1.期刊论文

right-hand遥感降质信息复原（去噪与去模糊）

clip_image001H. Shen, M. Jiang, J. Li, C. Zhou, Q. Yuan, and L. Zhang, “Coupling Model- and Data-Driven Methods for Remote Sensing Image Restoration and Fusion: Improving physical interpretability,” IEEE Geoscience and Remote Sensing Magazine, vol. 10, no. 2, pp. 231-249, 2022.(PDF)

clip_image001H. Zhang, J. Cai, W. He, H. Shen, and L. Zhang, “Double Low-Rank Matrix Decomposition for Hyperspectral Image Denoising and Destriping,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-19, 2022.(PDF)

clip_image001H. Shen, C. Zhou, J. Li, & Q. Yuan, “SAR Image Despeckling Employing a Recursive Deep CNN Prior,” IEEE Transactions on Geoscience and Remote Sensing, 2020.(PDF)

clip_image001Q. Zhang, Q. Yuan, J. Li, X. Liu, H. Shen, and L. Zhang, “Hybrid Noise Removal in Hyperspectral Imagery With a Spatial–Spectral Gradient Network,” IEEE Transactions on Geoscience and Remote Sensing, vol. 57, pp. 7317-7329, 2019.(PDF)

clip_image001X. Ma, P. Wu, and H. Shen, “Multifrequency Polarimetric SAR Image Despeckling by Iterative Nonlocal Means Based on a Space-Frequency Information Joint Covariance Matrix,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 1, pp. 274-284, 2019.(PDF)

clip_image001X. Ma, P. Wu, and H. Shen, “A Nonlinear Guided Filter for Polarimetric SAR Image Despeckling,” IEEE Transactions on Geoscience and Remote Sensing, 2018. DOI: 10.1109/TGRS.2018.2870188(PDF)

clip_image001W. He, H. Zhang, H. Shen, and L. Zhang, “Hyperspectral Image Denoising Using Local Low-Rank Matrix Recovery and Global Spatial-Spectral Total Variation,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 3, pp. 713-729, 2018.(PDF)

clip_image001X. Ma, P. Wu, Y. Wu, and H. Shen, “A Review on Recent Developments in Fully Polarimetric SAR Image Despeckling,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 3, pp. 743-758, 2017.(PDF)

clip_image001X. Liu, H. Shen, Q. Yuan, X. Lu, and C. Zhou, “A Universal Destriping Framework Combining 1-D and 2-D Variational Optimization Methods,” IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 2, pp. 808-822, 2017.(PDF)

clip_image001J. Li, Q. Yuan, H. Shen, and L. Zhang, “Noise Removal From Hyperspectral Image With Joint Spectral-Spatial Distributed Sparse Representation,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 9, pp. 5425-5439, 2016.(PDF)

clip_image001X. Ma, H. Shen, X. Zhao, and L. Zhang, “SAR Image Despeckling by the Use of Variational Methods With Adaptive Nonlocal Functionals,” IEEE Transactions on Geoscience and Remote Sensing,, vol. 54, no. 6, pp. 3421-3435, 2016.(PDF)

clip_image001C. Jiang, H. Zhang, L. Zhang, H. Shen, and Q. Yuan, “Hyperspectral Image Denoising with a Combined Spatial and Spectral Weighted Hyperspectral Total Variation Model,” Canadian Journal of Remote Sensing, vol. 42, no. 1, pp. 53-72, 2016.(PDF)

clip_image001X. Liu, X. Lu, H. Shen, Q. Yuan, Y. Jiao, L. Zhang, “Stripe Noise Separation and Removal in Remote Sensing Images by Consideration of the Global Sparsity and Local Variational Properties,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 5, pp. 3049-3060, 2016.(PDF)

clip_image001W. He, H. Zhang, L. Zhang, and H. Shen, “Hyperspectral Image Denoising via Noise-Adjusted Iterative Low-Rank Matrix Approximation,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 6, pp. 3050-3061, 2015.(PDF)

clip_image001W. He, H. Zhang, L. Zhang, and H. Shen, “Total Variation Regularized Low-rank Matrix Factorization for Hyperspectral Image Restoration,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 1, pp. 178-188, 2016.(PDF)

clip_image001J. Li, Q. Yuan, H. Shen, and L. Zhang, “Hyperspectral Image Recovery Employing a Multidimensional Nonlocal Total Variation Model,” Signal Processing, vol. 111, pp. 230-248, 2015.(PDF)

clip_image001G. Yang, H. Shen, L. Zhang, Z. He, and X. Li, “A Moving Weighted Harmonic Analysis Method for Reconstructing High-Quality SPOT VEGETATION NDVI Time-Series Data,” IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 11, pp. 6008-6021, 2015.(PDF)

clip_image001X. Ma, H. Shen, L. Zhang, J. Yang, H. Zhang, “Adaptive Anisotropic Diffusion Method for Polarimetric SAR Speckle Filtering,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 3, pp. 1041-1050, 2015.(PDF)

clip_image001[5] H. Shen, W. Jiang, H. Zhang, L. Zhang, “A piece-wise approach to remove the nonlinear and irregular stripes in MODIS data,” International Journal of Remote Sensing, vol. 35, no. 1, pp. 44-53, 2014.(PDF)

clip_image001H. Zhang, W. He, L. Zhang, H. Shen, Q. Yuan, “Hyperspectral Image Restoration Using Low-Rank Matrix Recovery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 8, pp. 4729-4743, 2014.(PDF)

clip_image001Q. Yuan, L. Zhang, H. Shen, “Hyperspectral Image Denoising With a Spatial-Spectral View Fusion Strategy,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 5, pp. 2314-2325, 2014.(PDF)

clip_image001H. Shen, W. Zhao, Q. Yuan, L. Zhang, “Blind Restoration of Remote Sensing Images by a Combination of Automatic Knife-Edge Detection and Alternating Minimization,” Remote Sensing, vol. 6, no. 8, pp. 7491-7521, 2014.(PDF)

clip_image001X. Lan, L. Zhang, H. Shen, Q. Yuan, “Single Image Haze Removal Considering Sensor Blur and Noise,” EURASIP Journal on Advances in Signal Processing, vol. 2013, no. 1, pp. 1-13, 2013.(PDF)

clip_image001Q. Yuan, L. Zhang, and H. Shen, “Hyperspectral Image Denoising Employing a Spectral-spatial Adaptive Total Variation Model,” IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 10, pp. 3660-3677, 2012.(PDF)

clip_image001H. Shen, L. Du, L. Zhang, and W. Gong, “A Blind Restoration Method for Remote Sensing Images,” IEEE Geoscience and Remote Sensing Letters, vol. 9, no. 6, pp. 1137-1141, 2012.(PDF)

clip_image001Y. Wang, R. Niu, X. Yu, and H. Shen, “Image Restoration and Enhancement Based on Tunable Forward-and-Backward Diffusion,” Optical Engineering, vol. 49, no. 5, pp. 057004(1-20), 2010.(PDF)

clip_image001Y. Wang, R. Niu, L. Zhang, and H. Shen, “Region-based Adaptive Anisotropic Diffusion for Image Enhancement and Denoising,” Optical Engineering, vol. 49, no. 11, pp. 117007(1-19), 2010.(PDF)

clip_image001[5] H. Shen, L. Zhang, “A MAP-Based Algorithm for Destriping and Inpainting of Remotely Sensed Images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 47, no. 5, pp. 1492-1502, 2009.(PDF)

clip_image001兰霞, 刘欣鑫, 沈焕锋, 袁强强, 张良培, “一种消除高密度椒盐噪声的迭代中值滤波算法,” 武汉大学学报（信息科学版）, vol. 42, no. 12, pp. 1731-1737, 2017.

clip_image001马晓双, 沈焕锋, 杨杰, 张良培, “极化SAR相干斑抑制的局部加权最小均方差滤波算法,” 中国图象图形学报, vol. 20, no. 1, pp. 140-150, 2015.

clip_image001姜湾, 沈焕锋, 曾超, 张良培, 张洪艳, 刘欣鑫, “Terra MODIS数据28波段影像条带噪声去除方法,” 武汉大学学报（信息科学版）, vol. 39, no. 5, pp. 326-330, 2014.

clip_image001徐源璟, 汪俏珏, 沈焕锋, 李平湘, 张洪艳, “基于刃边法与正则化方法的遥感影像复原,” 测绘信息与工程, vol. 35, no. 6, pp. 7-9, 2010.

clip_image001王毅, 牛瑞卿, 喻鑫, 沈焕锋, “基于时间变化的鲁棒各向异性扩散模型,” 自动化学报, vol. 35, no. 9, pp. 1253-1256, 2009.

right-hand遥感差异信息校正

clip_image001X. Zhang, R. Feng, X. Li, H. Shen, and Z. Yuan, “Block Adjustment-Based Radiometric Normalization by Considering Global and Local Differences,” IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022.(PDF)

clip_image001J. Li, H. Shen, H. Li, M. Jiang, and Q. Yuan, “Radiometric quality improvement of hyperspectral remote sensing images: a technical tutorial on variational framework,” Journal of Applied Remote Sensing, vol. 15, no. 3, pp. 1-33, 2021.(PDF)

clip_image001R. Feng, H. Shen, J. Bai, and X. Li, “Advances and Opportunities in Remote Sensing Image Geometric Registration: A systematic review of state-of-the-art approaches and future research directions,” IEEE Geoscience and Remote Sensing Magazine, vol. 9, no. 4, pp. 120-142, 2021.(PDF)

clip_image001R. Feng, Q. Du, H. Shen, and X. Li, “Region-by-Region Registration Combining Feature-Based and Optical Flow Methods for Remote Sensing Images,” Remote Sensing, vol. 13, no. 8, p. 1475, 2021.(PDF)

clip_image001C. Zhang, H. Li, and H. Shen, “A scattering law based cirrus correction method for Landsat 8 OLI visible and near-infrared images,” Remote Sensing of Environment, vol. 253, pp. 112202, 2021.(PDF)

clip_image001X. Xu, X. Li, X. Liu, H. Shen, and Q. Shi, “Multimodal registration of remotely sensed images based on Jeffrey’s divergence,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 122, pp. 97-115, 2016.(PDF)

clip_image001H. Li, L. Xu, H. Shen, and 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.(PDF)

clip_image001H. Li, X. Wang, H. Shen, Q. Yuan, and 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.(PDF)

clip_image001X. Lan, Z. Zuo, H. Shen, L. Zhang, and J. Hu, “Framelet-based sparse regularization for uneven intensity correction of remote sensing images in a retinex variational framework,” Optik – International Journal for Light and Electron Optics, vol. 127, no. 3, pp. 1184-1189, 2016.(PDF)

clip_image001X. Li, N. Hui, H. Shen, Y. Fu, and L. Zhang, “A robust mosaicking procedure for high spatial resolution remote sensing images,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 109, pp. 108-125, 2015.(PDF)

clip_image001W. Gan, H. Shen, L. Zhang, W. Gong, “Normalization of medium-resolution NDVI by the use of coarser reference data: method and evaluation,” International Journal of Remote Sensing, vol. 35, no. 21, pp. 7400-7429, 2014.(PDF)

clip_image001X. Lan, H. Shen, L. Zhang, and Q. Yuan, “A spatially adaptive retinex variational model for the uneven intensity correction of remote sensing images,” Signal Processing, vol. 101, pp. 19-34, 2014.(PDF)

clip_image001T. Hu, H. Zhang, H. Shen, L. Zhang, “Robust Registration by Rank Minimization for Multiangle Hyper/Multispectral Remotely Sensed Imagery,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2443-2457, 2014.(PDF)

clip_image001H. 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, vol. 96, pp. 224-235, 2014.(PDF)

clip_image001H. Li, L. Zhang, H. Shen, “A Principal Component Based Haze Masking Method for Visible Images,” IEEE Geoscience and Remote Sensing Letters, vol. 11, no. 5, pp. 975-979, 2014.(PDF)

clip_image001H. Li, L. Zhang, H. Shen, ” An Adaptive Nonlocal Regularized Shadow Removal Method for Aerial Remote Sensing Images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 1, pp. 106-120, 2014.(PDF)

clip_image001H. Li, L. Zhang, H. Shen, and P. Li, “A Perceptually Inspired Variational Method for Uneven Intensity Correction of Remote Sensing Images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 8, pp. 3053-3065, 2012.(PDF)

clip_image001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, vol. 19, no. 5, pp. 798-805, 2014.

clip_image001李洪利, 沈焕锋, 杜博, 吴柯, “一种高保真同态滤波遥感影像薄云去除方法,” 遥感应用, vol. 2011, no.1, pp. 41-44, 2011.

clip_image001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, vol. 9, no. 6, pp. 585-591, 2010.

right-hand遥感缺失信息重建

clip_image001S. Zhu, Z. Li, H. Shen, and D. Lin, “A fast two-step algorithm for large-area thick cloud removal in high-resolution images,” Remote Sensing Letters,vol. 14, no. 1, pp. 1-9, 2023/01/02, 2023.(PDF)

clip_image001X. Liu, H. Shen, Q. Yuan, X. Lu, and S. Li, “One-Step High-Quality NDVI Time-Series Reconstruction by Joint Modeling of Gradual Vegetation Change and Negatively Biased Atmospheric Contamination,” IEEE Transactions on Geoscience and Remote Sensing,vol. 60, pp. 1-17, 2022.(PDF)

clip_image001H. Shen, Y. Wang, X. Guan, W. Huang, J. Chen, D. Lin, and W. Gan, “A Spatiotemporal Constrained Machine Learning Method for OCO-2 Solar-Induced Chlorophyll Fluorescence (SIF) Reconstruction,” IEEE Transactions on Geoscience and Remote Sensing,vol. 60, pp. 1-17, 2022.(PDF)

clip_image001L. Yue, F. Zan, X. Liu, Q. Yuan, and H. Shen, “The Spatio-temporal Reconstruction of Lake Water Levels Using Deep Learning Models: A Case Study on Altai Mountains,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,pp. 1-21, 2022.(PDF)

clip_image001D. Chu, H. Shen, X. Guan, J. Chen, X. Li, J. Li, L. Zhang, “Long time-series NDVI reconstruction in cloud-prone regions via spatio-temporal tensor completion,” Remote Sensing of Environment,264, 112632, 2021.(PDF)

clip_image001Q. Zhang, Q. Yuan, J. Li, Z. Li, H. Shen, and L. Zhang, “Thick cloud and cloud shadow removal in multitemporal imagery using progressively spatio-temporal patch group deep learning,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 162, pp. 148-160, 2020.(PDF)

clip_image001H. Shen, C. Zhang, H. Li, Q. Yuan, & L. Zhang, “A Spatial-Spectral Adaptive Haze Removal Method for Visible Remote Sensing Images,” IEEE Transactions on Geoscience and Remote Sensing, 2020.(PDF)

clip_image001Z. Li, H. Shen, Q. Cheng, W. Li, and L. Zhang, “Thick Cloud Removal in High Resolution Satellite Images Using Stepwise Radiometric Adjustment and Residual Correction,” Remote Sensing, vol. 11, 2019.(PDF)

clip_image001S. 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.(PDF)

clip_image001X. Li, Y. Jing, H. Shen, L. Zhang, “The recent developments in cloud removal approaches of MODIS snow cover product,” Hydrology and Earth System Sciences, vol. 23, pp. 2401-2416, 2019.(PDF)

clip_image001C. Zeng, D. Long, H. Shen, P. Wu, Y. Cui, and Y. Hong, “A two-step framework for reconstructing remotely sensed land surface temperatures contaminated by cloud,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 141, pp. 30-45, 2018.(PDF)

clip_image001G. Yang, H. Shen, W. Sun, J. Li, N. Diao, and Z. He, “On the Generation of Gapless and Seamless Daily Surface Reflectance Data,” IEEE Transactions on Geoscience and Remote Sensing, vol. 99, pp. 1-18, 2018.(PDF)

clip_image001Q. Cheng, H. Shen, L. Zhang, and Z. Peng, “Missing Information Reconstruction for Single Remote Sensing Images Using Structure-Preserving Global Optimization,” IEEE Signal Processing Letters, vol. 24, no. 8, 2017.(PDF)

clip_image001T. Zhang, C. Zeng, W. Gong, L. Wang, K. Sun, and H. Shen, “Improving Spatial Coverage for Aqua MODIS AOD using NDVI-Based Multi-Temporal Regression Analysis,” Remote Sensing, vol. 9, pp. 340, 2017.(PDF)

clip_image001X. Li, H. Shen, H. Li, and L. Zhang, “Patch Matching-Based Multitemporal Group Sparse Representation for the Missing Information Reconstruction of Remote-Sensing Images,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, pp. 3629-3641, 2016.(PDF)

clip_image001H. 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.(PDF)

clip_image001C. Zeng, H. Shen, M. Zhong, L. Zhang, P. Wu, “Reconstructing MODIS LST Based on Multitemporal Classification and Robust Regression,” IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 3, pp. 512-516, 2015.(PDF)

clip_image001X. Li, H. Shen, L. Zhang, and H. Li, “Sparse-based reconstruction of missing information in remote sensing images from spectral/temporal complementary information,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 106, pp. 1-15, 2015.(PDF)

clip_image001Q. Cheng, H. Shen, L. Zhang, P. Li, “Inpainting for Remotely Sensed Images with a Multichannel Nonlocal Total Variation Model,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 1, pp. 175-187, 2014.(PDF)

clip_image001X. Li, H. Shen, L. Zhang, H. Zhang, Q. Yuan, and G. Yang, “Recovering Quantitative Remote Sensing Products Contaminated by Thick Clouds and Shadows Using Multitemporal Dictionary Learning,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 11, pp. 7086-7098, 2014.(PDF)

clip_image001X. Li, H. Shen, L. Zhang, H. Zhang, Q. Yuan, ” Dead Pixel Completion of Aqua MODIS Band 6 using a Robust M-Estimator Multi-Regression”, IEEE Geoscience and Remote Sensing Letters, vol. 11, no. 4, pp. 768-772, 2014.(PDF)

clip_image001H. Shen, X. Li, L. Zhang, D. Tao, C. Zeng, “Compressed Sensing-Based Inpainting of Aqua Moderate Resolution Imaging Spectroradiometer Band 6 Using Adaptive Spectrum-Weighted Sparse Bayesian Dictionary Learning,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 2, pp. 894-906, 2014.(PDF)

clip_image001Q. Cheng, H. Shen, L. Zhang, Q. Yuan, C. Zeng, “Cloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal MRF model,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 92, pp. 54-68, 2014.(PDF)

clip_image001C. Zeng, H. Shen, L. Zhang, “Recovering missing pixels for Landsat ETM+ SLC-off imagery using multi-temporal regression analysis and a regularization method,” Remote Sensing of Environment, vol. 131, pp. 182-194, 2013.(PDF)

clip_image001H. Shen, C. Zeng, and L. Zhang, ” Recovering Reflectance of AQUA MODIS Band 6 Based on Within-Class Local Fitting,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 4, no. 1, pp. 185-192, 2011.(PDF)

clip_image001H. Shen, Y. Liu, T. Ai, Y. Wang, B. Wu, “Universal Reconstruction Method for Radiometric Quality Improvement of Remote Sensing Images,” International Journal of Applied Earth Observation and Geoinformation, vol. 12, no. 4, pp. 278-286, 2010.(PDF)

clip_image001 彭晓琳, 沈焕锋, 曾超, 张良培, 何宗宜, “一种Aura卫星遥感臭氧产品的修复方法,” 武汉大学学报（信息科学版）, vol. 42, no. 6, pp. 789-796, 2017.

clip_image001 刘紫涵, 吴鹏海, 吴艳兰, 沈焕锋, 曾超, “风云静止卫星地表温度产品空值数据稳健修复,” 遥感学报, vol. 21, no. 1, pp. 40-51, 2017.

clip_image001 付文轩, 沈焕锋, 李星华, 黄春林, 曾超,侯金亮, “时空自适应加权的MODIS积雪产品去云方法,” 遥感信息, vol. 31, no. 2, pp. 36-43, 2016.

right-hand多视融合（超分辨率重建）

clip_image001Y. Xiao, X. Su, Q. Yuan, D. Liu, H. Shen, and L. Zhang, “Satellite Video Super-Resolution via Multiscale Deformable Convolution Alignment and Temporal Grouping Projection,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-19, 2022.(PDF)

clip_image001J. He, J. Li, Q. Yuan, H. Shen, and L. Zhang, “Spectral Response Function-Guided Deep Optimization-Driven Network for Spectral Super-Resolution,” IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 9, pp. 4213-4227, 2022.(PDF)

clip_image001H. Shen, Z. Qiu, L. Yue, and L. Zhang, “Deep-Learning-Based Super-Resolution of Video Satellite Imagery by the Coupling of Multiframe and Single-Frame Models,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-14, 2022.(PDF)

clip_image001H. Shen, L. Lin, J. Li, Q. Yuan, and L. Zhao, “A residual convolutional neural network for polarimetric SAR image super-resolution,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 161, pp. 90-108, 2020.(PDF)

clip_image001J. Li, Q. Yuan, H. Shen, X. Meng, and L. Zhang, “Hyperspectral Image Super-Resolution by Spectral Mixture Analysis and Spatial-Spectral Group Sparsity,” IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 9, pp. 1250-1254, 2016.(PDF)

clip_image001L. Yue, H. Shen, J. Li, Q. Yuan, H. Zhang, and L. Zhang, “Image super-resolution: The techniques, applications, and future,” Signal Processing, vol. 128, pp. 389-408, 2016.(PDF)

clip_image001H. Shen, L. Peng, L. Yue, Q. Yuan, and L. Zhang, “Adaptive Norm Selection for Regularized Image Restoration and Super-Resolution,” IEEE Transactions on Cybernetics, vol. 46, no. 6, pp. 1388-1399, 2016.(PDF)

clip_image001H. Zhang, L. Zhang, and H. Shen, “A Blind Super-Resolution Reconstruction Method Considering Image Registration Errors,” International Journal of Fuzzy Systems, vol. 17, no. 2, pp. 353-364, 2015.(PDF)

clip_image001L. Yue, H. Shen, Q. Yuan, L. Zhang, “A locally adaptive L1-L2 norm for multi-frame super-resolution of images with mixed noise and outliers,” Signal Processing, vol. 105, pp. 156-174, 2014.(PDF)

clip_image001H. Zhang, Z. Yang, L. Zhang, and H. Shen, “Super-Resolution Reconstruction for Multi-Angle Remote Sensing Images Considering Resolution Differences,” Remote Sensing, vol. 6, no. 1, pp. 637-657, 2014.(PDF)

clip_image001Q. Yuan, L. Zhang, H. Shen, “Regional Spatially Adaptive Total Variation Super-resolution with Spatial Information Filtering and Clustering,” IEEE Transactions on Image Processing, vol. 22, no. 6, pp. 2327-2342, 2013.(PDF)

clip_image001Q. Yuan, L. Zhang, and H. Shen, “Multiframe Super-Resolution Employing a Spatially Weighted Total Variation Model,” IEEE Transactions On Circuits And Systems For Video Technology, vol. 22, no. 3, pp. 379-392, 2012.(PDF)

clip_image001H. Zhang, L. Zhang, H. Shen, “A Super-resolution Reconstruction Algorithm for Hyperspectral Images,” Signal Processing, vol. 92, no. 9, pp. 2082-2096, 2012.(PDF)

clip_image001L. Zhang, Q. Yuan, H. Shen, and P. Li, “Multiframe Image Super-resolution Adapted with Local Spatial Information,” Journal of the Optical Society of America A, vol. 28, no. 3, pp. 381-390, 2011.(PDF)

clip_image001Q. Yuan, L. Zhang, H. Shen, P. Li, “Adaptive Multiple-Frame Image Super-resolution Based on U-curve,” IEEE Transactions on Image Processing, vol. 19, no. 12, pp. 3157-3170, 2010.(PDF)

clip_image001L. Zhang, H. Zhang, H. Shen, and P. Li, “A Super-resolution Reconstruction Algorithm for Surveillance Images,” Signal Processing, vol. 90, no.3, pp. 848-859, 2010.(PDF)

clip_image001H. Shen, M. K. Ng, P. Li, L. Zhang, “Super Resolution Reconstruction Algorithm to MODIS Remote Sensing Images,” The Computer Journal, vol. 52, no. 1, pp. 90-100, 2009.(PDF)

clip_image001H. Shen, L. Zhang, B. Huang, P. Li, “A MAP Approach for Joint Motion Estimation, Segmentation, and Super Resolution,” IEEE Transactions on Image Processing, vol. 16, no. 2, pp. 479-490, 2007.(PDF)

clip_image001M. K. Ng, H. Shen, L. Zhang, E. Lam, “A Total Variation regularization Based Super-Resolution Reconstruction Algorithm for Digital Video,” EURASIP Journal on Advances in Signal Processing, vol. 2007, no. Article ID 74585, pp.1-16, 2007.(PDF)

clip_image001M. K. Ng, H. Shen, S. Chaudhuri, A. C. Yau, “Zoom-based super-resolution reconstruction approach using prior total variation,” Optical Engineering, vol. 46, no. 12, pp. 127003(1-11), 2007.(PDF)

clip_image001孙京, 袁强强, 李冀玮, 周春平, 沈焕锋, “亮度——梯度联合约束的车牌图像超分辨率重建,” 中国图象图形学报, vol. 23, pp. 0802-0813, 2018.

clip_image001岳林蔚, 沈焕锋, 袁强强, 张良培, 兰霞, “基于双边结构张量的局部自适应图像超分辨率重建,” 武汉大学学报（信息科学版）, vol. 40, no. 4, pp. 493-497, 2015.

clip_image001张洪艳, 沈焕锋, 张良培, 李平湘,袁强强, “基于最大后验估计的影像盲超分辨率重建方法,” 计算机应用, vol. 31, no. 5, pp. 1209-1213, 2011.

clip_image001袁强强, 沈焕锋, 李平湘, 张良培, “自适应正则化多幅影像超分辨率重建,” 中国图象图形学报, vol. 15, no. 12, pp. 1720-1727, 2010.

clip_image001吴柯, 牛瑞卿, 沈焕锋, 凌峰, 陈涛, “结合超分辨率重建的神经网络亚像元定位方法,” 中国图象图形学报, vol. 15, no. 11, pp. 1681-1687, 2010.

clip_image001张洪艳, 沈焕锋, 张良培, 李平湘, “一种基于保边缘先验模型的影像超分辨率重建方法,” 中国图象图形学报, vol. 14, no. 11, pp. 2255-2261, 2009.

clip_image001沈焕锋, 李平湘, 张良培, 王毅, “图像超分辨率重建技术与方法综述,” 光学技术, vol. 35, no. 2, pp. 194-203, 2009.

clip_image001沈焕锋等, “影像超分辨率重建技术的发展与应用现状,” 测控技术, vol. 28, no. 6, pp. 1-8, 2009.

clip_image001李平湘, 沈焕锋, 张良培, “影像超分辨率重建技术在遥感中的应用,” 地理空间信息, vol. 5, no. 5, pp. 1-3, 2007.

clip_image001吴柯, 张良培, 李平湘, 沈焕锋, “基于正则MAP模型的遥感影像亚像元定位,” 武汉大学学报（信息科学版）, vol. 32, no. 7, pp. 593-596, 2007.

clip_image001沈焕锋, 李平湘, 张良培, “不完全乔莱斯基分解预优共轭梯度的模型,” 计算机工程, vol. 32, no. 17, pp. 15-18, 2006.

clip_image001沈焕锋, 李平湘, 张良培, “自适应正则MAP超分辨率重建方法,” 武汉大学学报（信息科学版）, vol. 31, no. 11, pp. 949-952, 2006.

clip_image001沈焕锋, 李平湘, 张良培, “一种顾及影像纹理特性的自适应分辨率增强算法,” 遥感学报, vol. 9, no. 3, pp. 253-259, 2005.

clip_image001沈焕锋, 李平湘, 张良培, “一种基于正则化技术的超分辨率重建方法,” 中国图象图形学报, vol. 10, no. 4, pp. 436-440, 2005.

clip_image001沈焕锋, 李平湘, 汪志明, “遥感影像定标最佳样区的自动搜索方法,” 测绘信息与工程, vol. 29, no. 3, pp. 32-33, 2004.

right-hand时-空-谱信息融合

clip_image001J. Wu, L. Lin, T. Li, Q. Cheng, C. Zhang, and H. Shen, “Fusing Landsat 8 and Sentinel-2 data for 10-m dense time-series imagery using a degradation-term constrained deep network,”International Journal of Applied Earth Observation and Geoinformation, vol. 108, pp. 102738, 2022.(PDF)

clip_image001L. Lin, H. Shen, J. Li, and Q. Yuan, “FDFNet: A Fusion Network for Generating High-Resolution Fully PolSAR Images,”IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022.(PDF)

clip_image001M. Jiang, H. Shen, and J. Li, “Deep-Learning-Based Spatio-Temporal-Spectral Integrated Fusion of Heterogeneous Remote Sensing Images,”IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022.(PDF)

clip_image001L. Lin, J. Li, H. Shen, L. Zhao, Q. Yuan, and X. Li, “Low-Resolution Fully Polarimetric SAR and High-Resolution Single-Polarization SAR Image Fusion Network,”IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-17, 2022.(PDF)

clip_image001H. Zhang, H. Shen, Q. Yuan, and X. Guan, “Multispectral and SAR Image Fusion Based on Laplacian Pyramid and Sparse Representation,”Remote Sensing, vol. 14, no. 4, 2022.(PDF)

clip_image001X. Meng, G. Yang, F. Shao, W. Sun, H. Shen, and S. Li, “SARF: A Simple, Adjustable, and Robust Fusion Method,”IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022.(PDF)

clip_image001X. Guan, H. Shen, Y. Wang, D. Chu, X. Li, L. Yue, X. Liu, and L. Zhang, “Fusing MODIS and AVHRR products to generate a global 1-km continuous NDVI time series covering four decades,”Earth Syst. Sci. Data Discuss., vol. 2021, pp. 1-32, 2021.(PDF)

clip_image001M. Jiang, H. Shen, J. Li, Q. Yuan, and L. Zhang, “A differential information residual convolutional neural network for pansharpening,”ISPRS Journal of Photogrammetry and Remote Sensing, vol. 163, pp. 257-271, 2020.(PDF)

clip_image001Y. Wang, Q. Yuan, T. Li, H. Shen, L. Zheng, L. Zhang, “Large-scale MODIS AOD products recovery: Spatial-temporal hybrid fusion considering aerosol variation mitigation,” ISPRS Journal of Photogrammetry and Remote Sensing, 157, 1-12, 2019.(PDF)

clip_image001J. He, J. Li, Q. Yuan, H. Li, and H. Shen, “Spatial–Spectral Fusion in Different Swath Widths by a Recurrent Expanding Residual Convolutional Neural Network,” Remote Sensing, 11(19): 2203, 2019.(PDF)

clip_image001Á. Barsi, Z. Kugler, A. Juhász, G. Szabó, C. Batini, H. Abdulmuttalib, G. Huang, and H. Shen, “Remote sensing data quality model: from data sources to lifecycle phases,” International Journal of Image and Data Fusion, pp. 1-20, 2019.(PDF)

clip_image001J. Li, X. Liu, Q. Yuan, H. Shen, and L. Zhang, “Antinoise Hyperspectral Image Fusion by Mining Tensor Low-Multilinear-Rank and Variational Properties,” IEEE Transactions on Geoscience and Remote Sensing, pp. 1-17, 2019.(PDF)

clip_image001H. Shen, M. Jiang, J. Li, Q. Yuan, Y. Wei, and L. Zhang, “Spatial-Spectral Fusion by Combining Deep Learning and Variational Model,” IEEE Transactions on Geoscience and Remote Sensing, 2019. DOI: 10.1109/TGRS.2019.2904659(PDF)

clip_image001X. 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, 2018. DOI: 10.1109/TGRS.2018.2878007(PDF)

clip_image001X. 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, 2018.(PDF)

clip_image001Q. Yuan, Y. Wei, X. Meng, H. Shen, L. Zhang, “A Multiscale and Multidepth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 3, pp. 978-989, 2018.(PDF)

clip_image001Y. Wei, Q. Yuan, H. Shen, and L. Zhang, “Boosting the Accuracy of Multispectral Image Pansharpening by Learning a Deep Residual Network,” IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 10, pp. 1795-1799, 2017.(PDF)

clip_image001Q. Cheng, H. Liu, H. Shen, P. Wu, and L. Zhang, “A Spatial and Temporal Nonlocal Filter-Based Data Fusion Method,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 8, pp. 4476-4488, 2017. (PDF)

clip_image001 H. Shen, X. Meng, and L. Zhang, “An Integrated Framework for the Spatio-Temporal-Spectral Fusion of Remote Sensing Images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 12, pp. 7135-7148, 2016.(PDF)

clip_image001 X. Meng, J. Li, H.Shen, L. Zhang, H. Zhang, “Pansharpening with a Guided Filter Based on Three-Layer Decomposition,” Sensors, vol. 16, no. 7, pp. 1068(1-15), 2016.(PDF)

clip_image001 M. Guo, H. Zhang, J. Li, L. Zhang, H. Shen, “An Online Coupled Dictionary Learning Approach for Remote Sensing Image Fusion,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 4, pp. 1284-1294, 2014.(PDF)

clip_image001 X. Meng, H. Shen, H. Zhang, L. Zhang, H. Li, “Maximum a Posteriori Fusion Method Based on Gradient Consistency Constraint for Multispectral/Panchromatic Remote Sensing Images,” Spectroscopy and Spectral Analysis, vol. 34, no. 5, pp. 1332-1337, 2014.(PDF)

clip_image001C. Jiang, H. Zhang, H. Shen, L. Zhang, “Two-Step Sparse Coding for the Pan-Sharpening of Remote Sensing Images”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 5, pp. 1792-1805, 2014.(PDF)

clip_image001H. Shen, P. Wu, et al., “A Spatial and Temporal Reflectance Fusion Model Considering Sensor Observation Differences,” International Journal of Remote Sensing, vol. 34, no. 12, pp. 4367-4383, 2013.(PDF)

clip_image001P. Wu, H. Shen, et al., “Land Surface Temperature Retrieval at High Spatial and Temporal Resolutions Based on Multi-Sensor Fusion,” International Journal of Digital Earth, vol. 6, no. S1, pp. 113-133, 2013.(PDF)

clip_image001L. Zhang, H. Shen, W. Gong, and H. Zhang, “Adjustable Model-Based Fusion Method for Multispectral and Panchromatic Images,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 42, no. 6, pp. 1693-1704, 2012.(PDF)

clip_image001C. Jiang, H. Zhang, H. Shen, and L. Zhang, “A Practical Compressed Sensing-Based Pan-Sharpening Method,” IEEE Geoscience and Remote Sensing Letters, vol. 9, no. 4, pp. 629-633, 2012.(PDF)

clip_image001 H. Li, L. Zhang, H. Shen, “A Variational Gradient-based Fusion Method for Visible and SWIR Imagery,” Photogrammetric Engineering and Remote Sensing, vol. 78, no. 9, pp. 947-958, 2012.(PDF)

clip_image001 H. Li, L. Zhang, H. Shen, “A Variational Gradient-based Fusion Method for Visible and SWIR Imagery,” Photogrammetric Engineering and Remote Sensing, vol. 78, no. 9, pp. 947-958, 2012.(PDF)

clip_image001吴金橄, 程青, 李慧芳, 吴鹏海, 沈焕锋, “遥感时空融合中单/双时相辅助数据的适用性分析,” 地理与地理信息科学, vol. 33, no. 5, pp. 9-15, 2017.

clip_image001张亚坤, 张洪艳, 沈焕锋, 张良培, “一种基于稀疏表达的遥感影像时空融合方法,” 电子科技, vol. 30, no. 11, pp. 56-59, 2017.

clip_image001张良培, 沈焕锋, “遥感数据融合的进展与前瞻,” 遥感学报, vol. 20, no. 5, pp. 1050-1061, 2016.

clip_image001刘慧琴, 吴鹏海, 沈焕锋, 袁强强, “一种基于非局部滤波的遥感时空信息融合方法,” 地理与地理信息科学, vol. 31, no. 4, pp. 27-32, 2015.

right-hand多源异质数据信息融合

clip_image001J. Ma, H. Shen, P. Wu, J. Wu, M. Gao, and C. Meng, “Generating gapless land surface temperature with a high spatio-temporal resolution by fusing multi-source satellite-observed and model-simulated data,” Remote Sensing of Environment, vol. 278, pp. 113083, 2022/09/01/, 2022.(PDF)

clip_image001J. Chen, H. Shen, X. Li, T. Li, and Y. Wei, “Ground-level ozone estimation based on geo-intelligent machine learning by fusing in-situ observations, remote sensing data, and model simulation data,” International Journal of Applied Earth Observation and Geoinformation, vol. 112, pp. 102955, 2022.(PDF)

clip_image001J. Wu, T. Li, C. Zhang, Q. Cheng, and H. Shen, “Hourly PM2. 5 Concentration Monitoring with Spatiotemporal Continuity by the Fusion of Satellite and Station Observations,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021.(PDF)

clip_image001H. Shen, Y. Jiang, T. Li, Q. Cheng, C. Zeng, & L. Zhang, “Deep learning-based air temperature mapping by fusing remote sensing, station, simulation and socioeconomic data,” Remote Sensing of Environment, 240, 111692, 2020.(PDF)

clip_image001W. Chen, H. Shen, C. Huang, and X. Li, “Improving Soil Moisture Estimation with a Dual Ensemble Kalman Smoother by Jointly Assimilating AMSR-E Brightness Temperature and MODIS LST,” Remote Sensing, vol. 9, no. 3, pp. 273(1-23), 2017.(PDF)

clip_image001W. Chen, C. Huang, H. Shen, “Comparison of ensemble-based state and parameter estimation methods for soil moisture data assimilation, ” Advances in Water Resources, vol. 86, pp. 425-438, 2015.(PDF)

clip_image001F. Lei, C. Huang, H. Shen, and X. Li, “Improving the estimation of hydrological states in SWAT model via the ensemble Kalman smoother: synthetic experiments for the Heihe Basin in northwest China,” Advances in Water Resources, vol. 67, pp. 32-45, 2014.(PDF)

clip_image001沈焕锋, 刘露, 岳林蔚, 李星华, 张良培, “多源DEM融合的高差拟合神经网络方法,” 测绘学报, vol. 47, pp. 168-177, 2018.

clip_image001陈玮婧, 黄春林, 沈焕锋, “基于Lorenz-63模型的状态与参数同时估计方法对比研究,” 遥感技术与应用, vol. 30, no. 4, pp. 684-693, 2015.

clip_image001李同文, 孙越乔, 杨晨雪, 李明晓, 曾超, 沈焕锋, “融合卫星遥感与地面测站的区域PM2.5反演,” 测绘地理信息, vol.40, no.3, pp. 6-9, 2015.

clip_image001张添, 黄春林, 沈焕锋, “土壤水分对土壤参数的敏感性及其参数优化方法研究,” 地球科学进展, vol. 27, no. 6, pp. 678-685, 2012.

clip_image001张添, 黄春林, 沈焕锋, “地表通量对模型参数的不确定性和敏感性分析,” 遥感技术与应用, vol. 26, no. 5, pp. 569-576, 2011.

right-hand地学精确应用

clip_image001H. Li, C. Hu, X. Zhong, C. Zeng, and H. Shen, “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.(PDF)

clip_image001F. Nan, C. Zeng, G. Ni, M. Zhou, and H. Shen, “Development and Validation of Low-cost IoT Environmental Sensors: A Case Study in Wuhan, China,” IEEE Sensors Journal, pp. 1-1, 2022.(PDF)

clip_image001Y. Jing, L. Lin, X. Li, T. Li, and H. Shen, “Cascaded Downscaling–Calibration Networks for Satellite Precipitation Estimation,” IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022.(PDF)

clip_image001P. Wu, Y. Su, S.-b. Duan, X. Li, H. Yang, C. Zeng, X. Ma, Y. Wu, and H. Shen, “A two-step deep learning framework for mapping gapless all-weather land surface temperature using thermal infrared and passive microwave data,” Remote Sensing of Environment, vol. 277, pp. 113070, 2022/08/01/, 2022.(PDF)

clip_image001J. Yu, X. Li, X. Guan, and H. Shen, “A remote sensing assessment index for urban ecological livability and its application,” Geo-spatial Information Science, pp. 1-22, 2022.(PDF)

clip_image001W. Tan, L. Tian, H. Shen, and C. Zeng, “A New Downscaling-Calibration Procedure for TRMM Precipitation Data Over Yangtze River Economic Belt Region Based on a Multivariate Adaptive Regression Spline Model,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-19, 2022.(PDF)

clip_image001T. Li, J. Wu, J. Chen, and H. Shen, “An Enhanced Geographically and Temporally Weighted Neural Network for Remote Sensing Estimation of Surface Ozone,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-13, 2022.(PDF)

clip_image001X. Li, M. He, H. Li, and H. Shen, “A Combined Loss-Based Multiscale Fully Convolutional Network for High-Resolution Remote Sensing Image Change Detection,” IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022.(PDF)

clip_image001S. Tan, Y. Wang, Q. Yuan, L. Zheng, T. Li, H. Shen, and L. Zhang, “Reconstructing global PM2.5 monitoring dataset from OpenAQ using a two-step spatio-temporal model based on SES-IDW and LSTM,” Environmental Research Letters, vol. 17, no. 3, pp. 034014, 2022.(PDF)

clip_image001Y. Hu, C. Zeng, T. Li, and H. Shen, “Performance comparison of Fengyun-4A and Himawari-8 in PM2.5 estimation in China,” Atmospheric Environment, vol. 271, pp. 118898, 2022/02/15/, 2022.(PDF)

clip_image001J. Wu, X. Su, Q. Yuan, H. Shen, and L. Zhang, “Multivehicle Object Tracking in Satellite Video Enhanced by Slow Features and Motion Features,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-26, 2022.(PDF)

clip_image001W. Huang, W. Min, J. Ding, Y. Liu, Y. Hu, W. Ni, and H. Shen, “Forest height mapping using inventory and multi-source satellite data over Hunan Province in southern China,” Forest Ecosystems, vol. 9, pp. 100006, 2022.(PDF)

clip_image001Y. Yu, J. Li, Q. Yuan, Q. Shi, H. Shen, and L. Zhang, “Coupling Dual Graph Convolution Network and Residual Network for Local Climate Zone Mapping,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 1221-1234, 2022.(PDF)

clip_image001X. Guan, J. M. Chen, H. Shen, X. Xie, and J. Tan, “Comparison of big-leaf and two-leaf light use efficiency models for GPP simulation after considering a radiation scalar,” Agricultural and Forest Meteorology, vol. 313, pp. 108761, 2022.(PDF)

clip_image001Y. Jing, X. Li, and H. Shen, “STAR NDSI collection: a cloud-free MODIS NDSI dataset (2001–2020) for China,” Earth System Science Data, vol. 14, no. 7, pp. 3137-3156, 2022.(PDF)

clip_image001Z. Li, H. Shen, Q. Weng, Y. Zhang, P. Dou, and L. Zhang, “Cloud and cloud shadow detection for optical satellite imagery: Features, algorithms, validation, and prospects,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 188, pp. 89-108, 2022.(PDF)

clip_image001H. Li, Y. Li, T. Wang, Z. Wang, M. Gao, and H. Shen, “Quantifying 3D building form effects on urban land surface temperature and modeling seasonal correlation patterns,” Building and Environment, vol. 204, pp. 108132, 2021.(PDF)

clip_image001Y. Shen, C. Zeng, Q. Cheng, and H. Shen, “Opposite Spatiotemporal Patterns for Surface Urban Heat Island of Two “Stove Cities” in China: Wuhan and Nanchang,” Remote Sensing, vol. 13, no. 21, 2021.(PDF)

clip_image001Q. Yang, B. Wang, Y. Wang, Q. Yuan, C. Jin, J. Wang, S. Li, M. Li, T. Li, and S. Liu, “Global air quality change during COVID-19: a synthetic analysis of satellite, reanalysis and ground station data,” Environmental Research Letters, vol. 16, no. 7, p. 074052, 2021.(PDF)

clip_image001Y. Shen, H. Shen, Q. Cheng, and L. Zhang, “Generating Comparable and Fine-scale Time Series of Summer Land Surface Temperature for Thermal Environment Monitoring,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 2136 – 2147, 2021.(PDF)

clip_image001S. Luo, H. F. Li, R. Z. Zhu, Y. T. Gong, and H. F. 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, pp. 4633-4646, 2021.(PDF)

clip_image001X. Guan, J. M. Chen, H. Shen, and X. Xie, “A modified two-leaf light use efficiency model for improving the simulation of GPP using a radiation scalar,” Agricultural and Forest Meteorology, vol. 307, pp. 108546, 2021.(PDF)

clip_image001P. Dou, H. Shen, Z. Li, and X. Guan, “Time series remote sensing image classification framework using combination of deep learning and multiple classifiers system,” International Journal of Applied Earth Observation and Geoinformation, vol. 103, p. 102477, 2021.(PDF)

clip_image001P. Wu, Z. Yin, C. Zeng, S. B. Duan, F. M. Göttsche, X. Ma, X. Li, H. Yang, and H. Shen, “Spatially Continuous and High-Resolution Land Surface Temperature Product Generation: A review of reconstruction and spatiotemporal fusion techniques,” IEEE Geoscience and Remote Sensing Magazine, vol. 9, no. 3, pp. 112-137, 2021.(PDF)

clip_image001M. Gao, Z. Li, Z. Tan, Q. Liu, and H. Shen, “Simulating the Response of the Surface Urban Heat Environment to Land Use and Land Cover Changes: A Case Study of Wuhan, China,” Remote Sensing, vol. 13, no. 22, 2021.(PDF)

clip_image001P. Dou, H. Shen, Z. Li, X. Guan, and W. Huang, “Remote Sensing Image Classification Using Deep–Shallow Learning,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 3070-3083, 2021.(PDF)

clip_image001T. Li, H. Shen, Q. Yuan, and L. Zhang, “A Locally Weighted Neural Network Constrained by Global Training for Remote Sensing Estimation of PM2.5,” IEEE Transactions on Geoscience and Remote Sensing, 2021. DOI: 10.1109/TGRS.2021.3074569.(PDF)

clip_image001X. Li, Z. Li, R. Feng, S. Luo, C. Zhang, M. Jiang, and H. Shen, “Generating High-Quality and High-Resolution Seamless Satellite Imagery for Large-Scale Urban Regions,” Remote Sensing, 12(1): 81, 2020.(PDF)

clip_image001Q. Yuan, H. Xu, T. Li, H. Shen, and L. Zhang, “Estimating surface soil moisture from satellite observations using a generalized regression neural network trained on sparse ground-based measurements in the continental US,” Journal of Hydrology, vol. 580, pp. 124351, 2020.(PDF)

clip_image001Q. Yuan, H. Shen, T. Li, Z. Li, S. Li, Y. Jiang, and et al, “Deep learning in environmental remote sensing: Achievements and challenges,” Remote Sensing of Environment, vol. 241, pp. 111716, 2020.(PDF)

clip_image001Q. Yang, Q. Yuan, L. Yue, T. Li, H. Shen, & L. Zhang, “Mapping PM2. 5 concentration at a sub-km level resolution: A dual-scale retrieval approach,” ISPRS Journal of Photogrammetry and Remote Sensing, 165, 140-151, 2020.(PDF)

clip_image001Y. Wang, Q. Yuan, H. Shen, L. Zheng, & L. Zhang, “Investigating multiple aerosol optical depth products from MODIS and VIIRS over Asia: Evaluation, comparison, and merging,”Atmospheric Environment, 117548, 2020.(PDF)

clip_image001Y. Wang, Z. Li, C. Zeng, G. Xia, and H. Shen, “An Urban Water Extraction Method Combining Deep Learning and Google Earth Engine,”IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 768-781, 2020.(PDF)

clip_image001J. Wang, Q. Yuan, H. Shen, T. Liu, T. Li, L. Yue, and et al, “Estimating snow depth by combining satellite data and ground-based observations over Alaska: A deep learning approach,” Journal of Hydrology, vol. 585, pp. 124828, 2020.(PDF)

clip_image001X. Tong, G. Xia, Q. Lu, H. Shen, S. Li, S. You, and L. Zhang, “Land-cover classification with high-resolution remote sensing images using transferable deep models,”Remote Sensing of Environment, vol. 237, pp. 111322, 2020.(PDF)

clip_image001Y. Shen, H. Shen, Q. Cheng, L. Huang, and L. Zhang, “Monitoring Three-Decade Expansion of China’s Major Cities Based on Satellite Remote Sensing Images,”Remote Sensing, vol. 12, no. 3, pp. 491, 2020.(PDF)

clip_image001T. Li, H. Shen, C. Zeng, & Q. Yuan, “A validation approach considering the uneven distribution of ground stations for satellite-based PM2.5 estimation,”IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, no. 1, pp. 1312-1321, 2020.(PDF)

clip_image001Y. Jing, H. Shen, X. Li, & X. Guan, “A Two-Stage Fusion Framework to Generate a Spatio–Temporally Continuous MODIS NDSI Product over the Tibetan Plateau,”Remote Sensing, 11(19): 2261, 2019.(PDF)

clip_image001H. Wang, J. Li, Z. Gao, S. H. L. Yim, H. Shen, H. Chak Ho, Z. Li, Z. Zeng, C. Liu, Y. Li, G. Ning, and Y. Yang, “High-Spatial-Resolution Population Exposure to PM2. 5 Pollution Based on Multi-Satellite Retrievals: A Case Study of Seasonal Variation in the Yangtze River Delta, China in 2013,” Remote Sensing, 11(23): 2724, 2019.(PDF)

clip_image001H. Shen, M. Zhou, T. Li, and C. Zeng, “Integration of Remote Sensing and Social Sensing Data in a Deep Learning Framework for Hourly Urban PM 2.5 Mapping,” International Journal of Environmental Research and Public Health, vol. 16, pp.4102, 2019.(PDF)

clip_image001X. Li, R. Feng, X. Guan, H. Shen, and L. Zhang, “Remote sensing image mosaicking: Achievements and challenges,” IEEE Geoscience and Remote Sensing Magazine, vol. 7, no. 4, pp. 8-22, 2019.(PDF)

clip_image001J. Chen, H. Shen, T. Li, X. Peng, H. Cheng, and C. Ma, “Temporal and Spatial Features of the Correlation between PM2. 5 and O3 Concentrations in China,” International Journal of Environmental Research and Public Health, vol. 16, no. 23, pp. 4824, 2019.(PDF)

clip_image001Z. Pan, F. Mao, X. Lu, W. Gong, H. Shen, and Q. Mao, “Enhancement of vertical cloud induced radiative heating in East Asian monsoon circulation derived from CloudSat-CALIPSO observations,” International Journal of Remote Sensing, pp. 1-20, 2019.(PDF)

clip_image001H. Jiang, H. Shen, X. Li, C. Zeng, H. Liu, and F. Lei, “Extending the SMAP 9-km soil moisture product using a spatio-temporal fusion model,” Remote Sensing of Environment, vol. 231, p. 111224, 2019.(PDF)

clip_image001W. Du, N. Chen, S. Yuan, C. Wang, M. Huang, and H. Shen, “Sensor web – Enabled flood event process detection and instant service,” Environmental Modelling & Software, vol. 117, pp. 29-42, 2019.(PDF)

clip_image001Q. Yuan, S. Li, L. Yue, T. Li, H. Shen, and L. Zhang, “Monitoring the Variation of Vegetation Water Content with Machine Learning Methods: Point–Surface Fusion of MODIS Products and GNSS-IR Observations,” Remote Sensing, vol. 11, 2019.(PDF)

clip_image001X. Li, Y. Jing, H. Shen, and L. Zhang, “The recent developments in spatio-temporally continuous snow cover product generation,” Hydrology and Earth System Sciences, vol. 23, no.5, pp. 2401-2416, 2019.(PDF)

clip_image001M. Yuan, Y. Song, Y. Huang, H. Shen, and T. Li, “Exploring the association between the built environment and remotely sensed PM2. 5 concentrations in urban areas,” Journal of Cleaner Production,, vol. 220, pp. 1014–1023, 2019.(PDF)

clip_image001Q. Yang, Q. Yuan, L. Yue, T. Li, H. Shen, and L. Zhang, “The relationships between PM2. 5 and aerosol optical depth (AOD) in mainland China: About and behind the spatio-temporal variations,” Environmental Pollution,, vol. 248, pp. 526–535, 2019.(PDF)

clip_image001X. Guan, H. Shen, X. Li, W. Gan, and L. Zhang, “A long-term and comprehensive assessment of the urbanization-induced impacts on vegetation net primary productivity,” Science of The Total Environment,, vol. 665, pp. 342-253, 2019.(PDF)

clip_image001G. Yang, W. Sun, H. Shen, X. Meng, and J. Li, “An Integrated Method for Reconstructing Daily MODIS Land Surface Temperature Data,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,, vol. 12, no. 3, pp. 1026-1040, 2019.(PDF)

clip_image001H. Shen, J. Wu, Q. Cheng, M. Aihemaiti, C. Zhang, and Z. Li, “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,, vol. 12, no. 3, 2019.(PDF)

clip_image001R. Feng, Q. Du, X. Li, and H. Shen, “Robust registration for remote sensing images by combining and localizing feature-and area-based methods,” ISPRS Journal of Photogrammetry and Remote Sensing,, vol. 151, pp. 15–26, 2019.(PDF)

clip_image001Z. Li, H. Shen, Q. Cheng, Y. Liu, S. You, and Z. He, “Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 150, pp. 197-212, 2019.(PDF)

clip_image001L. Zang, F. Mao, J. Guo, W. Wang, Z. Pan, H. Shen, B. Zhu, Z. Wang, “Estimation of spatiotemporal PM1.0 distributions in China by combining PM2.5 observations with satellite aerosol optical depth,” Science of The Total Environment, vol. 658, pp. 1256-1264, 2019.(PDF)

clip_image001Y. Wang, Q. Yuan, T. Li, H. Shen, L. Zheng, and L. Zhang, “Evaluation and comparison of MODIS Collection 6.1 aerosol optical depth against AERONET over regions in China with multifarious underlying surfaces,” Atmospheric Environment, vol. 200, pp. 280–301, 2019.(PDF)

clip_image001H. Shen, T. Li, Q. Yuan, and L. Zhang, “Estimating Regional Ground‐Level PM2. 5 Directly From Satellite Top‐Of‐Atmosphere Reflectance Using Deep Belief Networks,” Journal of Geophysical Research: Atmospheres, vol. 123, no. 24, pp. 13–875, 2018.(PDF)

clip_image001X. Guan, H. Shen, X. Li, W. Gan, and L. Zhang, “Climate Control on Net Primary Productivity in the Complicated Mountainous Area: A Case Study of Yunnan, China,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, pp. 1-12, 2018.(PDF)

clip_image001H. Xu, Q. Yuan, T. Li, H. Shen, L. Zhang, and H. Jiang, “Quality Improvement of Satellite Soil Moisture Products by Fusing with In-Situ Measurements and GNSS-R Estimates in the Western Continental U.S,” Remote Sensing, vol. 10, no. 1351, pp. 1-22, 2018.(PDF)

clip_image001M. Gao, H. Shen, X. Han, H. Li, and L. Zhang, “Multiple timescale analysis of the urban heat island effect based on the Community Land Model: a case study of the city of Xi’an, China,” Environmental Monitoring and Assessment, vol. 190, no. 8, pp. 1-14, 2018.(PDF)

clip_image001M. Yuan, Y. Huang, H. Shen, and T. Li, “Effects of urban form on haze pollution in China: Spatial regression analysis based on PM2. 5 remote sensing data,” Applied Geography, vol. 98, pp. 215-223, 2018.(PDF)

clip_image001T. Zhang, Z. Zhu, W. Gong, Z. Zhu, K. Sun, L. Wang, Y. Huang, F. Mao, H. Shen, Z. Li, and K. Xu, “Estimation of ultrahigh resolution PM2.5 concentrations in urban areas using 160m Gaofen-1 AOD retrievals,” Remote Sensing of Environment, vol. 216, pp. 91-104, 2018.(PDF)

clip_image001L. Yue, H. Shen, W. Yu, L. Zhang, “Monitoring of Historical Glacier Recession in Yulong Mountain by the Integration of Multisource Remote Sensing Data,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 2, pp. 388-400, 2018.(PDF)

clip_image001X. Guan, H. Shen, W. Gan, G. Yang, L. Wang, X. Li and L. Zhang, “A 33-year NPP monitoring study in southwest China by the fusion of multi-source remote sensing and station data,” Remote Sensing, 9, pp. 1-23, 2017.(PDF)

clip_image001F. Lei, W. T. Crow, H. Shen, C. H. Su, T. R. H. Holmes, R. M. Parinussa, and G. Wang, “Assessment of the impact of spatial heterogeneity on microwave satellite soil moisture periodic error,” Remote Sensing of Environment, vol. 205, pp. 85-99, 2017.(PDF)

clip_image001Q. Yang, Q. Yuan, T. Li, H. Shen, and L. Zhang, “The relationships between PM2. 5 and meteorological factors in China: Seasonal and regional variations,” International journal of environmental research and public health, vol. 14, no. 12, pp. 1510-1528, 2017.(PDF)

clip_image001T. Li, H. Shen, Q. Yuan, X. Zhang, and L. Zhang, “Estimating ground‐level PM2.5 by fusing satellite and station observations: A geo‐intelligent deep learning approach,” Geophysical Research Letters, vol. 44, pp. 1-9, 2017.(PDF)

clip_image001X. Li, H. Shen, R. Feng, J. Li, and L. Zhang, “DEM generation from contours and a low-resolution DEM,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 131, pp. 135-147, 2017.(PDF)

clip_image001X. Li, W. Fu, H. Shen, C. Huang, and L. Zhang, “Monitoring snow cover variability (2000–2014) in the Hengduan Mountains based on cloud-removed MODIS products with an adaptive spatio-temporal weighted method,” Journal of Hydrology, 2017, DOI: 10.1016/j.jhydrol.2017.05.049.(PDF)

clip_image001H. Jiang, H. Shen, H. Li, F. Lei, W. Gan, and L. Zhang, “Evaluation of Multiple Downscaled Microwave Soil Moisture Products over the Central Tibetan Plateau,” Remote Sensing, vol. 9, pp. 402, 2017.(PDF)

clip_image001Z. 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.(PDF)

clip_image001T. Li, H. Shen, C. Zeng, Q. Yuan, and L. Zhang, “Point-surface fusion of station measurements and satellite observations for mapping PM2.5 distribution in China: Methods and assessment,” Atmospheric Environment, vol. 152, pp. 477-489, 2017.(PDF)

clip_image001L. Yue, H. Shen, L. Zhang, X. Zheng, F. Zhang, and Q. Yuan, “High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 123, pp. 20-34, 2017.(PDF)

clip_image001P. Wu, H. Shen, N. Cai, C. Zeng, Y. Wu, B. Wang, et al., “Spatiotemporal analysis of water area annual variations using a Landsat time series: a case study of nine plateau lakes in Yunnan province, China,” International Journal of Remote Sensing, vol. 37, pp. 5826-5842, 2016.(PDF)

clip_image001C. Huang, W. Chen, Y. Li, H. Shen, and X. Li, “Assimilating multi-source data into land surface model to simultaneously improve estimations of soil moisture, soil temperature, and surface turbulent fluxes in irrigated fields,” Agricultural and Forest Meteorology, vol. 230–231, pp. 142-156, 2016.(PDF)

clip_image001X. Peng, H. Shen, L. Zhang, C. Zeng, G. Yang, and Z. He, “Spatially Continuous Mapping of Daily Global Ozone Distribution (2004-2014) with the Aura OMI Sensor: Spatially Continuous Ozone Product,” Journal of Geophysical Research Atmospheres, vol. 121, no. 21, 2016.(PDF)

clip_image001W. Zhai, H. Shen, C. Huang, W. Pei, “Building Earthquake Damage Information Extraction from a Single Post-Earthquake PolSAR Image,” Remote Sensingvol. 8, no. 3, pp. 171, 2016.(PDF)

clip_image001H. Shen, L. Huang, L. Zhang, P. Wu, and C. Zeng, “Long-term and fine-scale satellite monitoring of the urban heat island effect by the fusion of multi-temporal and multi-sensor remote sensed data: A 26-year case study of the city of Wuhan in China,” Remote Sensing of Environment, vol. 7, no. 1, pp. 31-40, 2016.(PDF)

clip_image001W. Zhai, H. Shen, C. Huang, and W. Pei, “Fusion of polarimetric and texture information for urban building extraction from fully polarimetric SAR imagery,” Remote Sensing Letters, vol. 7, no. 1, pp. 31-40, 2016.(PDF)

clip_image001J. Li, H. Zhang, M. Guo, L. Zhang, H. Shen, and Q. Du, “Urban Classification by the Fusion of Thermal Infrared Hyperspectral and Visible Data,” Photogrammetric Engineering & Remote Sensingvol. 81, no. 12, pp. 901-911, 2015.(PDF)

clip_image001F. Lei, W. T. Crow, H. Shen, R. M. Parinussa, and T. R. H. Holmes, “The Impact of Local Acquisition Time on the Accuracy of Microwave Surface Soil Moisture Retrievals over the Contiguous United States,” Remote Sensing, vol. 7, no. 10, pp. 13448-13465, 2015.(PDF)

clip_image001L. Yue, H. Shen, Q. Yuan, and L. Zhang, “Fusion of Multi-scale DEMs using Regularized Super-resolution Methods,” International Journal of Geographical Information Science, vol. 29, no. 12, pp. 2095-2120, 2015.(PDF)

clip_image001P. Wu, H. Shen, L. Zhang, and F. M. Gottsche, “Integrated fusion of multi-scale polar-orbiting and geostationary satellite observations for the mapping of high spatial and temporal resolution land surface temperature,” Remote Sensing of Environment, vol. 156, pp. 169-181, 2015.(PDF)

clip_image001 X. Ma, H. Shen, J. Yang, L. Zhang and P. Li, “Polarimetric-Spatial Classification of SAR images based on the fusion of multiple classifiers”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 3, pp. 961-971, 2014.(PDF)

clip_image001B. Wu, X. Wang, H. Shen, and X. Zhou, “Feature Selection Based on Max-min-associated Indices for Classification of Remotely Sensed Imagery,” International Journal of Remote Sensing, vol.33, no.17, pp. 5492-5512, 2012.(PDF)

clip_image001翟玮, 沈焕锋, 黄春林, “结合PolSAR影像纹理特征分析提取倒塌建筑物,” 遥感技术与应用, vol. 31, no. 5, pp. 975-982, 2016.

clip_image001莫玉琴, 沈瑶, 史俊国, 吴鹏海, 张振威, 沈焕锋, “近15年天津市城市热岛时空演变分析,” 遥感技术与应用, vol. 30, no. 5, pp. 102-110, 2015.

clip_image001 管小彬, 沈焕锋, 甘文霞, 张良培, “基于Landsat TM/ETM+影像的武汉市冬季NPP估算及其时空变化分析,” 遥感技术与应用, vol. 30, no. 5, pp. 894-890, 2015.

clip_image001 莫玉琴, 沈瑶, 史俊国, 吴鹏海, 张振威, 沈焕锋, “基于Landsat系列卫星数据的天津市近15年城市热岛时空演变分析,” 遥感信息, vol. 30, no. 5, pp. 102-110, 2015.

clip_image001甘文霞, 沈焕锋, 张良培, 龚威, “采用6S模型的多时相MODIS植被指数NDVI归一化方法,” 武汉大学学报（信息科学版）, vol.39, no. 3, pp. 300-304, 2014.

2.会议论文

clip_image001T. Li, C. Zhang, H. Shen, Q. Yuan, and L. Zhang “Real-time and Seamless Monitoring of Ground-level PM2.5 Using Satellite Remote Sensing,” ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing, China, 2018.

clip_image001Z. Li, H. Shen, Y. Wei, Q. Cheng, and Q. Yuan, “Cloud Detection by Fusing Multi-Scale Convolutional Features,” ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing, China, 2018.

clip_image001X. Meng, H. Shen, Q. Yuan, H. Li, and L. Zhang, “An Integrated Fusion Framework for Joint Information Reconstruction and Resolution Enhancement,” ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Wuhan, China, 2017.

clip_image001X. Liu, H. Shen, Q. Yuan, L. Zhang, and Q. Cheng, “A Novel Removal Method for Dense Stripes in Remote Sensing Images,” XXIII ISPRS Congress, Prague, Czech Republic, 2016.

clip_image001X. Guan, H. Shen, W. Gan, and L. Zhang, “The estimation and analysis of NPP from 1982 to 2014 in Yunnan province based on multi-source remote sensing data,” 4th International Workshop on Earth Observation and Remote Sensing Applications (EORSA), Guangzhou, China, 2016.

clip_image001X. Zhang, H. Shen, and T. Li, “Effect characteristics of Chinese New Year fireworks/firecrackers on PM2.5 concentration at large space and time scales,” 4th International Workshop on Earth Observation and Remote Sensing Applications (EORSA), Guangzhou, China, 2016.

clip_image001M. Gao, H. Shen, X. Han, and W. Chen, “Numerical simulation of diurnal variation of urban land surface temperature based on CLM4.5,” 4th International Workshop on Earth Observation and Remote Sensing Applications (EORSA), Guangzhou, China, 2016.

clip_image001G. C. Iannelli, P. Gamba, X. Li, and H. Shen, “Improving urban extent extraction from VHR optical data by means of cloud detection and image reconstruction,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016.

clip_image001T. Li, H. Shen, and L. Zhang, “Mapping PM2.5 distribution in China by fusing station measurements and satellite observation,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016.

clip_image001Y. Shen, H. Shen, H. Li, and Q. Cheng, “Long-term urban impervious surface monitoring using spectral mixture analysis: A case study of Wuhan city in China,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016.

clip_image001Y. Wei, Q. Yuan, H. Shen, and L. Zhang, “A universal remote sensing image quality improvement method with deep learning,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016.

clip_image001H. Zhang, H. Shen, and L. Zhang, “Fusion of multispectral and SAR images using sparse representation,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016.

clip_image001H. Jiang and H. Shen, “SMOS soil moisture downscaling based on back propagation neural network with MODIS LST and EVI,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016.

clip_image001Z. Li, H. Shen, H. Li, and L. Zhang, “Automatic cloud and cloud shadow detection in GF-1 WFV imagery using multiple features,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016.

clip_image001Q. Yuan, H. Shen, and H. Li, “Single Remote Sensing Image Haze Removal Based on Spatial and Spectral Self-adaptive Model,” the 8th International Conference on Image and Graphics (ICIG), Tianjing, China, 2015.

clip_image001X. Li, H. Shen, H. Li, and Q. Yuan, “Temporal Domain Group Sparse Representation Based Clouds Removal of Remote Sensing Images,” the 8th International Conference on Image and Graphics (ICIG), Tianjing, China, 2015.

clip_image001H. Li, L. Xu, Z. Zhang, H. Shen, W. Li, and L. Cao, “A Land Cover Adaptive Topographic Correction and Evaluation Method for Remote Sensing data,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, 2015.

clip_image001L. Yue, W. Yu, H. Shen, and L. Zhang, “Accuracy Assessment of SRTM v4.1 and ASTER GDEM v2 in High-altitude Mountainous Areas: a Case Study in Yulong Snow Mountain, China,” IEEE International Geosciences and Remote Sensing Symposium (IGARSS), Milan, Italy, 2015.

clip_image001X. Meng, H. Shen, L. Zhang, Q. Yuan, and H. Li, “A Unified Framework for Spatio-temporal-spectral Fusion of Remote Sensing Images,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, 2015.

clip_image001X. Ma, H. Shen, “Refined PolSAR Anisotropic Diffusion Filter Coupling with Adaptive Data-fitting Term,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, 2015.

clip_image001X. Meng, H. Shen, H. Li, Q. Yuan, H. Zhang, and L. Zhang, “Improving the Spatial Resolution of Hyperspectral Image Using Panchromatic and Multispectral Images: an Integrated Method,” the 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Tokyo, Japan, 2015.

clip_image001L. Huang, H. Shen, L. Zhang, P. Wu, C. Zeng, “Relationships analysis of land surface temperature with vegetation indicators and impervious surface fraction by fusing multi-temporal and multi-sensor remotely sensed data”,Joint Urban Remote Sensing Event (JURSE), Lausanne, Switzerland, 2015.

clip_image001X. Guan, H. Shen, W. Gan, L. Zhang, “Analysis of Impacts of Drought on GPP in Yunnan province Based on MODIS Products,” the 3rdAgro-Geoinformatics, Beijing, China, 2014.

clip_image001X. Li, H. Shen, H. Li, L. Zhang, “Analysis Model Based Recovery of Remote Sensing Data,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Quebec, Canada, 2014.

clip_image001X. Ma, H. Shen, Q. Yuan, L. Zhang, “Spatially Adaptive Nonlocal Total Variation for PolSAR Despeckling,” IEEE International Geoscience and Remote Sensing Symposium(IGARSS), Quebec, Canada, 2014.

clip_image001W. He, H. Zhang, L. Zhang, H. Shen, “A Noise-adjusted Iterative Randomized Singular Value Decomposition Method for Hyperspectral Image Denoising,” IEEE International Geoscience and Remote Sensing Symposium(IGARSS), Quebec, Canada, 2014.

clip_image001F.Lei, H. Shen, and C. Huang, “Enhancing the operational hydrologic forecast by simultaneous assimilation of satellite-based soil moisture and in-situ streamflow,” the 34th Asian Conference on Remote sensing (ACRS), Bali, Indonesia, 2013.

clip_image001W. Gan, H. Shen, W. Gong, and X. Peng, “Normalizing medium resolution ndvi usinglow resolution modis products,” the 34th Asian Conference on Remote sensing(ACRS), Bali, Indonesia, 2013.

clip_image001X. Lan, H. Shen, L. Zhang. “An Adaptive Non-Local Means Filter Based on Region Homogeneity ,” the 7th International Conference on Image and Graphics (ICIG), Qingdao, China, 2013.

clip_image001J. Li, H. Shen, Q. Yuan, L. Zhang, W. Gong. “Hyperspectral Image Denoising via Multidimensional Nonlocal Model,” the 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Gainesville, Florida, USA, 2013.

clip_image001J. Li, C. Zeng, Q. Yuan, L. Zhang, H. Shen. “Hyperspectral Images Reconstruction Based Super-Pixel Mapping using Cross-Channel Sparse Model,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Melbourne, Australia, 2013.

clip_image001W. Gan, H. Shen, L. Zhang, W. Gong, “Normalization of NDVI from Different Sensor System using MODIS Products as Reference”, the 35th International Symposium on Remote Sensing of Environment (ISRSE), Beijing, China, 2013.

clip_image001Q. Yuan, H. Shen, L. Zhang, X. Lan, “Hypspectral image denoising with amulti-view fusion strategy “, the 4th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Shanghai, China, 2012.

clip_image001L. Zhang, X. Xu, J. Li, H. Shen, Y. Zhong, H. Xin, “Research on image reconstruction based and pixel unmixing based sub-pixel mapping methods” ISymposium (IGARSS), Munich, Germany, 2012.

clip_image001H. Shen, “Integrated Fusion Method For MultipleTemporal-Spatial-Spectral Images,” the XXII Congress of International Society for Photogrammetry and Remote Sensing (ISPRS), Melbourne, Australia, 2012.

clip_image001X. Li, H. Shen, C. Zeng, P. Wu, “Restoring Aqua Modis Band 6 By Other SpectralBands Using Compressed Sensing Theory”, the 4th Workshop on Hyperspectral Image and Signal Processing, Shanghai: Evolution in Remote Sensing (WHISPERS), China, 2012.

clip_image001Q. Wang, Y. Xu, Q. Yuan, R. Wang, H. Shen, Y. Wang, “Restoration of CBERS-02B Remote Sensing Image Based on Knife-edge PSF Estimation and Regularization Reconstruction Model,” the 4th International Conference on Intelligent Computation Technology and Automation (ICICTA), Shenzhen, China, 2011.

clip_image001R. Wang, C. Zeng, P. Li, and H. Shen,”Terra MODIS Band 5 Stripe Noise Detection and Correction Using MAP-Based Algorithm,” the International Conferenceon Remote Sensing, Environment and Transportation Engineering (RSETE), Nanjing, China, 2011.

clip_image001H. Zhang, L. Zhang, H. Shen, P. Li, “A MAP Approach for Joint Image Registration, Blur Identification and Super Resolution,” the 5thInternational Conference on Image and Graphics (ICIG), Xi’an, China, 2009.

clip_image001Y. Zhong, L. Zhang, P. Li, H. Shen, “A sub-pixel mapping algorithm based on artificial immune systems for remote sensing imagery,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 2009.

clip_image001Y. Wang, R. Niu, H. Shen, X. Yu,”Forward-and-Backward Diffusion for Hyperspectral Remote Sensing Image Smoothing and Enhancement,” the International Conference on Earth Observation Data Processsing and Analysis (ICEODPA), Wuhan, China, 2008.

clip_image001H. Shen, et al., “Improving the Quality of Remote Sensing Images Using a Universal Reconstruction Method,” the International Conference on Earth Observation Data Processing and Analysis (ICEODPA), Wuhan, China, 2008.

clip_image001H. Shen, et al., “Destriping and Inpainting of Remote Sensing Image Using Maximum A-Posteriori Method,” XXI Congress International Society for Photogrammetry and Remote Sensing (ISPRS), Beijing, China, 2008.

clip_image001P. Li, J. Zhang, H. Shen, L. Zhang, “A Super Resolution Reconstruction Algorithm to Multi-Temporal Remote Sensing Images,” the International Conference “Mapping Without The Sun-Techniques and Applications of Optical and SAR Imagery Fusion”, Chengdu, China, 2007.

clip_image001H. Shen, P. Li, L. Zhang, Y. Zhao, “A MAP Algorithm to Super-Resolution Image Reconstruction,” the 3rd International Conference on Image and Graphics (ICIG), Hong Kong, 2004.

clip_image001P. Li, H. Shen, L. Zhang, “A Method of Image Resolution Enhancement Based on the Matching Technique,” the 20th ISPRS Congress, vol. XXXV, Part B3, Istanbul, Turkey, 2004.

3.出版著作

clip_image001沈焕锋, 袁强强, 李杰, 岳林蔚, 张良培. 遥感数据质量改善之信息复原. 北京：科学出版社, 2018.

clip_image001沈焕锋, 李慧芳, 李星华, 张良培. 遥感数据质量改善之信息校正. 北京：科学出版社, 2018.

clip_image001沈焕锋, 程青, 李星华, 曾超, 张良培. 遥感数据质量改善之信息重建. 北京：科学出版社, 2018.

clip_image001张良培, 沈焕锋, 张洪艳, 袁强强. 图像超分辨率重建. 北京: 科学出版社, 2012.

clip_image001沈焕锋, 钟燕飞, 王毅等, ENVI遥感影像处理方法. 武汉: 武汉大学出版社, 2009.

4.发明专利

clip_image001沈焕锋，张良培. 一种自适应变分遥感影像融合方法，ZL201010227696.3.

clip_image001沈焕锋，曾超. 基于波段相关性的遥感影像类内局部拟合恢复方法，ZL201010227714.8.

clip_image001王密，张良培，潘俊，沈焕锋. 一种推扫式卫星影像CCD相对辐射校正方法， ZL200410060986.8.

clip_image001沈焕锋，李星华，张良培，张洪艳. 利用多时相数据去除光学遥感影像大面积厚云的方法，ZL201210551692.X.

clip_image001沈焕锋，姜湾，张良培，袁强强. 基于分段校正的遥感影像条带噪声去除方法，ZL201210551279.3.

clip_image001曾超，沈焕锋，张良培. 基于多时相数据的遥感影像加权回归恢复方法，ZL201210551266.6.

clip_image001沈焕锋，吴鹏海，艾廷华. 一种任意传感器数量的时空定量遥感融合方法，ZL201210551277.4.

clip_image001李杰，张良培，袁强强，沈焕锋. 一种结合波段聚类和稀疏表达的遥感影像复原方法，ZL201210551267.0.

clip_image001杨刚，沈焕锋，袁强强，张良培，李慧芳. 一种遥感序列数据的时域重建方法，申请号：201510074076.3.

clip_image001沈焕锋，刘慧琴，吴鹏海，袁强强. 顾及非局部特性与时空变化的遥感数据时空定量融合方法，ZL201510087994.X.

clip_image001沈焕锋，付文轩，李星华，张良培. 一种结合时空信息的遥感逐日积雪产品去云方法，ZL201510094932.1.

clip_image001刘欣鑫，沈焕锋，袁强强，张良培. 一维信号处理引导下的遥感影像条带噪声快速滤除方法，ZL201510613994.9.

clip_image001沈焕锋，李同文. 一种结合卫星和站点观测反演时空连续PM2.5浓度的方法，ZL201510849327.0.

clip_image001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.

clip_image001沈焕锋，林镠鹏，李杰，袁强强. 一种全极化合成孔径雷达影像超分辨率重建方法，ZL 202011348480.2

clip_image001窦鹏，沈焕锋. 基于特征关系学习模型训练方法及数据分类方法，ZL202010013802.1

clip_image001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.

clip_image001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. ZL2020113499935.

clip_image001李星华，顾小虎，管小彬，沈焕锋. 一种基于并联混合卷积网络的高分辨率遥感影像分类方法. ZL2022100652118.

clip_image001沈焕锋，孙京，袁强强，周春平，李小娟，杨灿坤，郭姣. 一种图像超分辨率重建方法及系统. 申请号：201710238065.3.

clip_image001沈焕锋，冯蕊涛，李星华，周春平，李小娟，杨灿坤，郭姣. 一种亚像素级影像配准方法及系统. 申请号：201710238081.2.

clip_image001沈焕锋，周曼，李同文，袁强强. 一种结合遥感数据与社会感知数据的PM2.5深度学习反演方法. 申请号：201910451339.6.

clip_image001沈焕锋，李志伟. 一种基于逐步校正的高分辨率遥感影像厚云去除方法. 申请号：201910494982.7.

clip_image001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. 申请号：202011349993.5.

clip_image001沈焕锋，周晨霞，李杰. 一种通用的单、多时相 SAR 影像相干斑噪声去除方法. 申请号：202011350566.9

clip_image001沈焕锋，周玮，李星华.一种顾及地物类别差异的多幅高分辨率遥感影像镶嵌方法.申请号：202011349672.5

clip_image001蒋梦辉，李杰，沈焕锋，袁强强. 一种非监督学习的遥感影像空谱融合方法及系统.申请号：202011398541.6

clip_image001沈焕锋，南方，周曼. 一种基于无线传输的气象集成传感器系统. 申请号：202022956914.9

clip_image001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. 申请号：202110345854.3

clip_image001黄文丽，闵万坤，丁家祺，刘迎春，沈焕锋. 基于多源数据的森林生物量遥感制图方法. 申请号：202110393861.0

clip_image001林德坤，沈焕锋，曾超，蒋梦辉，姜涛. 一种自适应空间加权的变分遥感影像空谱融合方. 申请号：202210354338.1.

clip_image001熊劲松，沈焕锋，曾超，林德坤，石浩杰. 一种基于多任务深度学习的遥感PM2.5和NO2协同反演方法. 申请号：202210354351.7.

5.软件著作权

clip_image001沈焕锋，曾超，吴崎，付文轩，张良培. 遥感信息缺失重建软件，软件著作权登记号：2015SR207195.

clip_image001沈焕锋，李志伟，李慧芳，李伟，吴崎. 国产高分辨率卫星影像云雪检测系统，软件著作权登记号：2017SR016436.

clip_image001沈焕锋，吴金橄，李伟. 多源遥感时空融合软件，软件著作权登记号：2018SR687581.

clip_image001沈焕锋，李同文，徐少良，袁强强. 大气PM2.5实时无缝监测发布系统，软件著作权登记号：2019SR0535101.