%0 Generic
%A Alu, Si
%A Lai, Quan
%A Guo, Enliang
%A Wang, Yongfang
%A Zhang, Jiquan
%D 2025
%T Data underlying the publication: Optimizing multi-resolution topographic indicator combinations for debris flow susceptibility assessment based on factorial experiments and UMAP analysis
%U 
%R 10.4121/6a777ec0-92a7-4818-ab89-b1234c5c1f80.v1
%K debris flow susceptibility
%K optimal pixel resolution combination
%K factorial experiment
%K UMAP
%K Machine learning
%X <p>This dataset 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 dataset contains the basic training and testing sets used in this study to assess debris flow susceptibility.</p>
%I 4TU.ResearchData