Scholarlink

<p>Traditional two-dimensional Projected Area (PA) calculations systematically underestimate area of mountain ecosystems, introducing significant uncertainty into resource management and sustainable development assessments. To address this critical data gap, we present the True Surface Area of China’s Mountains (TSA-MC v1.0), the first nationwide, 30-m resolution dataset providing a physically realistic three-dimensional land surface measure. Developed from ASTER GDEM V2 using a robust pixel decomposition algorithm, its reliability was confirmed through rigorous validation of its physical accuracy (e.g., TSA/PA ratio-slope correlation, ρ = 0.3917) and geomorphic consistency. The dataset, by accounting for three-dimensional topography, quantifies an additional 582,000 km² of surface area compared to traditional projected-area measurements. Consequently, this revision demonstrates that mountainous surface terrain is underestimated in previous assessments, with the updated estimate (67.25%, TSA-based) exceeding the Digital Map of China’s Mountains projection (64.9%, PA-based) by 2.35%. This foundational data layer enables more accurate area-dependent applications, including carbon stock accounting, hydrological modeling, habitat analysis, and the monitoring of SDGs. The complete dataset is openly available via the Zenodo repository to support further research.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

TSA-MC v1.0: A 30-m dataset of true surface area for China’s mountains to support SDG 15.4 indicators monitoring

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月7日

查看全文
  • Jinhu Bian,
  • Yaxin Wang,
  • Jinping Zhao,
  • Ainong Li,
  • Xi Nan,
  • Guangbin Lei,
  • Zhengjian Zhang,
  • Yi Deng,
  • Siyuan Li,
  • Amin Naboureh

摘要

Traditional two-dimensional Projected Area (PA) calculations systematically underestimate area of mountain ecosystems, introducing significant uncertainty into resource management and sustainable development assessments. To address this critical data gap, we present the True Surface Area of China’s Mountains (TSA-MC v1.0), the first nationwide, 30-m resolution dataset providing a physically realistic three-dimensional land surface measure. Developed from ASTER GDEM V2 using a robust pixel decomposition algorithm, its reliability was confirmed through rigorous validation of its physical accuracy (e.g., TSA/PA ratio-slope correlation, ρ = 0.3917) and geomorphic consistency. The dataset, by accounting for three-dimensional topography, quantifies an additional 582,000 km² of surface area compared to traditional projected-area measurements. Consequently, this revision demonstrates that mountainous surface terrain is underestimated in previous assessments, with the updated estimate (67.25%, TSA-based) exceeding the Digital Map of China’s Mountains projection (64.9%, PA-based) by 2.35%. This foundational data layer enables more accurate area-dependent applications, including carbon stock accounting, hydrological modeling, habitat analysis, and the monitoring of SDGs. The complete dataset is openly available via the Zenodo repository to support further research.