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        <datestamp>2026-09-12T12:23:34Z</datestamp>
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          <dc:title>Data and code for the manuscript entitled: Similarities and Differences in Triggering Conditions of Typhoon Rainstorm-Induced Clustered Shallow Landslides in Semi-humid Northern and Humid Southern China</dc:title>
          <dc:creator>Gang Mei (684440)</dc:creator>
          <dc:subject>Computational modelling and simulation in earth sciences</dc:subject>
          <dc:subject>Shallow landslides</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;&lt;b&gt;This repository contains the data, analysis code, and Supporting Information associated with the study “Similarities and Differences in Triggering Conditions of Typhoon-Rainstorm-Induced Clustered Shallow Landslides in Semi-humid Northern and Humid Southern China.”&lt;/b&gt;&lt;/p&gt;&lt;p dir="ltr"&gt;&lt;b&gt;The study compares clustered shallow landslides in two contrasting climatic and geomorphological regions of China: the semi-humid Northeastern Taihang Mountains and the humid Zixing Hills. The repository includes the datasets used in the analyses, landslide-related and conditioning-factor data, analysis scripts/code, and the Supporting Information accompanying the manuscript.&lt;/b&gt;&lt;/p&gt;&lt;p dir="ltr"&gt;&lt;b&gt;The Supporting Information includes supplementary figures and tables describing the conditioning-factor datasets and model settings. The deposited data and code support the spatial point pattern analysis and explainable machine-learning analyses reported in the article, including kernel density estimation, Ripley’s K-function analysis, XGBoost modelling, and SHAP-based interpretation.&lt;/b&gt;&lt;/p&gt;&lt;p dir="ltr"&gt;&lt;b&gt;These materials are provided to support transparency, reproducibility, and reuse of the analyses presented in the associated article.&lt;/b&gt;&lt;/p&gt;</dc:description>
          <dc:date>2026-09-12T12:23:34Z</dc:date>
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