A dataset of land surface water with a spatial resolution of 30 meters on the Qinghai-Tibet Plateau in 2022

Huichan Liu, G. He, Yan Peng, Gui-zhou Wang, R. Yin
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Abstract

The Tibetan Plateau is known as the Asian Water Tower. The distribution of surface water and its changes are closely related to global change, biodiversity and water-related ecosystems. Based on the collection of high-precision land surface water samples, we used the random forest classification algorithm in machine learning to extract land surface water information from Landsat series satellite images and produced a dataset of land surface water with a spatial resolution of 30 meters on the Qinghai-Tibet Plateau based on satellite remote sensing images in 2022. According to data quality assessment, the overall accuracy of the dataset is 92.9%, and the Kappa coefficient is 0.84. This dataset can provide foundational data support for water resource monitoring, ecosystem services, and global change research on the Qinghai-Tibet Plateau.
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青藏高原2022年30米空间分辨率陆地地表水数据集
青藏高原被称为亚洲水塔。地表水的分布及其变化与全球变化、生物多样性和与水有关的生态系统密切相关。在采集高精度陆地地表水样本的基础上,利用机器学习中的随机森林分类算法从Landsat系列卫星图像中提取陆地地表水信息,并基于2022年卫星遥感图像生成了空间分辨率为30米的青藏高原陆地地表水数据集。根据数据质量评价,数据集的总体准确率为92.9%,Kappa系数为0.84。该数据集可为青藏高原水资源监测、生态系统服务和全球变化研究提供基础数据支持。
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