中国大陆互花米草亚米级全国范围制图数据集（2020年）

当前10米分辨率的互花米草大规模分布图难以精确划定群落边界、探测潮沟等内部特征及识别小型斑块。这些局限性进一步影响了空间分布提取与后续分析的准确性。为此，本研究采用"对象化与亚米级增强的像元物候特征融合法（OSPPF）"，首次研制了2020年中国大陆亚米级互花米草分布图（CM-SSM...

Currently available large-scale distribution maps of *Spartina alterniflora* at 10-meter resolution are unable to accurately delineate community boundaries, detect internal features such as tidal creeks, and identify small patches. These limitations further compromise the accuracy of spatial distribution extraction and subsequent downstream analyses. To address these limitations, this study employs the Object-based and Sub-meter Enhanced Pixel Phenological Feature Fusion (OSPPF) method, and for the first time constructs the 2020 sub-meter distribution map of *Spartina alterniflora* in mainland China (CM-SSM...

搜集汇总

背景与挑战

背景概述

该数据集是2020年中国大陆互花米草（一种入侵植物）的亚米级高分辨率全国范围分布图，采用“对象化与亚米级增强的像元物候特征融合法（OSPPF）”，融合了Sentinel-2卫星物候特征和谷歌地球影像空间纹理，显著提升了制图精度和斑块探测能力。相比现有10米分辨率产品，总体精度提高14.60%，F1分数增加0.21，识别的斑块数量多17倍，并更准确地支持土壤有机碳储量估算，为滨海湿地管理和生态研究提供科学依据。