Department of Geography and Resource Management (GRM), The Chinese University of Hong Kong

Prof. MA Peifeng

Faculty Member

Prof. MA Peifeng

Vice-Chancellor Assistant Professor


(852) 3943-6533


  • 08/2023-07/2025 Development of CUHK satellites and integrated remote sensing technologies for near real-time landslide monitoring (PC, Innovation and Technology Fund)
  • 01/2023-12/2024 Deep learning-based radar remote sensing of land subsidence in deltaic metropolitan regions for sustainable development (PI, RGC General Research Fund)
  • 04/2022-03/2024 Multi-Temporal InSAR Remote Sensing for Sustainable Conservation of World Heritage (PI, CUHK Knowledge Transfer Project Fund)
  • 11/2021-10/2023 Integration of DInSAR and SAR Offset Tracking Technologies for Large Deformation Monitoring of Hong Kong Boundary Crossing Facilities (PC, Innovation and Technology Fund)
  • 10/2020-10/2022 Development of InSAR Deformation Analysis Technologies for Urban Infrastructural Safety Diagnosis  (PC, Innovation and Technology Fund)
  • 01/2020-12/2021 Deep Learning of InSAR Time-Series Deformation for Infrastructural Health Diagnosis  (PI, RGC General Research Fund)
  • 01/2020-12/2023 Fast Estimation and Intelligent Prediction of Time-Series Deformation Based  on Multi-baseline SAR(PI, National Natural Science Foundation of China)
  • 10/2018-09/2020 Continuous Land Cover Change Monitoring Using High-Resolution SAR Images for Hong Kong (PC, Innovation and Technology Fund)
  • 09/2016-08/2018 Remote Sensing of Infrastructural Dynamics and Early Warning of Risks for a Sustainable Built Environment (PI, AXA Research Fund)
  • 01/2017-12/2019 Robust detection of Persistent Scatterers in Complex Built Environments with Cloudy and Rainy Weather (PI, National Natural Science Foundation of China)
  • 11/2016-04/2018 Deformation Monitoring of Critical Infrastructures on Shenzhen Western Reclamation Lands and Early Warning of Risks (PI, Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources)
  • 07/2016-08/2018 Pilot Study on the Use of Remote Sensing Techniques in Ground Deformation Monitoring for the Hong Kong International Airport (Co-PI and technical leader, Innovation and Technology Fund)


[1] Ma, P., Lin, H., Wang, W., Yu, H., Chen, F., Jiang, L., . . . Wang, J., 2021. Toward Fine Surveillance: A Review of Multitemporal Interferometric Synthetic Aperture Radar for Infrastructure Health Monitoring. IEEE Geoscience and Remote Sensing Magazine, 2-25.

[2] Zhao, Z., Wu, Z., Zheng, Y., & Ma, P.*, 2021. Recurrent neural networks for atmospheric noise removal from InSAR time series with missing values. ISPRS Journal of Photogrammetry and Remote Sensing, 180, 227-237.

[3] Lin, Y., Wan, L., Zhang, H., Wei, S., Ma, P.*, Li, Y., & Zhao, Z., 2021. Leveraging optical and SAR data with a UU-Net for large-scale road extraction. International Journal of Applied Earth Observation and Geoinformation, 103, 102498.

[4] Wu, Z., Zhao, Z., Ma, P.*, & Huang, B., 2021. Real-World DEM Super-Resolution based on Generative Adversarial Networks for Improving InSAR Topographic Phase Simulation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1-1.

[5] Ma, P., Cui, Y., Wang, W., Lin, H., & Zhang, Y., 2021. Coupling InSAR and numerical modeling for characterizing landslide movements under complex loads in urbanized hillslopes. Landslides, 1-13.

[6] Shi, G., Ma, P.*, Hu, X., Huang, B., & Lin, H., 2021. Surface response and subsurface features during the restriction of groundwater exploitation in Suzhou (China) inferred from decadal SAR interferometry. Remote Sensing of Environment, 256, 112327.

[7] Ma, P., Zhang, F., Lin, H., 2020. Prediction of InSAR time-series deformation using deep convolutional neural networks. Remote Sensing Letters 11, 137-145.

[8] Shi, G., Ma, P., Lin, H., Huang, B., Zhang, B., Liu, Y., 2020. Potential of Using Phase Correlation in Distributed Scatterer InSAR Applied to Built Scenarios. Remote Sensing 12, 686.

[9] Ma, P., Wang, W., Zhang, B., Wang, J., Shi, G., Huang, G., Chen, F., Jiang, L., Lin, H., 2019. Remotely sensing large-and small-scale ground subsidence: A case study of the Guangdong–Hong Kong–Macao Greater Bay Area of China. Remote Sensing of Environment 232, 111282.

[10] Ma, P., Li, T., Fang, C., Lin, H., 2019. A tentative test for measuring the sub-millimeter settlement and uplift of a high-speed railway bridge using COSMO-SkyMed images. ISPRS Journal of Photogrammetry and Remote Sensing 155, 1-12.

[11] Liu, Y., Ma, P.*, Lin, H., Wang, W., Shi, G., 2019. Distributed Scatterer InSAR Reveals Surface Motion of the Ancient Chaoshan Residence Cluster in the Lianjiang Plain, China. Remote Sensing 11, 166.

[12] Ma, P., Liu, Y., Wang, W., Lin, H., 2019. Optimization of PSInSAR networks with application to TomoSAR for full detection of single and double persistent scatterers. Remote Sensing Letters 10, 717-725.

[13] Shi, G., Lin, H., Bürgmann, R., Ma, P., Wang, J., Liu, Y., 2019. Early soil consolidation from magnetic extensometers and full resolution SAR interferometry over highly decorrelated reclaimed lands. Remote Sensing of Environment 231, 111231.

[14] Zhang, B., Wang, R., Deng, Y., Ma, P., Lin, H., Wang, J., 2019. Mapping the Yellow River Delta land subsidence with multitemporal SAR interferometry by exploiting both persistent and distributed scatterers. ISPRS Journal of Photogrammetry and Remote Sensing 148, 157-173.

[15] Wang, J., Deng, Y., Wang, R., Ma, P., Lin, H., 2019. A Small-Baseline InSAR Inversion Algorithm Combining a Smoothing Constraint and L₁-Norm Minimization. IEEE Geoscience and Remote Sensing Letters.

[16] Wang, J., Huang, B., Zhang, H.K., Ma, P., 2019. Sentinel-2A Image Fusion Using a Machine Learning Approach. IEEE Transactions on Geoscience and Remote Sensing 57, 9589-9601.

[17] Shi, G., Lin, H., Ma, P.*, 2018. A Hybrid Method for Stability Monitoring in Low-Coherence Urban Regions Using Persistent and Distributed Scatterers. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1-11.

[18] Zhou, L., Chai, D., Xia, Y., Ma, P., 2018. Comparison of optimization algorithms for interferometric synthetic aperture radar phase unwrapping based on identical Markov random fields. Journal of Applied Remote Sensing 12, 025016.

[19] Sun, Q., Jiang, L., Jiang, M., Lin, H., Ma, P., Wang, H., 2018. Monitoring Coastal Reclamation Subsidence in Hong Kong with Distributed Scatterer Interferometry. Remote Sensing 10, 1738.

[20] Zhou, L., Chai, D., Xia, Y., Ma, P., Lin, H., 2018. Interferometric synthetic aperture radar phase unwrapping based on sparse Markov random fields by graph cuts. Journal of Applied Remote Sensing 12, 015006.

[21] Lin, H., Ma, P.*, 2017. Urban infrastructural health diagnosis with satellite-terrestrial sensing technologies. Annals of GIS, 1-8.

[22] Lin Hui, Ma, P.*, Wang Weixi, 2017. Urban Infrastructure Health Monitoring with Spaceborne Multi-temporal Synthetic Aperture Radar Interferometry[J]. Acta Geodaetica et Cartographica Sinica, 46(10): 1421-1433.

[23] Chen, F., Guo, H., Ma, P., Lin, H., Wang, C., Ishwaran, N., Hang, P., 2017. Radar interferometry offers new insights into threats to the Angkor site. Science advances 3, e1601284.

[24] Xu, Y., Ren, C., Ma, P., Ho, J., Wang, W., Lau, K.K.-L., Lin, H., Ng, E., 2017. Urban morphology detection and computation for urban climate research. Landscape and Urban Planning 167, 212-224.

[25] Chen, F., Wu, Y., Zhang, Y., Parcharidis, I., Ma, P., Xiao, R., Xu, J., Zhou, W., Tang, P., Foumelis, M., 2017. Surface Motion and Structural Instability Monitoring of Ming Dynasty City Walls by Two-Step Tomo-PSInSAR Approach in Nanjing City, China. Remote Sensing 9, 371.

[26] Ma, P., Lin, H., 2016. Robust Detection of Single and Double Persistent Scatterers in Urban Built Environments. IEEE Transactions on Geoscience and Remote Sensing 54, 2124-2139.

[27] Ma, P., Lin, H., Lan, H., Chen, F., 2015. Multi-dimensional SAR tomography for monitoring the deformation of newly built concrete buildings. ISPRS Journal of Photogrammetry and Remote Sensing 106, 118-128.

[28] Ma, P., Lin, H., Lan, H., Chen, F., 2015. On the performance of reweighted L1 minimization for tomographic SAR imaging. IEEE Geoscience and Remote Sensing Letters 12, 895-899.

Teaching Fields

Remote sensing
Smart cities
Big data analysis
Sustainable development

Research interests

SAR/InSAR remote sensing
Geohazard monitoring
Carbon neutrality
sustainable development

Services/ Posts

Contact person, United Nations Economic and Social Commission for Asia and the Pacific Hong Kong Focal Point
Contact person, Department of Hong Kong Research, Development and Training, National Remote Sensing Center of China, MOST
Expert Review Panel, Logistics and Supply Chain MultiTech R&D Centre, Innovation and Technology Commission (ITC)
Council Member, China Association of Remote Sensing Application, Loess Plateau Chapter
Senior Member, Institute of Electrical and Electronics Engineers (IEEE)
Member, Association of American Geographers (AAG)


First Class, National Surveying and Mapping Science and Technology Progress Award, 2020
Remote Sensing Young Talent Award, National Remote Sensing Centre of China, MOST, 2017
AXA Post-Doctoral Fellowships, AXA Research Fund, 2016
Postgraduate Research Output Award, The Chinese University of Hong Kong, 2016
First Class, Yuen-Yuen Scholarship, The Chinese University of Hong Kong, 2015
Chen Shupeng Scholarship, The Chinese University of Hong Kong, 2013


I am currently recruiting postdoctoral fellow, postgraduate student and research assistant with the background of computer science, SAR/InSAR remote sensing, GIS, and signal and information processing. Please contact me via email if you have the interests.