Professor Ma received the B.S. degree from Shandong University of Science and Technology, M.S. and Ph.D. degree from Beijing Normal University. She was a Joint Ph.D. Student with the Department of Geographical Sciences, University of Maryland. She was working at Wuhan University prior to joining HKU. Her main research interests include radiative transfer modeling, development of land surface and atmosphere variables retrieval algorithms using data assimilation and machine learning techniques, to support global environmental change applications and sustainable development.
Research Interests
-
Land-atmosphere parameters retrieval from multiple satellite observations
-
Land and atmospheric radiative transfer modeling
-
Data assimilation and machine learning methodology
-
Global high-resolution seamless satellite biophyscial products development
Selected Publications
2025
Zhang, F., Liang, S., Ma, H., Li, W., Chen, Y., He, T.,…Zhang, Y. (2026). A review of crop yield estimation on pixel and field scales from remotely sensed data. Science of Remote Sensing, 13, 100342. https://doi.org/10.1016/j.srs.2025.100342
Zhang, Y., Liang, S., Ma, H., He, T., Tian, F., Zhang, G., & Xu, J. (2025). A seamless global daily 5 km soil moisture product from 1982 to 2021 using AVHRR satellite data and an attention-based deep learning model. Earth system science data, 17(10), 5181-5207. https://doi.org/10.5194/essd-17-5181-2025
Ma, Y., Liang, S., Peng, W., He, T., Ma, H., Chen, Y.,…Guan, S. (2025). A universal physically-based topographic correction framework for high-resolution optical satellite data. ISPRS journal of photogrammetry and remote sensing, 227, 459-480. https://doi.org/10.1016/j.isprsjprs.2025.05.027
Li, W., Liang, S., Chen, K., Chen, Y., Ma, H., Xu, J.,…Shi, Z. (2026). AgriFM: A multi-source temporal remote sensing foundation model for Agriculture mapping. Remote sensing of environment, 334, 115234. https://doi.org/10.1016/j.rse.2026.115234
Liang, S., He, T., Cheng, J., Jiang, B., Jin, H., Li, A.,…Li, L. (2025). An overview of the high-resolution global LAnd surface satellite (Hi-GLASS) products suite. Science of Remote Sensing, 12, 100263. https://doi.org/10.1016/j.srs.2025.100263
Mai, S., He, M., Wu, X., Lu, Y., Gan, Z., Chen, Y., & Ma, H. (2025). Application of network pharmacology and molecular docking to explore the mechanism of metronidazole in treating paronychia. Journal of biotech research, 23, 104-109.
Wenyuan, L. a. L. S. a. C. Y. a. M. H. a. M. Y. a. C. Z. a. F. H. a. Z. F. (2025). Asiawheat: The First Asian 250-M Annual Fractional Wheat Cover Time Series (2001-2023) Using Convolutional Neural Networks and Transformer Models. https://doi.org/10.2139/ssrn.5102645
Li, W., Liang, S., Zhang, Y., Liu, L., Chen, K., Chen, Y.,…Shi, Z. (2025). Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream Transformer Method. https://doi.org/10.48550/arxiv.2506.06155
Liang, H., Liang, S., Jiang, B., He, T., Tian, F., Ma, H.,…Fang, H. (2025). Generation of global 1 km daily land surface–air temperature difference and sensible heat flux products from 2000 to 2020. Earth system science data, 17(10), 5571-5600. https://doi.org/10.5194/essd-17-5571-2025
The First Algorithm for Mapping High-Resolution Cropland Inundation Status Throughout the Growing Season Using Swot Karin Data. (2025).
Ma, H., Wang, Q., Li, W., Chen, Y., Xu, J., Ma, Y.,…Liang, S. (2025). The first gap-free 20 m 5-day LAI/FAPAR products over China (2018–2023) from integrated Landsat-8/9 and Sentinel-2 Analysis Ready Data. Remote sensing of environment, 331, 115048. https://doi.org/10.1016/j.rse.2025.115048
Zhang, Y., Liang, S., Li, W., Ma, H., Xu, J., Ma, Y.,…Xia, X.-G. (2026). UniTS: Unified Spatio-Temporal Generative Model for Remote Sensing. https://doi.org/10.48550/arxiv.2512.04461
2024
Liang, S., He, T., Huang, J., Jia, A., Zhang, Y., Cao, Y., . . . Song, L. (2024). "Advancements in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges." Science of Remote Sensing 10: 100152. DOI:https://doi.org/10.1016/j.srs.2024.100152
Fang, H., Liang, S., Chen, Y., Ma, H., Li, W., He, T., . . . Zhang, F. (2024). "A comprehensive review of rice mapping from satellite data: Algorithms, product characteristics and consistency assessment." Science of Remote Sensing 10: 100172. DOI:https://doi.org/10.1016/j.srs.2024.100172
Li, B., Liang, S., Ma, H., Dong, G., Liu, X., He, T. and Zhang, Y. (2024). "Generation of global 1 km all-weather instantaneous and daily mean land surface temperatures from MODIS data." Earth System Science Data 16(8): 3795-3819. DOI:https://doi.org/10.5194/essd-16-3795-2024
Ding, A., Ma, H., Liang, S., Jiao, Z., Kokhanovsky, A., Shi, H., . . . Xu, K. (2024). Hapke-Hsr + Marmir-2: An Improved Soil Reflectance Model, Elsevier BV. DOI:https://doi.org/10.2139/ssrn.4762428
Ding, A., Liang, S., Ma, H., He, T., Jia, A. and Wang, Q. (2024). "Improved estimation of daily blue-sky snow shortwave albedo from MODIS data and reanalysis information." Science of Remote Sensing 10: 100163. DOI:https://doi.org/10.1016/j.srs.2024.100163
Liang, S., Chen, Y., Liu, J., Ma, H., Li, W., Sucharitakul, P., . . . Xu, J. (2024). Mapping Paddy Rice Cropping Intensity and Calendar in Monsoon Asia at 20 M Resolution between 2018 and 2021 from Multi-Source Satellite Data Using a Sample-Free Algorithm, Elsevier BV. DOI:https://doi.org/10.2139/ssrn.4948283
Huang, J., Song, J., Huang, H., Zhuo, W., Niu, Q., Wu, S., . . . Liang, S. (2024). "Progress and perspectives in data assimilation algorithms for remote sensing and crop growth model." Science of Remote Sensing 10: 100146. DOI:https://doi.org/10.1016/j.srs.2024.100146
Ding, A., Jiao, Z., Ma, H., Kokhanovsky, A., Guo, J., Zhang, X. and Dong, Y. (2024). The Reflectance of Solar Light from Natural Surfaces, Springer Nature Switzerland: 1-84. DOI:https://doi.org/10.1007/978-3-031-66578-3_1
Zhang, G., Liang, S., Ma, H., He, T., Yin, G., Xu, J., . . . Zhang, Y. (2024). "Simultaneous estimation of five temporally regular land variables at seven spatial resolutions from seven satellite data using a multi-scale and multi-depth convolutional neural network." Remote Sensing of Environment 301: 113928. DOI:https://doi.org/10.1016/j.rse.2023.113928