121/67fc83eb-5128-490d-a265-6b45943159a1.v1
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DOI: 10.4121/67fc83eb-5128-490d-a265-6b45943159a1

Datacite citation style

Alu, Si; Lai, Quan; Guo, Enliang; Wang, Yongfang; Zhang, Jiquan (2025): Supplemental Material underlying the publication: Optimizing multi-resolution topographic indicator combinations for debris flow susceptibility assessment based on factorial experiments and UMAP analysis. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/67fc83eb-5128-490d-a265-6b45943159a1.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This supplemental material supports the study "Optimizing multi-resolution topographic indicator combinations for debris flow susceptibility assessment based on factorial experiments and UMAP analysis". It leveraging a factorial experimental design and UMAP analysis to systematically evaluated nearly 350,000 prediction results from RF, GBDT, and BPNN models. Then a multi-faceted assessment across seven dimensions revealed the impact of resolution combinations on susceptibility and identified each model's optimal combination. The supplemental material 1 and 2 includes seven evaluation indices data of the debris flow susceptibility prediction results for all treatment combinations, and the supplemental material 3 and 4 includes Probability 1 (AUC ranked in the top 1000) and Probability 2（remaining six indices all ranked in the top 15%) data of each treatment combinations.

History

  • 2025-10-31 first online, published, posted

Publisher

4TU.ResearchData

Format

excel/.xlsx

Funding

  • Natural Science Foundation of Inner Mongolia Autonomous Region (grant code Grant No. 2024QN04005)
  • Research Program of Science and Technology at Universities of Inner Mongolia Autonomous Region (grant code Grant No. NJZZ23018)
  • Fundamental Research Funds for Inner Mongolia Normal University (grant code Grant No. 2023JBQN043)
  • Scientific Research Foundation for Advanced Talents of Inner Mongolia Normal University (grant code Grant No. 2021YJRC009)

Organizations

Inner Mongolia Normal University, College of Tourism

DATA

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