WANG Jing

Research interest

1. Monitoring the spatial and temporal dynamics of forest ecosystems in a context of climate change;
2. Multi-source remote sensing data fusion and applications in land cover change mapping;
3. Capturing rapid and fine-scale land surface dynamics with CubeSats observations.
4. We are actively recruiting! Our group welcomes applications from graduate students, joint-training graduate students, research assistants, and postdoctoral fellows. Interested individuals, please feel free to reach out via email.

Education

08/2014–11/2018——Doctor of Philosophy

School & Department: The Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong

Major: Earth system and geo-information science

09/2011–07/2014——Master of Engineering 

School & Department: The Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing

Major: Electronics and communications engineering

09/2007-07/2011——Bachelor of Engineering 

School & Department: The School of Geoscience and Info-Physics, Central South University, Changsha

Major: Surveying and mapping

Work Experience

04/2019-present——Post-doctoral Fellow 

School & Department: School of Biological Sciences, The University of Hong Kong

Social Service

《Remote Sensing in Ecology and Conservation》 Associate Editor (AE)

Research Projects

Shenzhen Science and Technology Program,2022.10-2025.09, PI

National Natural Science Foundation of China, 2024.01-2026.12, PI

Overseas Postdoctoral Special Program, 2024.05-, PI

Publications

• Jing Wang*, Yuanzhi Li, Md Mizanur Rahman, Buhang Li, Zhengbing Yan, Guangqin Song, Yingyi Zhao, Jin Wu*, Chengjin Chu* (2024). Unraveling the Drivers and Impacts of Leaf Phenological Diversity in a Subtropical Forest: A Fine-Scale Analysis using PlanetScope CubeSats. New Phytologist. https://doi.org/10.1111/nph.19850
• Qu, Y.(2nd-year master’s student), Peñuelas, J., Yu, Z., Zeng, X., Zhang, Y., He, Y., Wu, Y.,Jing Wang *. Quantifying the Rate and Extent of Urbanization Effects on Vegetation Phenology in Mainland China. Remote Sens. 2025, 17, 2758. https://doi.org/10.3390/rs17162758
• Jing Wang#, Guangqin Song#, Michael Liddell, Patricia Morellato, Calvin K.F. Lee, Dedi Yang, Bruna Alberton, Matteo Detto, Xuanlong Ma, Yingyi Zhao, Henry C.H. Yeung, Hongsheng Zhang, Michael Ng, Bruce W. Nelson, Alfredo Huete, & Jin Wu* (2023). An ecologically-constrained deep learning model for tropical leaf phenology monitoring using PlanetScope satellites. Remote Sensing of Environment, 286, 113429.
• Jing Wang, Calvin KF Lee, Xiaolin Zhu, Ruyin Cao, Yating Gu, Shengbiao Wu, Jin Wu* (2022). A new object-class based gap-filling method for PlanetScope satellite image time series，Remote Sensing of Environment, 280, 113136.  
• Jing Wang, Dedi Yang, Shuli Chen, Xiaolin Zhu, Shengbiao Wu, Marc Bogonovich, Zhengfei Guo, Zhe Zhu, Jin Wu* (2021). Automatic cloud and cloud shadow detection in tropical areas for PlanetScope satellite images. Remote Sensing of Environment, 264, 112604.
• Jing Wang, Dedi Yang, Matteo Detto, Bruce W. Nelson, Min Chen, Kaiyu Guan, Shengbiao Wu, Zhengbin Yan, and Jin Wu* (2020). Multi-scale integration of satellite remote sensing improves characterization of dry-season green-up in an Amazon tropical evergreen forest. Remote Sensing of Environment, 246, 111865.
• Jing Wang, Bo Huang*, Hankui H. Zhang*, Peifeng Ma (2019). Sentinel-2A image fusion using a machine learning approach, IEEE Transactions on Geoscience and Remote Sensing, 57(12), 9589-9601.
• Jing Wang and Bo Huang* (2018). A spatiotemporal satellite image fusion model with auto-regressive error correction (AREC), International Journal of Remote Sensing, 39(20), 6731-6756.
• Jing Wang and Bo Huang* (2017). A rigorously-weighted spatiotemporal fusion model with uncertainty analysis, Remote Sensing, 9(10), 990.
• Jing Wang, Junyong Fang*, Xue Liu, Dong Zhao, Qing Xiao (2014). A fast mosaic method for airborne images: the new Template-Convolution Speed-Up Robust Features (TSURF) algorithm, International Journal of Remote Sensing, 35(16), 5959-5970.
• Guangqin Song, Shengbiao Wu, Calvin K.F. Lee, Shawn P. Serbin, Brett Wolfe, Michael K. Ng, Marc Bogonovich, Jing Wang, Ziyu Lin, Scott Saleska, Bruce W. Nelson, Alistair Rogers, and Jin Wu* (2022). Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies. ISPRS Journal of Photogrammetry and Remote Sensing, 183, 19-33.
• Zhengbing Yan, Zhengfei Guo, Shawn P Serbin, Guangqin Song, Yingyi Zhao, Yang Chen, Shengbiao Wu, Jing Wang, Xin Wang, Jing Li, Bin Wang, Yuntao Wu, Yanjun Su, Han Wang, Alistair Rogers, Lingli Liu, Jin Wu* (2021). Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types. New Phytologist.
• Shengbiao Wu, Jing Wang, Zhengbing Yan, Guangqin Song, Yang Chen, Qin Ma, Meifeng Deng, Yuntao Wu, Yingyi Zhao, Zhengfei Guo, Zuoqiang Yuan, Guanhua Dai, Xiangtao Xu, Xi Yang, Yanjun Su, Lingli Liu, and Jin Wu* (2021). Monitoring tree-crown scale autumn leaf phenology in a temperate forest with an integration of PlanetScope and drone remote sensing observations. ISPRS Journal of Photogrammetry and Remote Sensing, 171, 36-48.