Education
Kebiao Mao obtained his Ph.D. in Geographic Information Systems from the Chinese Academy of Sciences after completing his Bachelor’s and Master’s degrees in Geography from Northeast Normal University and Nanjing University, respectively.
Research Focus
Professor Mao’s research primarily focuses on remote sensing applications in agriculture, with a particular emphasis on geophysical parameters retrieval, satellite data assimilation, and the development of crop growth models. He specializes in utilizing artificial intelligence and big data techniques to monitor drought, estimate land surface temperature, and analyze soil moisture.
Professional Journey
Professor Mao has held various academic and research positions throughout his career. He has served as a Professor at the Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, and as an Associate Professor and Assistant Researcher in the same institution. Additionally, he has undertaken visiting research positions at prestigious institutions, such as the National Central University in Taiwan.
Honors & Awards
Throughout his career, Professor Mao has received numerous honors and awards for his outstanding contributions to the field of remote sensing and agricultural science. His innovative research has been recognized both nationally and internationally, solidifying his reputation as a leading expert in his field.
Publications Top Noted & Contributions
Professor Mao has authored over 150 papers in international and Chinese scientific journals, covering a wide range of topics related to remote sensing and agricultural resources management. He has also applied for several patents for inventions, demonstrating his commitment to advancing technological solutions in the field.
“Near‐surface air temperature estimation from ASTER data based on neural network algorithm” (2008):
- Authors: K. Mao, HJ Tang, XF Wang, QB Zhou, DL Wang
- Published in the International Journal of Remote Sensing.
- This article discusses the estimation of near-surface air temperature using ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data, employing a neural network algorithm.
“A fine-resolution soil moisture dataset for China in 2002–2018” (2020):
- Authors: X Meng, K Mao, F Meng, J Shi, J Zeng, X Shen, Y Cui, L Jiang, Z Guo
- Published in Earth System Science Data Discussions.
- It presents a detailed dataset of soil moisture at a fine resolution for China spanning from 2002 to 2018.
“Analysis of the spatiotemporal change in land surface temperature for a long-term sequence in Africa (2003–2017)” (2020):
- Authors: N NourEldeen, K Mao, Z Yuan, X Shen, T Xu, Z Qin
- Published in Remote Sensing.
- This article analyzes the spatiotemporal changes in land surface temperature over a long-term period (2003–2017) in Africa.
“An RM‐NN algorithm for retrieving land surface temperature and emissivity from EOS/MODIS data” (2007):
- Authors: K Mao, J Shi, ZL Li, H Tang
- Published in the Journal of Geophysical Research: Atmospheres.
- It proposes an algorithm called RM‐NN for retrieving land surface temperature and emissivity from EOS/MODIS data.
“A soil moisture estimation framework based on the CART algorithm and its application in China” (Year not specified):
- Authors: J Han, K Mao, T Xu, J Guo, Z Zuo, C Gao
- Published in the Journal of Hydrology.
- This article presents a framework for estimating soil moisture based on the CART (Classification and Regression Trees) algorithm and its application in China.
Research Timeline
Professor Mao’s research journey has evolved over the years, starting with his education in geography and culminating in his current position as a Professor at the Institute of Agricultural Resources and Regional Planning. Along the way, he has made significant contributions to the field through his research, publications, and patent applications, shaping the landscape of remote sensing and agricultural resources management.
