1. Papers

right-handImage Restoration (Denoising and Deblurring)

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_image001X. Lan, X. Liu, H. Shen, Q. Yuan, L. Zhang, “A Novel Median Filter to Iteratively Remove Salt-and-Pepper Noise from Highly Corrupted Images,” Geomatics and Information Science of Wuhan University, vol. 42, no. 12, pp. 1731-1737, 2017. (in Chinese)

clip_image001X. Ma, H. Shen, J. Yang, L. Zhang, “Polarimetric SAR speckle filtering using a nonlocal weighted minimum mean squared error filter,” Journal of Image and Graphics, vol. 20, no. 1, pp. 140-150, 2015. (in Chinese)

clip_image001W. Jiang, H. Shen, C. Zeng, L. Zhang, H. Zhang, X. Liu, “Destriping Method for Band 28 of Terra MODIS Images,” Geomatics and Information Science of Wuhan University, vol. 39, no. 5, pp. 326-330, 2014. (in Chinese)

clip_image001Y. Xu, Q. Wang, H. Shen, P. Li, H. Zhang, “A Remote Sensing Image Restoration Method Based on Estimation and Regularization Model,” Journal of Geomatics, vol. 35, no. 6, pp. 7-9, 2010. (in Chinese)

clip_image001Y. Wang, R. Niu, X. Yu, H. Shen, “Time Dependent Robust Anisotropic Di?usion Processes,” Acta Automatica Sinica, vol. 35, no. 9, pp. 1253-1256, 2009. (in Chinese)

right-handCorrection of Non-uniform Information

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_image001X. Wang, H. Li, Q. Yuan, H. Shen, L. Zhang, “Uneven intensity correction using split Bregman for remote sensing images,” Journal of Image and Graphics, vol. 19, no. 5, pp. 798-805, 2014. (in Chinese)

clip_image001H. Li, H. Shen, B. Du, K. Wu, “A High-fidelity Method of Removing Thin Cloud from Remote Sensing Digital Images Based on Homomorphic Filtering,” Remote Sensing Information, no.1, pp. 41-44, 2011. (in Chinese)

clip_image001H. Li, H. Shen, L. Zhang, P. Li, “An Uneven Illumination Correction Method Based on Variational Retinex for Remote Sensing Image,” Acta Geodaetica et Cartographica Sinica, vol. 9, no. 6, pp. 585-591, 2010. (in Chinese)

right-handImage Missing Information Reconstruction

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 X. Peng, H. Shen, C. Zeng, L. Zhang, Z. He, “A Method for the Recovery of Aura Satellite Remote Sensing Ozone Products,” Geomatics and Information Science of Wuhan University, vol. 42, no. 6, pp. 789-796, 2017. (in Chinese)

clip_image001 Z. Liu, P. Wu, Y. Wu, H. Shen, C. Zeng, “Robust reconstruction of missing data in Feng Yun geostationary satellite land surface temperature products,” Journal of Remoe Sensing, vol. 21, no. 1, pp. 40-51, 2017. (in Chinese)

clip_image001 W. Fu, H. Shen, X. Li, C. Huang, C. Zeng, J. Hou, “Adaptively Spatio-temporal Weighted Method for Removing Cloud Obscuration from MODIS Daily Snow Cover Products,” Remote Sensing Information, 31, no. 2, pp. 36-43, 2016. (in Chinese)

right-hand Multi-view Fusion (Super-resolution)

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_image001L. Yue, H. Shen, Q. Yuan, L. Zhang, L. Xia, “A Bilateral Structure Based Local Adaptive Regularization for Super-resolution,” Geomatics and Information Science of Wuhan University, vol. 40, no. 4, pp. 493-497, 2015. (in Chinese)

clip_image001H. Zhang, H. Shen, L. Zhang, P. Li, Q. Yuan, “Blind super-resolution reconstruction method based on maximum a posterior estimation,” Journal of Computer Applications, vol. 31, no. 5, pp. 1209-1213, 2011. (in Chinese)

clip_image001Q. Yuan, H. Shen, P. Li, L. Zhang, “Adaptively Regularized Multi-frame Image Super-resolution Reconstruction,” Journal of Image and Graphics, vol. 15, no. 12, pp. 1720-1727, 2010. (in Chinese)

clip_image001K. Wu, R. Niu, H. Shen, F. Ling, T. Chen, “Sub-pixel mapping method based on ANN and super-resolution reconstructed model,” Journal of Image and Graphics, vol. 15, no. 11, pp. 1681-1687, 2010. (in Chinese)

clip_image001H. Zhang, H. Shen, L. Zhang, P. Li, “An Edge-preserving Image Super-resolution Reconstruction Method,” Journal of Image and Graphics, vol. 14, no. 11, pp. 2255-2261, 2009. (in Chinese)

clip_image001H. Shen, P. Li, L. Zhang, Y. Wang, “Overview on Super Resolution Image Reconstruction,” Optical Technique, vol. 35, no. 2, pp. 194-203, 2009. (in Chinese)

clip_image001H. Shen et al, “Development and Application of Super Resolution Image Reconstruction Technique,” Measurement & Control Technology, vol. 28, no. 6, pp. 1-8, 2009. (in Chinese)

clip_image001P. Li, H. Shen, L. Zhang, “Super Resolution Image Reconstruction Applied in Remote Sensing,” Geospatial Information, vol. 5, no. 5, pp. 1-3, 2007. (in Chinese)

clip_image001K. Wu, L. Zhang, P. Li, H. Shen, “Sub-pixel Mapping of Remote Sensing Images Based on MAP Model,” Geomatics and Information Science of Wuhan University, vol. 32, no. 7, pp. 593-596, 2007. (in Chinese)

clip_image001H. Shen, P. Li, L. Zhang, “Incomplete Cholesky Decomposition Conjugate Gradient Model,” Computer Engineering, vol. 32, no. 17, pp. 15-18, 2006. (in Chinese)

clip_image001H. Shen, P. Li, L. Zhang, “Adaptive Regularized MAP Super-resolution Reconstruction Method,” Geomatics and Information Science of Wuhan University, vol. 31, no. 11, pp. 949-952, 2006. (in Chinese)

clip_image001H. Shen, P. Li, L. Zhang, “An Adaptive Algorithm for Resolution Enhancement Considering the Texture Attribute of Images,” Journal of Remote Sensing, vol. 9, no. 3, pp. 253-259, 2005. (in Chinese)

clip_image001H. Shen, P. Li, L. Zhang, “A Regularized Super-resolution Image Reconstruction Method,” Journal of Image and Graphics, vol. 10, no. 4, pp. 436-440, 2005. (in Chinese)

clip_image001H. Shen, P. Li, Z. Wang, “Automatic Search of ROI for Calibration in Remote Sensing Images,” Journal of Geomatics, vol. 29, no. 3, pp. 32-33, 2004. (in Chinese)

right-handSpatio-temporal-spectral Information Fusion

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_image001J. Wu, Q. Chen, H. Li, P. Wu, H. Shen, “Applicability Analysis of Mono and Bi-temporal Auxiliary Data in Remote Sensing Spatiotemporal Fusion,”Geography and Geo-Information Science, vol. 33, no. 5, pp. 9-15, 2017. (in Chinese)

clip_image001Y. Zhang, H. Zhang, H. Shen, L. Zhang, “A Spatiotemporal Fusion Algorithm based on Sparse Representation for Remote Sensing Imagery,”Electronic Science and Technology, vol. 30, no. 11, pp. 56-59, 2017. (in Chinese)

clip_image001L. Zhang, H. Shen, “Progress and future of remote sensing data fusion,” Journal of Remote Sensing, vol. 20, no. 5, pp. 1050-1061, 2016. (in Chinese)

clip_image001H. Liu, P. Wu, H. Shen, Q. Yuan, “A Spatio-Temporal Information Fusion Method Based on Non-Local Means Filter,” Geography and Geo-Information Science, vol. 31, no. 4, pp. 27-32, 2015. (in Chinese)

right-handMulti-source Heterogeneous Data Fusion

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_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_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_image001W. Chen, C. Huang, H. Shen, “Comparison of Methods for Simultaneous States and Parameters Estimation based on Lorenz-63 Model,” Remote Sensing Technology and Application, vol. 30, no. 4, pp. 684-693, 2015. (in Chinese)

clip_image001T. Li, Y. Sun, C. Yang, M. Li, C. Zeng, H. Shen, “Retrieving PM2.5 Using Satellite Remote Sensing and Ground Station Measurements,” Journal of Geomatics, vol.40, no.3, pp. 6-9, 2015. (in Chinese)

clip_image001T. Zhang, C. Huang, H. Shen, “Sensitivity and Parameters Optimization Method of Soil Parameters to Soil Moisture in Common Land Model,” Advances in Earth Science, vol. 27, no. 6, pp. 678-685, 2012. (in Chinese)

clip_image001T. Zhang, C. Huang, H. Shen, “The Uncertainty and Sensitivity Analysis of Surface Turbulent Fluxes to Remote Sensing Products,” Remote Sensing Technology and Application, vol. 26, no. 5, pp. 569-576, 2011. (in Chinese)

right-handAccurate Application in Geosciences

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_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_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, pp. 1–12, 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 Xian, 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, and W. Pei, ” Building Earthquake Damage Information Extraction from a Single Post-Earthquake PolSAR Image,” Remote Sensing, vol. 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_image001W. Zhai, H. Shen, C. Huang, “Collapsed Buildings Extraction from the PolSAR Image Based on the Analysis of Texture Features,” Remote Sensing Technology and Application, vol. 31, no. 5, pp. 975-982, 2016. (in Chinese)

clip_image001Y. Mo, Y. Shen, J. Shi, P. Wu, Z. Zhang, H. Shen, “Temporal and Spatial Evolution of Tianjin Urban Heat Islands in Recent 15 Years,” Remote Sensing Information, vol. 30, no. 5, pp. 102-110, 2015. (in Chinese)

clip_image001X. Guan, H. Shen, W. Gan, L. Zhang, “Estimation and Spatiotemporal Analysis of Winter NPP in Wuhan Based on Landsat TM/ETM+ Images,” Remote Sensing Technology and Application, vol. 30, no. 5, pp. 894-890, 2015. (in Chinese)

clip_image001 Y. Mo, Y. Shen, J. Shi, P. Wu, Z. Zhang, H. Shen, “Using Landsat satellite data to analyze the temporal and spatial evolution of Tianjin Urban Heat Islands of recent 15 years,” Remote Sensing Information, 30, no. 5, pp. 102-110, 2015. (in Chinese)

clip_image001W. Gan, H. Shen, L. Zhang, W. Gong, “Normalization of Multi-temporal MODIS NDVI Based on 6S Radiative Transfer Model,” Geomatics and Information Science of Wuhan University, vol.39, no. 3, pp. 300-304, 2014. (in Chinese)

2.Conference Papers

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.