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Research Article

STFRDN: a residual dense network for remote sensing image spatiotemporal fusion

ORCID Icon & ORCID Icon
Pages 3259-3277 | Received 20 Feb 2023, Accepted 26 May 2023, Published online: 08 Jun 2023

References

  • Chen, G., P. Jiao, H. Qing, L. Xiao, and Z. Ye. 2022. “SwinStfm: Remote Sensing Spatiotemporal Fusion Using Swin Transformer.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–18, 5410618. doi:10.1109/TGRS.2022.3182809.
  • Chen, Y., K. Shi, G. Yong, Y. Zhou, F. Lin, and S. Zhang. 2021. “Spatiotemporal Remote Sensing Image Fusion Using Multiscale Two-Stream Convolutional Neural Networks.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–12. doi:10.1109/TGRS.2020.3034752.
  • DeVries, B., C. Huang, J. Armston, W. Huang, J. W. Jones, and M. W. Lang. 2020. “Rapid and Robust Monitoring of Flood Events Using Sentinel-1 and Landsat Data on the Google Earth Engine.” Remote Sensing of Environment 240: 111664. doi:10.1016/j.rse.2020.111664.
  • Gao, F., J. Masek, M. Schwaller, and F. Hall. 2006. “On the Blending of the Landsat and MODIS Surface Reflectance: Predicting Daily Landsat Surface Reflectance.” IEEE Transactions on Geoscience and Remote Sensing 44 (8): 2207–2218. doi:10.1109/TGRS.2006.872081.
  • Ghamisi, P., B. Rasti, N. Yokoya, Q. Wang, B. Hofle, L. Bruzzone, F. Bovolo, M. Chi, K. Anders, and R. Gloaguen. 2019. “Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art.” IEEE Geoscience and Remote Sensing Magazine 7 (1): 6–39. doi:10.1109/MGRS.2018.2890023.
  • Guo, D., W. Shi, M. Hao, and X. Zhu. 2020. “FSDAF 2.0: Improving the Performance of Retrieving Land Cover Changes and Preserving Spatial Details.” Remote Sensing of Environment 248: 111973. doi:10.1016/j.rse.2020.111973.
  • He, K., W. Sun, G. Yang, X. Meng, K. Ren, J. Peng, and D. Qian. 2022. “A Dual Global–Local Attention Network for Hyperspectral Band Selection.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–13. doi:10.1109/TGRS.2022.3230846.
  • Hong, D., L. Gao, N. Yokoya, J. Yao, J. Chanussot, Q. Du, and B. Zhang. 2020. “More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification.” IEEE Transactions on Geoscience and Remote Sensing 59 (5): 4340–4354. doi:10.1109/TGRS.2020.3016820.
  • Hong, D., N. Yokoya, J. Chanussot, and X. Xiang Zhu. 2018. “An Augmented Linear Mixing Model to Address Spectral Variability for Hyperspectral Unmixing.” IEEE Transactions on Image Processing 28 (4): 1923–1938. doi:10.1109/TIP.2018.2878958.
  • Hou, T., W. Sun, C. Chen, G. Yang, X. Meng, and J. Peng. 2022. “Marine Floating Raft Aquaculture Extraction of Hyperspectral Remote Sensing Images Based Decision Tree Algorithm.” International Journal of Applied Earth Observation and Geoinformation 111: 102846. doi:10.1016/j.jag.2022.102846.
  • Huang, B., and H. Song. 2012. “Spatiotemporal Reflectance Fusion via Sparse Representation.” IEEE Transactions on Geoscience and Remote Sensing 50 (10): 3707–3716. doi:10.1109/TGRS.2012.2186638.
  • Jia, D., C. Song, C. Cheng, S. Shen, L. Ning, and C. Hui. 2020. “A Novel Deep Learning-Based Spatiotemporal Fusion Method for Combining Satellite Images with Different Resolutions Using a Two-Stream Convolutional Neural Network.” Remote Sensing 12 (4): 698. doi:10.3390/rs12040698.
  • Jiaxin, L., D. Hong, L. Gao, J. Yao, K. Zheng, B. Zhang, and J. Chanussot. 2022. “Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review.” International Journal of Applied Earth Observation and Geoinformation 112: 102926. doi:10.1016/j.jag.2022.102926.
  • Kingma, D. P., and J. Ba (2015). Adam: A Method for Stochastic Optimization. In Y. Bengio and Y. LeCun (edited by), 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 3rd International Conference on Learning Representations, ICLR 2015. http://arxiv.org/abs/1412.6980
  • Lei, D., M. Bai, L. Zhang, and L. Weisheng. 2022. “Convolution Neural Network with Edge Structure Loss for Spatiotemporal Remote Sensing Image Fusion.” International Journal of Remote Sensing 43 (3): 1015–1036. doi:10.1080/01431161.2022.2030070.
  • Lin, Y., X. Chen, L. Huang, C. Zhu, A. Shahtahmassebi, J. Zhang, S. Shen, R. Peng, J. Deng, and K. Wang. 2021. “Fine-Scale Mapping of Urban Ecosystem Service Demand in a Metropolitan Context: A Population-Income-Environmental Perspective.” Science of the Total Environment 781: 146784. doi:10.1016/j.scitotenv.2021.146784.
  • Liu, X., C. Deng, J. Chanussot, D. Hong, and B. Zhao. 2019. “StfNet: A Two-Stream Convolutional Neural Network for Spatiotemporal Image Fusion.” IEEE Transactions on Geoscience and Remote Sensing 57 (9): 6552–6564. doi:10.1109/TGRS.2019.2907310.
  • Liu, X., C. Deng, S. Wang, G.-B. Huang, B. Zhao, and P. Lauren. 2016. “Fast and Accurate Spatiotemporal Fusion Based Upon Extreme Learning Machine.” IEEE Geoscience and Remote Sensing Letters 13 (12): 2039–2043. doi:10.1109/LGRS.2016.2622726.
  • Liu, X., D. Hong, J. Chanussot, B. Zhao, and P. Ghamisi. 2021. “Modality Translation in Remote Sensing Time Series.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–14. doi:10.1109/TGRS.2021.3079294.
  • Liu, K., W. Sun, Y. Shao, W. Liu, G. Yang, X. Meng, J. Peng, D. Mao, and K. Ren. 2022. “Mapping Coastal Wetlands Using Transformer in Transformer Deep Network on China ZY1-02D Hyperspectral Satellite Images.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15: 3891–3903. doi:10.1109/JSTARS.2022.3173349.
  • Mingquan, W., Z. Niu, C. Wang, W. Chaoyang, and L. Wang. 2012. “Use of MODIS and Landsat Time Series Data to Generate High-Resolution Temporal Synthetic Landsat Data Using a Spatial and Temporal Reflectance Fusion Model.” Journal of Applied Remote Sensing 6 (1): 063507. doi:10.1117/1.JRS.6.063507.
  • Munaro, L. B., T. J. Hefley, E. DeWolf, S. Haley, A. K. Fritz, G. Zhang, L. A. Haag, A. J. Schlegel, J. T. Edwards, and D. Marburger. 2020. “Exploring Long-Term Variety Performance Trials to Improve Environment-Specific genotype× Management Recommendations: A Case-Study for Winter Wheat.” Field Crops Research 255: 107848. doi:10.1016/j.fcr.2020.107848.
  • Panteras, G., and G. Cervone. 2018. “Enhancing the Temporal Resolution of Satellite-Based Flood Extent Generation Using Crowdsourced Data for Disaster Monitoring.” International Journal of Remote Sensing 39 (5): 1459–1474. doi:10.1080/01431161.2017.1400193.
  • Ren, K., W. Sun, X. Meng, G. Yang, J. Peng, and J. Huang. 2021. “A Locally Optimized Model for Hyperspectral and Multispectral Images Fusion.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–15. doi:10.1109/TGRS.2021.3133670.
  • Shengbiao, W., J. Wang, Z. Yan, G. Song, Y. Chen, M. Qin, M. Deng, W. Yuntao, Y. Zhao, and Z. Guo. 2021. “Monitoring Tree-Crown Scale Autumn Leaf Phenology in a Temperate Forest with an Integration of PlanetScope and Drone Remote Sensing Observations.” ISPRS Journal of Photogrammetry and Remote Sensing 171: 36–48. doi:10.1016/j.isprsjprs.2020.10.017.
  • Shen, M., Y. Tang, J. Chen, X. Zhu, and Y. Zheng. 2011. “Influences of Temperature and Precipitation Before the Growing Season on Spring Phenology in Grasslands of the Central and Eastern Qinghai-Tibetan Plateau.” Agricultural and Forest Meteorology 151 (12): 1711–1722. doi:10.1016/j.agrformet.2011.07.003.
  • Shi, W., D. Guo, and H. Zhang. 2022. “A Reliable and Adaptive Spatiotemporal Data Fusion Method for Blending Multi-Spatiotemporal-Resolution Satellite Images.” Remote Sensing of Environment 268: 112770. doi:10.1016/j.rse.2021.112770.
  • Song, D.-X., C. Huang, H. Tao, M. Feng, L. Ainong, L. Sike, Y. Pang, W. Hao, A. Rashid Mohamed Shariff, and J. R. Townshend. 2021. “Very Rapid Forest Cover Change in Sichuan Province, China: 40 Years of Change Using Images from Declassified Spy Satellites and Landsat.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14: 10964–10976. doi:10.1109/JSTARS.2021.3121260.
  • Song, H., Q. Liu, G. Wang, R. Hang, and B. Huang. 2018. “Spatiotemporal Satellite Image Fusion Using Deep Convolutional Neural Networks.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11 (3): 821–829. doi:10.1109/JSTARS.2018.2797894.
  • Sun, W., K. Liu, G. Ren, W. Liu, G. Yang, X. Meng, and J. Peng. 2021. “A Simple and Effective Spectral-Spatial Method for Mapping Large-Scale Coastal Wetlands Using China ZY1-02D Satellite Hyperspectral Images.” International Journal of Applied Earth Observation and Geoinformation 104: 102572. doi:10.1016/j.jag.2021.102572.
  • Sun, W., K. Ren, X. Meng, G. Yang, C. Xiao, J. Peng, and J. Huang. 2022. “MLR-DBPFN: A Multi-Scale Low Rank Deep Back Projection Fusion Network for Anti-Noise Hyperspectral and Multispectral Image Fusion.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–14. doi:10.1109/TGRS.2022.3231215.
  • Sun, W., G. Yang, J. Peng, X. Meng, K. He, L. Wei, L. Heng-Chao, and D. Qian. 2021. “A Multiscale Spectral Features Graph Fusion Method for Hyperspectral Band Selection.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–12. doi:10.1109/TGRS.2021.3102246.
  • Tan, Z., P. Yue, D. Liping, and J. Tang. 2018. “Deriving High Spatiotemporal Remote Sensing Images Using Deep Convolutional Network.” Remote Sensing 10 (7): 1066. doi:10.3390/rs10071066.
  • Wang, Q., and P. M. Atkinson. 2018. “Spatio-Temporal Fusion for Daily Sentinel-2 Images.” Remote Sensing of Environment 204: 31–42. doi:10.1016/j.rse.2017.10.046.
  • Weisheng, L., D. Cao, Y. Peng, and C. Yang. 2021. “MSNet: A Multi-Stream Fusion Network for Remote Sensing Spatiotemporal Fusion Based on Transformer and Convolution.” Remote Sensing 13 (18): 3724. doi:10.3390/rs13183724.
  • Weisheng, L., X. Zhang, Y. Peng, and M. Dong. 2020. “DMNet: A Network Architecture Using Dilated Convolution and Multiscale Mechanisms for Spatiotemporal Fusion of Remote Sensing Images.” IEEE Sensors Journal 20 (20): 12190–12202. doi:10.1109/JSEN.2020.3000249.
  • Xin, W., D. Hong, and J. Chanussot. 2022. “UIU-Net: U-Net in U-Net for Infrared Small Object Detection.” IEEE Transactions on Image Processing 32: 364–376. doi:10.1109/TIP.2022.3228497.
  • Yang, G., K. Huang, W. Sun, X. Meng, D. Mao, and G. Yong. 2022. “Enhanced Mangrove Vegetation Index Based on Hyperspectral Images for Mapping Mangrove.” ISPRS Journal of Photogrammetry and Remote Sensing 189: 236–254. doi:10.1016/j.isprsjprs.2022.05.003.
  • Yin, G., L. Ainong, H. Jin, and J. Bian. 2018. “Spatiotemporal Fusion Through the Best Linear Unbiased Estimator to Generate Fine Spatial Resolution NDVI Time Series.” International Journal of Remote Sensing 39 (10): 3287–3305. doi:10.1080/01431161.2018.1439202.
  • Yin, Z., W. Penghai, G. M. Foody, W. Yanlan, Z. Liu, D. Yun, and F. Ling. 2020. “Spatiotemporal Fusion of Land Surface Temperature Based on a Convolutional Neural Network.” IEEE Transactions on Geoscience and Remote Sensing 59 (2): 1808–1822. doi:10.1109/TGRS.2020.2999943.
  • Yuan, Q., Y. Wei, X. Meng, H. Shen, and L. Zhang. 2018. “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 11 (3): 978–989. doi:10.1109/JSTARS.2018.2794888.
  • Zhang, W., L. Ainong, H. Jin, J. Bian, Z. Zhang, G. Lei, Z. Qin, and C. Huang. 2013. “An Enhanced Spatial and Temporal Data Fusion Model for Fusing Landsat and MODIS Surface Reflectance to Generate High Temporal Landsat-Like Data.” Remote Sensing 5 (10): 5346–5368. doi:10.3390/rs5105346.
  • Zhang, Y., S. De Backer, and P. Scheunders. 2009. “Noise-Resistant Wavelet-Based Bayesian Fusion of Multispectral and Hyperspectral Images.” IEEE Transactions on Geoscience and Remote Sensing 47 (11): 3834–3843. doi:10.1109/TGRS.2009.2017737.
  • Zhang, Y., Y. Tian, Y. Kong, B. Zhong, and F. Yun. 2020. “Residual Dense Network for Image Restoration.” IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (7): 2480–2495. doi:10.1109/TPAMI.2020.2968521.
  • Zheng, K., L. Gao, D. Hong, B. Zhang, and J. Chanussot. 2021. “NonRegsrnet: A Nonrigid Registration Hyperspectral Super-Resolution Network.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–16. doi:10.1109/TGRS.2021.3135501.
  • Zheng, K., L. Gao, W. Liao, D. Hong, B. Zhang, X. Cui, and J. Chanussot. 2020. “Coupled Convolutional Neural Network with Adaptive Response Function Learning for Unsupervised Hyperspectral Super Resolution.” IEEE Transactions on Geoscience and Remote Sensing 59 (3): 2487–2502. doi:10.1109/TGRS.2020.3006534.
  • Zheng, Y., H. Song, L. Sun, W. Zebin, and B. Jeon. 2019. “Spatiotemporal Fusion of Satellite Images via Very Deep Convolutional Networks.” Remote Sensing 11 (22): 2701. doi:10.3390/rs11222701.
  • Zhou, W., and A. C. Bovik. 2002. “A Universal Image Quality Index.” IEEE Signal Processing Letters 9 (3): 81–84. doi:10.1109/97.995823.
  • Zhou, J., W. Sun, X. Meng, G. Yang, K. Ren, and J. Peng. 2022. “Generalized Linear Spectral Mixing Model for Spatial–Temporal–Spectral Fusion.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–16. doi:10.1109/TGRS.2022.3188501.
  • Zhu, X., F. Cai, J. Tian, and T. Kay-Ann Williams. 2018. “Spatiotemporal Fusion of Multisource Remote Sensing Data: Literature Survey, Taxonomy, Principles, Applications, and Future Directions.” Remote Sensing 10 (4): 527. doi:10.3390/rs10040527.
  • Zhu, X., J. Chen, F. Gao, X. Chen, and J. G. Masek. 2010. “An Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model for Complex Heterogeneous Regions.” Remote Sensing of Environment 114 (11): 2610–2623. doi:10.1016/j.rse.2010.05.032.
  • Zhu, X., E. H. Helmer, F. Gao, D. Liu, J. Chen, and M. A. Lefsky. 2016. “A Flexible Spatiotemporal Method for Fusing Satellite Images with Different Resolutions.” Remote Sensing of Environment 172: 165–177. doi:10.1016/j.rse.2015.11.016.
  • Zurui, A., Y. Sun, X. Pan, and Q. Xin. 2022. “Deep Learning-Based Spatiotemporal Data Fusion Using a Patch-To-Pixel Mapping Strategy and Model Comparisons.” IEEE Transactions on Geoscience and Remote Sensing 60: 1–18. doi:10.1109/TGRS.2022.3154406.

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