Publication List

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

International Journal Papers

(* corresponding author, # co-first author)

  • 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]

  • 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⭐)

  • 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]

  • 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]

  • 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]

  • 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]

  • 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]

  • 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]

  • 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]

  • 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🏆)

  • 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]

  • 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]

  • 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]

  • 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🏆)

  • 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]

  • 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]

  • 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]

  • 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]

  • 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🏆)

  • 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]

  • 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]

  • 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.


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.