郭迪洲
讲师
办公室：
招生专业：
邮箱：
DizhouGuo@163.com
研究方向：
多源遥感影像时空数据融合与重建 基于深度学习的遥感智能处理 洪水灾害智能化检测
个人概况

代表性论文

[1] Guo,D.,Li, Z*., Gao, X., Gao, M., Yu, C., Zhang, C., & Shi, W.(2025) RealFusion: A reliable deep learning-based spatiotemporalfusion framework for generating seamless fine-resolutionimagery. Remote Sensing of Environment, 321, 114689.（中科院1区TOP）

[2] GuoD.,Li Z*., Jia Q., Hao, M. (2025) An improved ROBust OpTimization-based(iROBOT) fusion model for reliable spatiotemporal seamless remotesensing data reconstruction[J]. International Journal of AppliedEarth Observation and Geoinformation, 2025, 145: 104964.（中科院1区TOP）

代码/数据：https://github.com/Andy-cumt/iROBOT_spatiotemporal-fusion

[3] Guo,D.,Shi, W*., Hao, M., & Zhu, X. (2020). FSDAF 2.0: Improving theperformance of retrieving land cover changes and preserving spatialdetails. Remote Sensing of Environment, 248, 111973.（中科院1区TOP）

代码/数据：https://github.com/Andy-cumt/FSDAF2_GUI

[4]Shi, W., Guo,D*.,& Zhang, H. (2022). A reliable and adaptive spatiotemporal datafusion method for blending multi-spatiotemporal-resolution satelliteimages. Remote Sensing of Environment, 268, 112770.（中科院1区TOP）

代码/数据：https://github.com/Andy-cumt/RASDF_GUI

[5] Guo,D.,Shi, W*., Zhang, H., & Hao, M. (2022). A flexible object-levelprocessing strategy to enhance the weight function-basedspatiotemporal fusion method. IEEE Transactions on Geoscience andRemote Sensing, 60, 1-11.（中科院1区TOP）

代码/数据：https://github.com/Andy-cumt/Object-level-spatiotemporal-fusion-models

[6] Guo,D.,Shi, W*., Qian, F., Wang, S., & Cai, C. (2022). Monitoring thespatiotemporal change of Dongting Lake wetland by integrating Landsatand MODIS images, from 2001 to 2020. Ecological Informatics, 72,101848.（中科院1区TOP）

代码/数据：https://github.com/Andy-cumt/Dongting-Lake-Data-2001-2020

[7] Guo,D.,& Shi, W*. (2023). Object-Level Hybrid Spatiotemporal Fusion:Reaching a Better Trade-Off Among Spectral Accuracy, Spatial Accuracyand Efficiency. IEEE Journal of Selected Topics in Applied EarthObservations and Remote Sensing,16:8007-8021.（中科院2区TOP）

代码/数据：https://github.com/Andy-cumt/Object-level-spatiotemporal-fusion-models

[8] Guo,D.,& Shi, W*. (2023). A task decoupled framework for enhancing thedeep learning-based spatiotemporal fusion method. InternationalJournal of Remote Sensing, 44(13), 4163-4189.（中科院3区）

代码/数据：https://github.com/Andy-cumt/Spatiotemporal-fusion-dataset-DeepLearning


研究领域

多源遥感影像时空数据融合与重建

基于深度学习的遥感智能处理

洪水灾害智能化检测

开授课程

《计算机图形学》《遥感地学解译》《自然资源调查与遥感监测专题》

科研项目

[1]基于跨时空多模态融合的高分辨率无缝遥感影像重建方法研究，国自然青年科学基金项目，2026-2028，主持

[2]多云雾地区高时空分辨率无缝遥感影像重建方法研究，国家资助博士后研究人员计划，2025-2026，主持

[3]面向云污染场景的多模态遥感影像时空融合方法，中国博士后科学基金面上项目，2026-2027，主持

[4]面向秦岭地区全天候遥感精细监测的光学-SAR多模态影像时空融合方法研究，陕西省青年项目，2025-2026，主持

[5]基于多源遥感影像时空谱信息融合的薄云-厚云-云阴影协同去除方法研究，陕西省博士后项目，2025-2026，主持

[6]陕西秦岭北麓主体山水林田湖草沙一体化保护和修复工程子项目——生态环境监测与数字化工程建设，中国山水工程子项目，林草动态监测负责人

[7]基于深度学习的时空无缝高空间分辨率遥感影像重建方法研究，中央高校基本科研业务费，2025-2026，主持

论文

代表性论文

[1] Guo,D.,Li, Z*., Gao, X., Gao, M., Yu, C., Zhang, C., & Shi, W.(2025) RealFusion: A reliable deep learning-based spatiotemporalfusion framework for generating seamless fine-resolutionimagery. Remote Sensing of Environment, 321, 114689.（中科院1区TOP）

[2] GuoD.,Li Z*., Jia Q., Hao, M. (2025) An improved ROBust OpTimization-based(iROBOT) fusion model for reliable spatiotemporal seamless remotesensing data reconstruction[J]. International Journal of AppliedEarth Observation and Geoinformation, 2025, 145: 104964.（中科院1区TOP）

代码/数据：https://github.com/Andy-cumt/iROBOT_spatiotemporal-fusion

[3] Guo,D.,Shi, W*., Hao, M., & Zhu, X. (2020). FSDAF 2.0: Improving theperformance of retrieving land cover changes and preserving spatialdetails. Remote Sensing of Environment, 248, 111973.（中科院1区TOP）

代码/数据：https://github.com/Andy-cumt/FSDAF2_GUI

[4]Shi, W., Guo,D*.,& Zhang, H. (2022). A reliable and adaptive spatiotemporal datafusion method for blending multi-spatiotemporal-resolution satelliteimages. Remote Sensing of Environment, 268, 112770.（中科院1区TOP）

代码/数据：https://github.com/Andy-cumt/RASDF_GUI

[5] Guo,D.,Shi, W*., Zhang, H., & Hao, M. (2022). A flexible object-levelprocessing strategy to enhance the weight function-basedspatiotemporal fusion method. IEEE Transactions on Geoscience andRemote Sensing, 60, 1-11.（中科院1区TOP）

代码/数据：https://github.com/Andy-cumt/Object-level-spatiotemporal-fusion-models

[6] Guo,D.,Shi, W*., Qian, F., Wang, S., & Cai, C. (2022). Monitoring thespatiotemporal change of Dongting Lake wetland by integrating Landsatand MODIS images, from 2001 to 2020. Ecological Informatics, 72,101848.（中科院1区TOP）

代码/数据：https://github.com/Andy-cumt/Dongting-Lake-Data-2001-2020

[7] Guo,D.,& Shi, W*. (2023). Object-Level Hybrid Spatiotemporal Fusion:Reaching a Better Trade-Off Among Spectral Accuracy, Spatial Accuracyand Efficiency. IEEE Journal of Selected Topics in Applied EarthObservations and Remote Sensing,16:8007-8021.（中科院2区TOP）

代码/数据：https://github.com/Andy-cumt/Object-level-spatiotemporal-fusion-models

[8] Guo,D.,& Shi, W*. (2023). A task decoupled framework for enhancing thedeep learning-based spatiotemporal fusion method. InternationalJournal of Remote Sensing, 44(13), 4163-4189.（中科院3区）

代码/数据：https://github.com/Andy-cumt/Spatiotemporal-fusion-dataset-DeepLearning


科技成果


荣誉奖励

2021年日内瓦国际发明展金奖

工作经历

2024.6-至今长安大学 讲师