100-m-resolution surface soil moisture data during the thawing season on the Qinghai‒Tibet Plateau

Abstract The characteristics of the spatial distribution of surface soil moisture (SM) on the Qinghai‒Tibet Plateau (QTP) on a fine scale are unclear due to the lack of high-spatial-resolution SM datasets. To improve this situation, we first supplemented 659 SM datasets in areas on the QTP containin...

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Main Authors: Zhibin Li, Lin Zhao, Lingxiao Wang, Guangyue Liu, Erji Du, Defu Zou, Guojie Hu, Zanpin Xing, Chong Wang, Shibo Liu, Minxuan Xiao, Luhui Yin, Yiwei Wang
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-025-04831-1
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author Zhibin Li
Lin Zhao
Lingxiao Wang
Guangyue Liu
Erji Du
Defu Zou
Guojie Hu
Zanpin Xing
Chong Wang
Shibo Liu
Minxuan Xiao
Luhui Yin
Yiwei Wang
author_facet Zhibin Li
Lin Zhao
Lingxiao Wang
Guangyue Liu
Erji Du
Defu Zou
Guojie Hu
Zanpin Xing
Chong Wang
Shibo Liu
Minxuan Xiao
Luhui Yin
Yiwei Wang
author_sort Zhibin Li
collection DOAJ
description Abstract The characteristics of the spatial distribution of surface soil moisture (SM) on the Qinghai‒Tibet Plateau (QTP) on a fine scale are unclear due to the lack of high-spatial-resolution SM datasets. To improve this situation, we first supplemented 659 SM datasets in areas on the QTP containing sparse monitoring stations from 2021–2022 and integrated published SM datasets. Based on Sentinel-1&2 and measured SM data, we developed an SM retrieval algorithm for the ascending and descending orbits. Then, 100-m-resolution SM spatial data were generated for the thawing season of 2017–2023 in the SAR signal-applicable area on the QTP. As validated by the measured data, the correlation coefficients of the retrieval results for the ascending and descending orbits were 0.72 and 0.69, respectively, and the bias reached 0.07 m³/m³ and an RMSE of 0.07 m³/m³ for both. These SM datasets exhibit notable promise for improving our understanding and analysis of the ecology and hydrology of different environments on the QTP.
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publishDate 2025-03-01
publisher Nature Portfolio
record_format Article
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spelling doaj-art-4e888fa6b9354df299299e64e58cc5232025-08-20T02:49:29ZengNature PortfolioScientific Data2052-44632025-03-0112111510.1038/s41597-025-04831-1100-m-resolution surface soil moisture data during the thawing season on the Qinghai‒Tibet PlateauZhibin Li0Lin Zhao1Lingxiao Wang2Guangyue Liu3Erji Du4Defu Zou5Guojie Hu6Zanpin Xing7Chong Wang8Shibo Liu9Minxuan Xiao10Luhui Yin11Yiwei Wang12School of Geographical Sciences, Nanjing University of Information Science & TechnologySchool of Geographical Sciences, Nanjing University of Information Science & TechnologySchool of Geographical Sciences, Nanjing University of Information Science & TechnologyCryosphere Research Station on the Qinghai‒Tibet Plateau, State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of SciencesCryosphere Research Station on the Qinghai‒Tibet Plateau, State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of SciencesCryosphere Research Station on the Qinghai‒Tibet Plateau, State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of SciencesCryosphere Research Station on the Qinghai‒Tibet Plateau, State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of SciencesCenter for the Pan-Third Pole Environment, Lanzhou UniversitySchool of Geographical Sciences, Nanjing University of Information Science & TechnologySchool of Geographical Sciences, Nanjing University of Information Science & TechnologySchool of Geographical Sciences, Nanjing University of Information Science & TechnologySchool of Geographical Sciences, Nanjing University of Information Science & TechnologySchool of Geographical Sciences, Nanjing University of Information Science & TechnologyAbstract The characteristics of the spatial distribution of surface soil moisture (SM) on the Qinghai‒Tibet Plateau (QTP) on a fine scale are unclear due to the lack of high-spatial-resolution SM datasets. To improve this situation, we first supplemented 659 SM datasets in areas on the QTP containing sparse monitoring stations from 2021–2022 and integrated published SM datasets. Based on Sentinel-1&2 and measured SM data, we developed an SM retrieval algorithm for the ascending and descending orbits. Then, 100-m-resolution SM spatial data were generated for the thawing season of 2017–2023 in the SAR signal-applicable area on the QTP. As validated by the measured data, the correlation coefficients of the retrieval results for the ascending and descending orbits were 0.72 and 0.69, respectively, and the bias reached 0.07 m³/m³ and an RMSE of 0.07 m³/m³ for both. These SM datasets exhibit notable promise for improving our understanding and analysis of the ecology and hydrology of different environments on the QTP.https://doi.org/10.1038/s41597-025-04831-1
spellingShingle Zhibin Li
Lin Zhao
Lingxiao Wang
Guangyue Liu
Erji Du
Defu Zou
Guojie Hu
Zanpin Xing
Chong Wang
Shibo Liu
Minxuan Xiao
Luhui Yin
Yiwei Wang
100-m-resolution surface soil moisture data during the thawing season on the Qinghai‒Tibet Plateau
Scientific Data
title 100-m-resolution surface soil moisture data during the thawing season on the Qinghai‒Tibet Plateau
title_full 100-m-resolution surface soil moisture data during the thawing season on the Qinghai‒Tibet Plateau
title_fullStr 100-m-resolution surface soil moisture data during the thawing season on the Qinghai‒Tibet Plateau
title_full_unstemmed 100-m-resolution surface soil moisture data during the thawing season on the Qinghai‒Tibet Plateau
title_short 100-m-resolution surface soil moisture data during the thawing season on the Qinghai‒Tibet Plateau
title_sort 100 m resolution surface soil moisture data during the thawing season on the qinghai tibet plateau
url https://doi.org/10.1038/s41597-025-04831-1
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