On the morning of April 8, 2022, the Award Ceremony of the First Outstanding Shared Open Remote Sensing Dataset Collection Event was held at the Aerospace Information Research Institute (AIR) under the Chinese Academy of Sciences (CAS) both online and offline. The surface soil moisture dataset jointly published by the Research Group of Associate Professor Lu Hui of Tsinghua University and Dr Yao Panpan of the AIR, CAS won the "Top Ten Most Valuable Datasets" award, and Lu Hui's team won the honor of "Top Ten Data Teams with the Greatest Contributions".

Lu Hui (second from left) received the award at the Award Ceremony

Lu Hui (corresponding author) and Yao Panpan (first author), together with Associate Researcher Zhao Tianjie of the Chinese Academy of Sciences, Researcher Shi Jiancheng of the National Space Science Center (NSSC) of the Chinese Academy of Sciences (CAS), Professor Yang Kun of Tsinghua University, and researchers of US Department of Agriculture (USDA) and Massachusetts Institute of Technology (MIT), jointly completed “a long term global daily soil moisture dataset derived from AMSR-E and AMSR2 (2002-2020)”, and the results were published in Scientific Data (2021). This dataset, built with a completely domestic independently developed algorithm, features an accuracy equivalent to that of SMAP soil moisture products with the best international accuracy, and it has Long-term and high time-space consistency. The dataset had been continuously updated to 2021, providing global surface soil moisture information for nearly 20 years (2002/07/27~2021/12/31). The data have by far been browsed and downloaded for over 9,000 times.

Award Certificate of "Top Ten Most Valuable Annual Datasets"

This evaluation is the first of its kind jointly organized by the National Earth Observation Scientific Data Center, Journal of Remote Sensing and other units. The results have been produced after strict review by the scientific committee and the review expert group led by seven academicians including Tong Qingxi. The evaluation team commended the selected works for having achieved remarkable results in open sharing, representing the highest level of open sharing of scientific data in the field of remote sensing in China. The selected teams have made outstanding contributions to the output and research of scientific data in China.

Webpage publishing the results of dataset evaluation:

http://www.aircas.ac.cn/dtxw/kydt/202203/t20220302_6380706.html

Articles:

Yao, P.P., Lu, H., Shi, J.C., Zhao, T.J., Yang K., Cosh, M.H., Gianotti, D.J.S., & Entekhabi, D. (2021). A long term global daily soil moisture dataset derived from AMSR-E and AMSR2 (2002-2019). Scientific Data, 8, 143 (2021).

Yao, P.P., Shi, J.C., Zhao, T.J., Lu, H. & Al-Yaari, A. (2017). Rebuilding Long-term Global Soil Moisture Products Using the Neural Network Adopting the Microwave Vegetation Index. Remote Sensing 9(1), 35.

Data link:

https://data.tpdc.ac.cn/zh-hans/data/c26201fc-526c-465d-bae7-5f02fa49d738/

Written by Yao Panpan and Lu Hui

Edited by Wang Jiayin

Reviewed by Zhang Qiang