个人简介
李慧芳，女，教授，博导，太阳成集团tyc7111cc。主要研究方向为城市遥感信息处理与应用，针对大气衰减和复杂地表导致的卫星和航空影像中的严重辐射畸变问题，以机理、变分、统计、深度学习等模型为基础，开展多模型融合的计算校正理论方法研究，开展城市温度多尺度遥感监测与分析，取得了系列创新性成果。主持国家自然科学基金3项，国家重点研发项目课题/子课题3项，省部级及其他项目10余项，发表学术论文50余篇，其中RSE、ISPRS P&RS、IEEE TGRS等地学顶级期刊论文17篇，论文总被引1500多次（Google scholar）；出版《遥感数据质量改善之信息校正》专著一部；获得美国摄影测量与遥感协会(ASPRS)授予的ERDAS最佳遥感科学论文奖；获得测绘科技进步一等奖。
欢迎有兴趣的研究生、本科生联系并加入我们的研究团队！（长期有效）
研究生招收专业：
资源环境监测与规划（硕博）、土地资源管理、自然地理（硕博）、人文地理、测绘工程（专硕）
科研项目
国家重点研发计划课题，城市典型生态环境问题时空特征与演变规律，2022.9-2026.8，主持
国家重点研发计划子课题，多源融合与异构同化的生态环境参数高精度感知技术，2020.1-2022.12，主持
国家自然科学基金面上项目，城市复杂场景下的数据-模型联合驱动遥感影像阴影校正方法，2024.1-2027.12，主持
国家自然科学基金面上项目，耦合统计信息与物理机制的遥感影像云雾校正研究，2019.1-2022.12，主持
国家自然科学基金青年项目，高分辨率遥感影像的软阴影检测与高保真修复方法研究，2015.1-2017.12，主持
湖北省自然科学基金，面向城市固体废弃物的遥感信息校正与目标检测方法研究，2021.06-2023.06. 主持.
湖北省自然科学基金，感知驱动的遥感影像快速变分校正方法研究，2014.01-2015.12. 主持.
国家自然科学基金重点项目，山地典型生态参量遥感反演建模及其时空表征，2017.01-2021.12, 参与
国家重点研发计划，高光谱激光雷达理论体系建立及总体技术集成研发， 2018.05-2022.04
论文
Liu, Ye;
Li, Huifang*; Hu, Chao; Luo, Shuang; Luo, Yan; Chen, Chang Wen, " Learning to Aggregate Multi-Scale Context for Instance Segmentation in Remote Sensing Images,"
IEEE Transactions on Neural Networks and Learning Systems, 2023, ACCEPT
H. Li*, Y. Han, T. Wang, Z. Wang, Y. Li, H. Shen, Evolution of urban morphological polycentricity and the thermal response in Wuhan from 2000 to 2020,
Sustainable Cities and Society, 2023, 105055, ISSN 2210-6707,
https://doi.org/10.1016/j.scs.2023.105055. S. Luo,
H. Li*, Y. Li, C. Shao, H. Shen and L. Zhang, "An Evolutionary Shadow Correction Network and a Benchmark UAV Dataset for Remote Sensing Images,"
IEEE Trans. on Geoscience and Remote Sensing, vol. 61, pp. 1-14, 2023, Art no. 5615414,
Dataset and Code: https://github.com/UrbanRScode/ESCNet C. Zhang,
H. Li*, H. Shen, H. He, Y. Liu, P. Yi, L. Xu, "A General Thin Cloud Correction Method Combining Statistical Information and a Scattering Model for Visible and Near-infrared Satellite Images,"
IEEE Trans. on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2023.3296151.
Y. Gong,
H. Li*, H. Shen, C. Meng, P. Wu, “Cloud-covered MODIS LST reconstruction by combining assimilation data and remote sensing data through a nonlocality-reinforced network,”
International Journal of Applied Earth Observation and Geoinformation, vol. 117, no. 203195, 2023.
H. Li*; Hu, Chao; Zhong, Xinrun; Zeng, Chao; Shen, Huanfeng, “Solid waste detection in cities using remote sensing imagery based on a location-guided key point network with multiple enhancements”,
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 191-201, 2023.
C. Zhang,
H. Li*, H. Shen, A scattering law based cirrus correction method for Landsat 8 OLI visible and near-infrared images,
Remote Sensing of Environment, vol. 253, 112202, Feb. 2021.
H. Li*, Y. Li, T. Wang, Z. Wang, M. Gao, H. Shen, "Quantifying 3D Building Form Effects on Urban Land Surface Temperature and Modeling Seasonal Correlation Patterns",
Building and Environment, 2021, 204, 108132.
S. Luo,
H. Li*, H. Shen*, Deeply supervised convolutional neural network for shadow detection based on a novel aerial shadow imagery dataset,
ISPRS Journal of Photogrammetry and Remote Sensing, vol. 167, Pages 443-457, Sep. 2020.
Dataset and Code:
https://github.com/RSrscoder/AISD H. Shen, C. Zhang,
H. Li*, A Spatial-Spectral Adaptive Haze Removal Method for Visible Remote Sensing Images,
IEEE Trans. on Geoscience and Remote Sensing, vol. 58, no. 9, pp. 6168-6180, 2020.
S. Luo,
H. Li*, R. Zhu, Y. Gong, and H. Shen, ESPFNet: An Edge-aware Spatial Pyramid Fusion Network for Salient Shadow Detection in Aerial Remote Sensing Images,
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, 4633-4645, 2021.
S. Luo, H. Shen,
H. Li*, and Y. Chen, Shadow removal based on separated illumination correction for urban aerial remote sensing images,
Signal Processing, vol. 165, pp. 197-208, 2019.
Z. Li, H. Shen*,
H. Li*, G. Xia, P. Gamba, and L. Zhang, Multi-feature combined cloud and cloud shadow detection in GaoFen-1 wide field of view imagery,
Remote Sensing of Environment, vol. 191, pp. 342-358, 2017.
H. Li, L. Xu, H. Shen, L. Zhang, A general variational framework considering cast shadows for the topographic correction of remote sensing imagery,
ISPRS Journal of Photogrammetry and Remote Sensing, vol. 117, no. 7, pp. 161-171, 2016.
H. Li, X. Wang, H. Shen, L. Zhang, An efficient multi-resolution variational Retinex scheme for the radiometric correction of airborne remote sensing images,
International Journal of Remote Sensing, vol. 37, no. 5, pp. 1154-1172, 2016.
H. Li, L. Zhang, H. Shen, A Perceptually Inspired Variational Method for the Uneven Intensity Correction of Remote Sensing Images,
IEEE Trans. on Geoscience and Remote Sensing, 2012, vol. 50, no. 8, pp. 3053-3065.
H. Li, L. Zhang, H. Shen, An adaptive non-local regularized shadow removal method for aerial remote sensing images,
IEEE Trans. on Geoscience and Remote Sensing, 2014, vol. 52, no. 1, pp. 106-120.
H. Li, L. Zhang, H. Shen, A Principal Component based Haze Masking Method for Visible Images,
IEEE Geoscience and Remote Sensing Letters, 2014, vol. 11, no. 5, pp. 975-979.
H. Shen,
H. Li*, Y. Qian, L. Zhang, Q. Yuan, An effective thin cloud removal procedure for visible remote sensing images,
ISPRS Journal of Photogrammetry and Remote Sensing, 2014, vol. 96, pp. 224-235.
H. Shen, X. Li, Q. Cheng, C. Zeng, G. Yang,
H. Li, and L. Zhang, “Missing Information Reconstruction of Remote Sensing Data: A Technical Review,”
IEEE Geoscience and Remote Sensing Magazine, vol. 3, no. 3, pp. 61-85, 2015.
X. Meng, H. Shen, Q. Yuan,
H. Li, L. Zhang, and W. Sun, “Pansharpening for cloud-contaminated very high-resolution remote sensing images,”
IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 5, pp. 2840-2854, 2018.
X. Meng, H. Shen,
H. Li, L. Zhang, and R. Fu, "Review of the pansharpening methods for remote sensing images based on the idea of meta-analysis: Practical discussion and challenges,"
Information Fusion, vol. 46, pp. 102-113, 2019.
李慧芳, 沈焕锋, 张良培, 李平湘, "一种基于变分Retinex的遥感影像不均匀性校正方法,"
测绘学报, 39(6), 585-591, 2010.
王晓静, 李慧芳*, 袁强强, 沈焕锋, 张良培, "采用分裂Bregman的遥感影像亮度不均变分校正,"
中国图象图形学报,19(5), 798-805, 2014.
张弛, 李慧芳*, 沈焕锋.联合统计信息与散射模型的GF-5 AHSI可见光影像薄云校正[J].
遥感学报, 2020, 24 (04): 368-378.
发明专利
[1] 李慧芳，张弛，沈焕锋. 一种短波红外波段辅助的遥感影像薄云雾校正方法，ZL202011339970.6.
[2] 沈焕锋，罗爽，李慧芳. 一种基于深度学习的无人机遥感影像阴影去除方法，ZL202011349993.5.
[3] 李慧芳，胡超，罗爽. 沈焕锋基于多策略增强的遥感影像固体废弃物识别方法及系统，ZL202110345854.3
[4] 李慧芳，徐立颖，一种不配对遥感影像薄云雾检测及去除方法，申请号202210554878.4.
[5] 沈焕锋，李志伟，李慧芳，吴崎. 一种多特征联合的光学卫星影像云与云阴影检测方法，ZL201610018751.5.
