TY - DATA T1 - Supplemental Material underlying the publication: Optimizing multi-resolution topographic indicator combinations for debris flow susceptibility assessment based on factorial experiments and UMAP analysis PY - 2025/10/31 AU - Si Alu AU - Quan Lai AU - Enliang Guo AU - Yongfang Wang AU - Jiquan Zhang UR - DO - 10.4121/67fc83eb-5128-490d-a265-6b45943159a1.v1 KW - debris flow susceptibility KW - optimal pixel resolution combination KW - factorial experiment KW - UMAP KW - Machine learning N2 -

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.

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