Articles | Volume 14, issue 7
https://doi.org/10.5194/essd-14-3137-2022
© Author(s) 2022. 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-14-3137-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
STAR NDSI collection: a cloud-free MODIS NDSI dataset (2001–2020) for China
Yinghong Jing
School of Resource and Environmental Sciences, Wuhan University, Wuhan
430079, China
School of Remote Sensing and Information Engineering, Wuhan
University, Wuhan 430079, China
Huanfeng Shen
CORRESPONDING AUTHOR
School of Resource and Environmental Sciences, Wuhan University, Wuhan
430079, China
Collaborative Innovation Centre of Geospatial Technology, Wuhan
430079, China
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Xiaobin Guan, Zhihao Sun, Dong Chu, Guanglei Xie, Yuchen Wang, and Huanfeng Shen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-465, https://doi.org/10.5194/essd-2023-465, 2023
Preprint under review for ESSD
Short summary
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Although there are various XCO2 products, they are all limited by the spatial resolution or spatiotemporal coverage. In this study, the first global 0.05° XCO2 product (GCXCO2) for 21 years is generated by combining the OCO-2 satellite observations and models simulations. The dynamic normalization strategy is applied to enhance the temporal expansibility of stacking learning model, and the product is superior than the model simulations showing similar characteristic with OCO-2 observations.
Yonghong Zheng, Huanfeng Shen, Rory Abernethy, and Rob Wilson
Biogeosciences, 20, 3481–3490, https://doi.org/10.5194/bg-20-3481-2023, https://doi.org/10.5194/bg-20-3481-2023, 2023
Short summary
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Investigations in central and western China show that tree ring inverted latewood intensity expresses a strong positive relationship with growing-season temperatures, indicating exciting potential for regions south of 30° N that are traditionally not targeted for temperature reconstructions. Earlywood BI also shows good potential to reconstruct hydroclimate parameters in some humid areas and will enhance ring-width-based hydroclimate reconstructions in the future.
Y. Tao, W. Huang, W. Gan, and H. Shen
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 209–215, https://doi.org/10.5194/isprs-annals-V-3-2022-209-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-209-2022, 2022
Xiaobin Guan, Huanfeng Shen, Yuchen Wang, Dong Chu, Xinghua Li, Linwei Yue, Xinxin Liu, and Liangpei Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-156, https://doi.org/10.5194/essd-2021-156, 2021
Preprint withdrawn
Short summary
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This study generated the first global 1-km continuous NDVI product (STFLNDVI) for 4-decades by fusing multi-source satellite products. Simulated and real-data assessments confirmed the satisfactory and stable accuracy of STFLNDVI regarding spatial details and temporal variations. STFLNDVI is an ideal solution to the trade-off between spatial resolution and time coverage in current NDVI products, which of great significance for long-term regional and global vegetation and climate change studies.
L. Xu, J. Yang, S. Li, and X. Li
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 695–700, https://doi.org/10.5194/isprs-annals-V-3-2020-695-2020, https://doi.org/10.5194/isprs-annals-V-3-2020-695-2020, 2020
C. Zhou, J. Li, H. Shen, and Q. Yuan
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-5-2020, 101–107, https://doi.org/10.5194/isprs-annals-V-5-2020-101-2020, https://doi.org/10.5194/isprs-annals-V-5-2020-101-2020, 2020
R. Feng, X. Li, and H. Shen
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 479–484, https://doi.org/10.5194/isprs-annals-IV-2-W5-479-2019, https://doi.org/10.5194/isprs-annals-IV-2-W5-479-2019, 2019
Xinghua Li, Yinghong Jing, Huanfeng Shen, and Liangpei Zhang
Hydrol. Earth Syst. Sci., 23, 2401–2416, https://doi.org/10.5194/hess-23-2401-2019, https://doi.org/10.5194/hess-23-2401-2019, 2019
Short summary
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This paper is a review article on the cloud removal methods of MODIS snow cover products.
Z. Kugler, G. Szabó, H. M. Abdulmuttalib, C. Batini, H. Shen, A. Barsi, and G. Huang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 315–320, https://doi.org/10.5194/isprs-archives-XLII-4-315-2018, https://doi.org/10.5194/isprs-archives-XLII-4-315-2018, 2018
Tongwen Li, Chengyue Zhang, Huanfeng Shen, Qiangqiang Yuan, and Liangpei Zhang
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 143–147, https://doi.org/10.5194/isprs-annals-IV-3-143-2018, https://doi.org/10.5194/isprs-annals-IV-3-143-2018, 2018
Zhiwei Li, Huanfeng Shen, Yancong Wei, Qing Cheng, and Qiangqiang Yuan
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 149–152, https://doi.org/10.5194/isprs-annals-IV-3-149-2018, https://doi.org/10.5194/isprs-annals-IV-3-149-2018, 2018
X. Meng, H. Shen, Q. Yuan, H. Li, and L. Zhang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 831–835, https://doi.org/10.5194/isprs-archives-XLII-2-W7-831-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-831-2017, 2017
Xinxin Liu, Huanfeng Shen, Qiangqiang Yuan, Liangpei Zhang, and Qing Cheng
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-6, 57–61, https://doi.org/10.5194/isprs-annals-III-6-57-2016, https://doi.org/10.5194/isprs-annals-III-6-57-2016, 2016
Related subject area
Domain: ESSD – Global | Subject: Meteorology
ET-WB: water-balance-based estimations of terrestrial evaporation over global land and major global basins
Global High-Resolution Drought Indices for 1981–2022
GSDM-WBT: global station-based daily maximum wet-bulb temperature data for 1981–2020
The PANDA automatic weather station network between the coast and Dome A, East Antarctica
Jinghua Xiong, Abhishek, Li Xu, Hrishikesh A. Chandanpurkar, James S. Famiglietti, Chong Zhang, Gionata Ghiggi, Shenglian Guo, Yun Pan, and Bramha Dutt Vishwakarma
Earth Syst. Sci. Data, 15, 4571–4597, https://doi.org/10.5194/essd-15-4571-2023, https://doi.org/10.5194/essd-15-4571-2023, 2023
Short summary
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To overcome the shortcomings associated with limited spatiotemporal coverage, input data quality, and model simplifications in prevailing evaporation (ET) estimates, we developed an ensemble of 4669 unique terrestrial ET subsets using an independent mass balance approach. Long-term mean annual ET is within 500–600 mm yr−1 with a unimodal seasonal cycle and several piecewise trends during 2002–2021. The uncertainty-constrained results underpin the notion of increasing ET in a warming climate.
Solomon H. Gebrechorkos, Jian Peng, Ellen Dyer, Diego G. Miralles, Sergio M. Vicente-Serrano, Chris Funk, Hylke E. Beck, Dagmawi T. Asfaw, Michael B. Singer, and Simon J. Dadson
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-276, https://doi.org/10.5194/essd-2023-276, 2023
Revised manuscript accepted for ESSD
Short summary
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Drought is one of the most complex and major natural hazards and it has devastating impacts on the environment, economy, water resources, agriculture and society worldwide. High-resolution drought indices will help assess drought impacts at a global, regional and local scale thereby supporting the development of site-specific adaptation measures.
Jianquan Dong, Stefan Brönnimann, Tao Hu, Yanxu Liu, and Jian Peng
Earth Syst. Sci. Data, 14, 5651–5664, https://doi.org/10.5194/essd-14-5651-2022, https://doi.org/10.5194/essd-14-5651-2022, 2022
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We produced a new dataset of global station-based daily maximum wet-bulb temperature (GSDM-WBT) through the calculation of wet-bulb temperature, data quality control, infilling missing values, and homogenization. The GSDM-WBT covers the complete daily series of 1834 stations from 1981 to 2020. The GSDM-WBT dataset handles stations with many missing values and possible inhomogeneities, which could better support the studies on global and regional humid heat events.
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
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The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
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Short summary
Snow variation is a vital factor in global climate change. Satellite-based approaches are effective for large-scale environmental monitoring. Nevertheless, the high cloud fraction seriously impedes the remote-sensed investigation. Therefore, a recent 20-year cloud-free snow cover collection in China is generated for the first time. This collection can serve as a basic dataset for hydrological and climatic modeling to explore various critical environmental issues.
Snow variation is a vital factor in global climate change. Satellite-based approaches are...
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