Articles | Volume 15, issue 11
https://doi.org/10.5194/essd-15-4959-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-4959-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
10 Nov 2023
Data description paper |
| 10 Nov 2023
| 10 Nov 2023
A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin
Shaomin Liu
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Ziwei Xu
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Xin Li
National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System and Resources Environment, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Tongren Xu
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Zhiguo Ren
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Yang Zhang
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Junlei Tan
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Lisheng Song
Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze–Huaihe River Basin, School of Geography and Tourism, Anhui Normal University, Wuhu 241000, China
Ji Zhou
School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China
Zhongli Zhu
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Xiaofan Yang
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Rui Liu
Institute of Urban Study, School of Environmental and Geographical Sciences (SEGS), Shanghai Normal University, Shanghai 200234, China
Yanfei Ma
Hebei Technology Innovation Centre for Remote Sensing Identification of Environmental Change, Hebei Key Laboratory of Environmental Change and Ecological Construction, School of Geographical Sciences, Hebei Normal University, Shijiazhuang 050024, China
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Cited
15 citations as recorded by crossref.
- Using Geostationary Satellite Observations to Improve the Monitoring of Vegetation Phenology J. Lu et al. 10.3390/rs16122173
- Innovative approach for estimating evapotranspiration and gross primary productivity by integrating land data assimilation, machine learning, and multi-source observations X. He et al. 10.1016/j.agrformet.2024.110136
- EATEM: A Method for Estimating Equivalent Acquisition Time of Pixels in UAV Thermal Infrared Mosaics Z. Wang et al. 10.1109/LGRS.2024.3459875
- Analysis of Spatial and Temporal Variations in Evapotranspiration and Its Driving Factors Based on Multi-Source Remote Sensing Data: A Case Study of the Heihe River Basin X. Li et al. 10.3390/rs16152696
- A Hybrid Model Coupling Physical Constraints and Machine Learning to Estimate Daily Evapotranspiration in the Heihe River Basin X. Li et al. 10.3390/rs16122143
- A Framework for Quantifying the Uncertainty in Upscaling Evapotranspiration From Homogeneous to Heterogeneous Underlying Surface X. Li et al. 10.1109/TGRS.2024.3453589
- A two-source non-parametric method for estimating terrestrial evapotranspiration: Validation at eddy covariance sites X. Pan et al. 10.1016/j.jhydrol.2024.132278
- Spatio-temporal variations and multi-scale correlations of climate, water, land, and vegetation resources over the past four decades in the Heihe River Basin D. Jiao et al. 10.1016/j.ejrh.2024.101941
- A System for Investigating Water–Heat–Salt-Mechanics Coupling Effects in Saline Soil under Climate Change Z. Zhou et al. 10.1061/JCRGEI.CRENG-824
- Effects of increased rainfall on heat and mass transfer and deformation of sulfate saline soil: An experimental investigation Z. Zhou et al. 10.1016/j.coldregions.2024.104363
- A Comprehensive Validation Scheme for Satellite-Derived Land Surface Temperature Dataset J. Ma et al. 10.1109/TGRS.2024.3488083
- Dataset of spatially extensive long-term quality-assured land–atmosphere interactions over the Tibetan Plateau Y. Ma et al. 10.5194/essd-16-3017-2024
- A Novel Land Surface Temperature Retrieval Algorithm for SDGSAT-1 Images N. Li et al. 10.1109/TGRS.2024.3514359
- TRIMS LST: a daily 1 km all-weather land surface temperature dataset for China's landmass and surrounding areas (2000–2022) W. Tang et al. 10.5194/essd-16-387-2024
- A dataset of energy, water vapor, and carbon exchange observations in oasis–desert areas from 2012 to 2021 in a typical endorheic basin S. Liu et al. 10.5194/essd-15-4959-2023
14 citations as recorded by crossref.
- Using Geostationary Satellite Observations to Improve the Monitoring of Vegetation Phenology J. Lu et al. 10.3390/rs16122173
- Innovative approach for estimating evapotranspiration and gross primary productivity by integrating land data assimilation, machine learning, and multi-source observations X. He et al. 10.1016/j.agrformet.2024.110136
- EATEM: A Method for Estimating Equivalent Acquisition Time of Pixels in UAV Thermal Infrared Mosaics Z. Wang et al. 10.1109/LGRS.2024.3459875
- Analysis of Spatial and Temporal Variations in Evapotranspiration and Its Driving Factors Based on Multi-Source Remote Sensing Data: A Case Study of the Heihe River Basin X. Li et al. 10.3390/rs16152696
- A Hybrid Model Coupling Physical Constraints and Machine Learning to Estimate Daily Evapotranspiration in the Heihe River Basin X. Li et al. 10.3390/rs16122143
- A Framework for Quantifying the Uncertainty in Upscaling Evapotranspiration From Homogeneous to Heterogeneous Underlying Surface X. Li et al. 10.1109/TGRS.2024.3453589
- A two-source non-parametric method for estimating terrestrial evapotranspiration: Validation at eddy covariance sites X. Pan et al. 10.1016/j.jhydrol.2024.132278
- Spatio-temporal variations and multi-scale correlations of climate, water, land, and vegetation resources over the past four decades in the Heihe River Basin D. Jiao et al. 10.1016/j.ejrh.2024.101941
- A System for Investigating Water–Heat–Salt-Mechanics Coupling Effects in Saline Soil under Climate Change Z. Zhou et al. 10.1061/JCRGEI.CRENG-824
- Effects of increased rainfall on heat and mass transfer and deformation of sulfate saline soil: An experimental investigation Z. Zhou et al. 10.1016/j.coldregions.2024.104363
- A Comprehensive Validation Scheme for Satellite-Derived Land Surface Temperature Dataset J. Ma et al. 10.1109/TGRS.2024.3488083
- Dataset of spatially extensive long-term quality-assured land–atmosphere interactions over the Tibetan Plateau Y. Ma et al. 10.5194/essd-16-3017-2024
- A Novel Land Surface Temperature Retrieval Algorithm for SDGSAT-1 Images N. Li et al. 10.1109/TGRS.2024.3514359
- TRIMS LST: a daily 1 km all-weather land surface temperature dataset for China's landmass and surrounding areas (2000–2022) W. Tang et al. 10.5194/essd-16-387-2024
Latest update: 25 Dec 2024
Short summary
We present a suite of observational datasets from artificial and natural oases–desert systems that consist of long-term turbulent flux and auxiliary data, including hydrometeorological, vegetation, and soil parameters, from 2012 to 2021. We confirm that the 10-year, long-term dataset presented in this study is of high quality with few missing data, and we believe that the data will support ecological security and sustainable development in oasis–desert areas.
We present a suite of observational datasets from artificial and natural oases–desert systems...
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