Publications

Book Chapters

[1]

Geospatial practices for sustainable development in Asia and the Pacific 2022: A compendium.

ESCAP United Nations (2023).
United Nations publication. (Research support)
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Peer-reviewed Papers

* -- indicates the corresponding author

[1]

Uncovering the role of solar radiation and water stress factors in constraining decadal intra-site spring phenology variability in diverse ecosystems across the Northern Hemisphere

Gu, Y., Meng, L., Wang, Y., Wu, Z., Pan, Y., Zhao, Y., Detto, M. and Wu, J. (2025).
New Phytol.
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[2]

Analysis of continuous calving front retreat and the associated influencing factors of the Thwaites Glacier using high-resolution remote sensing data from 2015 to 2023

Zhu, Q., Guo, H., Zhang, L., Liang, D., Wu, Z., Liu, Y., Dou, X., and, X.D. (2024).
Int. J. Digit. Earth 17, 2390438.
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[3]

Efficient management and processing of massive InSAR images using an HPC-based cloud platform.

Wu, Z., Ma, P., Zhang, X., & Ye, G. (2024).
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17: 2866-2876.
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[4]

Improving time-series InSAR deformation estimation for city clusters by deep learning-based atmospheric delay correction.

Ma, P., Yu, C., Jiao, Z., Zheng, Y., Wu, Z.*, Mao, W., & Lin, H. (2024).
Remote Sensing of Environment, 304: 114004.
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[ESI Highly Cited Paper]
[5]

SAR-Transformer-based decomposition and geophysical interpretation of InSAR time-series deformations for the Hong Kong-Zhuhai-Macao Bridge.

Ma, P., Wu, Z., Zhang, Z., & Au, F. T. (2024).
Remote Sensing of Environment, 302: 113962.
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[6]

Sequential image registration algorithm based on the PrePS points association for GNSS-based InBSAR systems.

Wang, Z., Wu, Z., Yang, T., & Ma, P. (2024).
IEEE Transactions on Geoscience and Remote Sensing, 62: 5226012.
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[7]

A context-structural feature decoupling change detection network for detecting earthquake-triggered damage.

Zheng, Z., Ma, P., & Wu, Z. (2024).
International Journal of Applied Earth Observation and Geoinformation, 131: 103961.
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[8]

Robust time-series InSAR deformation monitoring by integrating variational mode decomposition and gated recurrent units.

Ma, P., Jiao, Z., & Wu, Z. (2024).
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
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[9]

Automated surface melt detection over the Antarctic from Sentinel-1 imagery using deep learning.

Zhu, Q., Guo, H., Zhang, L., Liang, D., Wu, Z., de Roda Husman, S., & Du, X. (2024).
International Journal of Applied Earth Observation and Geoinformation, 130: 103895.
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[10]

Investigating the dynamics and interactions of surface features on Pine Island Glacier using remote sensing and deep learning

Zhu, Q., Guo, H., Zhang, L., Liang, D., Wu, Z., Lyu, Z., & Du, X. (2024).
Advances in Climate Change Research.
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[11]

Mining-Related Subsidence Measurements Using a Robust Multi-Temporal InSAR Method and Logistic Model.

Ma, P., Yu, C., Wu, Z., Wang, Z., & Chen, J. (2024).
IEEE Journal on Miniaturization for Air and Space Systems.
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[12]

Automatic detection and classification of land subsidence in deltaic metropolitan areas using distributed scatterer InSAR and Oriented R-CNN.

Wu, Z., Ma, P., Zheng, Y., Gu, F., Liu, L., & Lin, H. (2023).
Remote Sensing of Environment, 290: 113545.
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[ESI Highly Cited Paper]
[13]

Understanding spatially non-stationary effects of natural and human-induced factors on land subsidence based on InSAR and multi-source geospatial data: A case study in the Guangdong-Hong Kong-Macao Greater Bay Area.

Wu, Z., Zhang, X., Cai, J., Ma, P., & Kwan, M.-P. (2023).
International Journal of Digital Earth, 16(2): 4404-4427.
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[14]

How did urban environmental characteristics influence land surface temperature in Hong Kong from 2017 to 2022? Evidence from remote sensing and land use data.

Wu, Z., Zhang, X., Ma, P., Kwan, M.-P, & Liu, Y. (2023).
Sustainability, 15(21):15511.
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[15]

Deep learning of InSAR time-series signals for assessing the impacts of geotechnical, meteorological, and marine conditions on cross-sea bridge deformations.

Wu, Z., & Ma, P. (2023).
American Geophysical Union (AGU) Fall Meeting 2023, San Francisco, United States, 11-15 December 2023.
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[16]

GLA-STDeepLab: SAR enhancing glacier and ice shelf fronts detection using Swin-TransDeepLab with Global-Local attention.

Zhu, Q., Guo, H., Zhang, L., Liang, D., Wu, Z., & Gou, Y. (2023).
IEEE Transactions on Geoscience and Remote Sensing, 61: 1-13.
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[17]

Building risk monitoring and prediction using integrated multi-temporal InSAR and numerical modeling techniques.

Ma, P., Zheng, Y., Zhang, Z., Wu, Z., & Yu, C. (2022).
International Journal of Applied Earth Observation and Geoinformation, 114: 103076.
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[18]

Visualizing and quantifying the spatiotemporal expansion of the Blue Lentic Belt in Alabama and Mississippi.

Liu, Y., Kwan, M.-P., & Wu, Z. (2022).
Water Research, 217: 118444.
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[19]

Real-world DEM super-resolution based on generative adversarial networks for improving InSAR topographic phase simulation.

Wu, Z., Zhao, Z., Ma, P., & Huang, B. (2021).
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14: 8373-8385.
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[20]

Automatic detection of widely distributed local-scale subsidence bowls in rapidly urbanizing metropolitan region using time-series InSAR and deep learning methods.

Wu, Z., Zhao, Z., Zheng, Y., & Ma, P. (2021).
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, 11-16 July 2021.
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[21]

Recurrent neural networks for atmospheric noise removal from InSAR time series with missing values.

Zhao, Z., Wu, Z., Zheng, Y., & Ma, P. (2021).
ISPRS Journal of Photogrammetry and Remote Sensing, 180: 227-237.
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[22]

ESRGAN-based DEM super-resolution for enhanced slope deformation monitoring in Lantau island of Hong Kong.

Wu, Z., & Ma, P. (2020).
International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, 351-356, Nice, France, 14–20 June 2020.
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