Publication List

Google Scholar: https://scholar.google.com/citations?user=SlXpfWMAAAAJ

International Journal Papers

(* corresponding author, # co-first author)

  1. Weng, Q., Li, Z., Cao, Y., Lu, X., Gamba, P., Zhu, X., Xu, Y., Zhang, F., Qin, R., Yang, M. and Ma, P., 2024. How will AI transform urban observing, sensing, imaging, and mapping? npj Urban Sustainability, 4(1), 1-9. [HTML] [PDF]

  2. Li, Z., Xu, S. and Weng, Q., 2024. Beyond clouds: Seamless flood mapping using Harmonized Landsat and Sentinel-2 time series imagery and water occurrence data. ISPRS Journal of Photogrammetry and Remote Sensing, 216, 185-199. [HTML] [PDF] [Code] (Featured in ’Select Landsat Publications’ by NASA Landsat Science⭐)

  3. Li, J., Hu, C., Sheng, Q., Wang, B., Ling, X., Gao, F., Xu, Y., Li, Z. and Molinier, M., 2024. A Unified Cloud Detection Method for Suomi-NPP VIIRS Day and Night PAN Imagery. IEEE Transactions on Geoscience and Remote Sensing, 62, 4106913. [HTML] [PDF]

  4. Li, Z., Weng, Q., Zhou, Y., Dou, P. and Ding, X., 2024. Learning spectral-indices-fused deep models for time-series land use and land cover mapping in cloud-prone areas: The case of Pearl River Delta. Remote Sensing of Environment, 308, 114190. [HTML] [PDF]

  5. Dou, P., Shen, H., Huang, C., Li, Z., Mao, Y. and Li, X., 2024. Large-scale land use/land cover extraction from Landsat imagery using feature relationships matrix based deep-shallow learning. International Journal of Applied Earth Observation and Geoinformation, 129, 103866. [HTML] [PDF]

  6. Dong, J., Zhang, T., Wang, L., Li, Z., Wong, M.S., Bilal, M., Zhu, Z., Mao, F., Xia, X., Han, G., Xu, Q., Gu, Y., Lin, Y., Zhao, B., Li, Z., Xu, K., Chen, X. and Gong, W., 2024. First retrieval of daily 160 m aerosol optical depth over urban areas using Gaofen-1/6 synergistic observations: Algorithm development and validation. ISPRS Journal of Photogrammetry and Remote Sensing, 211, 372-391. [HTML] [PDF]

  7. Zhu, S., Li, Z. and Shen, H., 2024. Transferring Deep Models for Cloud Detection in Multisensor Images via Weakly Supervised Learning. IEEE Transactions on Geoscience and Remote Sensing, 62, 5609518. [HTML] [PDF] [Dataset]

  8. Jiang, B., Xu, S. and Li, Z., 2023. Polyline simplification using a region proposal network integrating raster and vector features. GIScience & Remote Sensing, 60(1), 2275427. [HTML] [PDF]

  9. Zhu, S., Li, Z., Shen, H. and Lin, D., 2023. A fast two-step algorithm for large-area thick cloud removal in high-resolution images. Remote Sensing Letters, 14(1), 1-9. [HTML] [PDF]

  10. Li, Z., Shen, H., Weng, Q., Zhang, Y., Dou, P. and Zhang, L., 2022. Cloud and cloud shadow detection for optical satellite imagery: Features, algorithms, validation, and prospects. ISPRS Journal of Photogrammetry and Remote Sensing, 188, pp.89-108. [HTML] [PDF] [Project] (ESI Highly Cited Paper🏆)

  11. Dou, P., Shen, H., Li, Z*. and Guan, X., 2021. Time series remote sensing image classification framework using combination of deep learning and multiple classifiers system. International Journal of Applied Earth Observation and Geoinformation, 103, 102477. [HTML] [PDF]

  12. Zhang, Q., Yuan, Q., Li, Z*, Sun, F. and Zhang, L., 2021. Combined deep prior with low-rank tensor SVD for thick cloud removal in multitemporal images. ISPRS Journal of Photogrammetry and Remote Sensing, 177, 161-173. [HTML] [PDF] [Dataset]

  13. Dou, P., Shen, H., Li, Z.*, Guan, X. and Huang, W., 2021. Remote Sensing Image Classification Using Deep–Shallow Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 3070-3083. [HTML] [PDF]

  14. Yuan, Q., Shen, H., Li, T., Li, Z., Li, S., Jiang, Y., Xu, H., Tan, W., Yang, Q., Wang, J. and Gao, J., 2020. Deep learning in environmental remote sensing: Achievements and challenges. Remote Sensing of Environment, 241, 111716. [HTML] [PDF] (ESI Highly Cited Paper🏆 2020年中国百篇最具影响国际学术论文🏆)

  15. Zhang, Q., Yuan, Q., Li, J., Li, Z., Shen, H. and Zhang, L., 2020. Thick cloud and cloud shadow removal in multitemporal imagery using progressively spatio-temporal patch group deep learning. ISPRS Journal of Photogrammetry and Remote Sensing, 162, 148-160. [HTML] [PDF] [Code] [Dataset]

  16. Wang, Y., Li, Z., Zeng, C., Xia, G.S. and Shen, H., 2020. An Urban Water Extraction Method Combining Deep Learning and Google Earth Engine. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 769-782. [HTML] [PDF] [Code] [Dataset]

  17. Li, X.#, Li, Z.#, Feng, R., Luo, S., Zhang, C., Jiang, M. and Shen, H., 2020. Generating high-quality and high-resolution seamless satellite imagery for large-scale urban regions. Remote Sensing, 12(1), 81. [HTML] [PDF]

  18. Li, Z., Shen, H., Cheng, Q., Li, W. and Zhang, L., 2019. Thick cloud removal in high-resolution satellite images using stepwise radiometric adjustment and residual correction. Remote Sensing, 11(16), 1925. [HTML] [PDF]

  19. Li, Z., Shen, H., Cheng, Q., Liu, Y., You, S. and He, Z., 2019. Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors. ISPRS Journal of Photogrammetry and Remote Sensing, 150, 197-212. [HTML] [PDF] [Project] [Dataset] (ESI Highly Cited Paper🏆)

  20. Shen, H., Wu, J., Cheng, Q., Aihemaiti, M., Zhang, C. and Li, Z., 2019. A Spatiotemporal Fusion Based Cloud Removal Method for Remote Sensing Images With Land Cover Changes. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(3), 862-874. [HTML] [PDF]

  21. Zhang, T., Zhu, Z., Gong, W., Zhu, Z., Sun, K., Wang, L., Huang, Y., Mao, F., Shen, H., Li, Z. and Xu, K., 2018. Estimation of ultrahigh resolution PM2. 5 concentrations in urban areas using 160 m Gaofen-1 AOD retrievals. Remote Sensing of Environment, 216, 91-104. [HTML] [PDF]

  22. Li, Z., Shen, H., Li, H., Xia, G., Gamba, P. and Zhang, L., 2017. Multi-feature combined cloud and cloud shadow detection in GaoFen-1 wide field of view imagery. Remote Sensing of Environment, 191, 342-358. [HTML] [PDF] [Project] [Dataset] (ESI Highly Cited Paper🏆)


Book Chapter

  • Li, Z., Yoo, C. and Weng, Q., 2024. Urban Flooding Monitoring and Management in Geospatial Perspective: Data, Techniques, and Platforms. In Handbook of Geospatial Approaches to Sustainable Cities (pp. 44-57). CRC Press. [HTML]


Conference Papers

  • Li, Z., Xu, S., Weng, Q., 2024. Can we reconstruct cloud-covered flooding areas in harmonized Landsat and Sentinel-2 image time series?, IEEE International Geoscience and Remote Sensing Symposium (IGARSS). pp. 3686–3688, Athens, Greece.

  • Li, Z., Shen, H., Wei, Y., Cheng, Q., Yuan, Q., 2018. Cloud detection by fusing multi-scale convolutional features, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. pp. 149–152, Beijing, China.

  • Zhang, C., Li, Z., Cheng, Q., Li, X., Shen, H., 2017. Cloud removal by fusing multi-source and multi-temporal images, IEEE International Geoscience and Remote Sensing Symposium (IGARSS). pp. 2577–2580, Texas, USA.

  • Li, Z., Shen, H., Li, H., Zhang, L., 2016. Automatic cloud and cloud shadow detection in GF-1 WFV imagery using multiple features, IEEE International Geoscience and Remote Sensing Symposium (IGARSS). pp. 7612–7615, Beijing, China.