Huichan Liu, G. He, Yan Peng, Gui-zhou Wang, R. Yin
{"title":"青藏高原2022年30米空间分辨率陆地地表水数据集","authors":"Huichan Liu, G. He, Yan Peng, Gui-zhou Wang, R. Yin","doi":"10.11922/11-6035.csd.2023.0040.zh","DOIUrl":null,"url":null,"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.","PeriodicalId":57643,"journal":{"name":"China Scientific Data","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A dataset of land surface water with a spatial resolution of 30 meters on the Qinghai-Tibet Plateau in 2022\",\"authors\":\"Huichan Liu, G. He, Yan Peng, Gui-zhou Wang, R. Yin\",\"doi\":\"10.11922/11-6035.csd.2023.0040.zh\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":57643,\"journal\":{\"name\":\"China Scientific Data\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"China Scientific Data\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.11922/11-6035.csd.2023.0040.zh\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"China Scientific Data","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.11922/11-6035.csd.2023.0040.zh","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A dataset of land surface water with a spatial resolution of 30 meters on the Qinghai-Tibet Plateau in 2022
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.