State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, 26 Xinong Road, Yangling, Shaanxi Province, 712100, P. R. China.
Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, 26 Xinong Road, Yangling, Shaanxi Province, 712100, P. R. China.
Sci Data. 2024 Apr 6;11(1):348. doi: 10.1038/s41597-024-03198-z.
Check dams on the Chinese Loess Plateau (CLP) have captured billions of tons of eroded sediment, substantially reducing sediment load in the Yellow River. However, uncertainties persist regarding the precise sediment capture and the role of these dams in Yellow River flow and sediment dynamics due to the lack of available spatial distribution datasets. We produced the first vectorized dataset of silted land formed by check dams on the CLP, combining high-resolution and easily accessible Google Earth images with object-based classification methods. The accuracy of the dataset was verified by 1947 collected test samples, and the producer's accuracy and user's accuracy of the dam lands were 88.9% and 99.5%, respectively. Our dataset not only provides fundamental information for accurately assessing the ecosystem service functions of check dams, but also helps to interpret current changes in sediment delivery of the Yellow River and plan future soil and water conservation projects.
中国黄土高原上的淤地坝已拦截了数以亿吨计的侵蚀泥沙，大量减少了黄河的输沙量。然而，由于缺乏可用的空间分布数据集，淤地坝对黄河水沙动态的具体拦沙作用仍存在不确定性。我们利用易于获取的谷歌地球高分辨率影像，结合基于对象的分类方法，首次生成了中国黄土高原淤地坝淤地空间分布的矢量数据集。通过 1947 个采集样本对数据集进行了验证，其坝地的生产者精度和使用者精度分别为 88.9%和 99.5%。该数据集不仅为准确评估淤地坝的生态系统服务功能提供了基础信息，还有助于解释黄河泥沙输送的现状变化，并规划未来的水土保持项目。
