个人简介：

杜守航，博士、副教授、博士生导师。

2021年博士毕业于北京大学地图学与地理信息系统专业。

中国测绘学会对地观测工作委员会委员，中国测绘学会智能化测绘工作委员会委员，中国测绘学会青年工作委员会委员。近年来，主持国家自然科学基金、中国博士后科学基金特别资助等项目15项，参与国家重点研发计划、企事业单位横向课题等项目20余项。发表一作/通讯论文32篇，其中SCI论文25篇，Remote Sensing of Environment（IF=12.3）、ISPRS Journal of Photogrammetry and Remote Sensing（IF=12.9）等中科院一区/TOP期刊论文13篇，ESI高被引1篇，论文被引用1800余次，授权发明专利4项，授权软件著作权2项。获全国“高校GIS新秀”等荣誉称号，成果入选《地球大数据支撑可持续发展目标报告（2021）》，获得2023年地理信息科技进步一等奖和2022年地理信息科技进步二等奖。担任《测绘工程》青年编委，RSE、TGRS、JSTARS、GRSL、JAG、CEUS、Cities、IJDE等SCI期刊审稿人。

主讲本科生《测量学基础》、《人工智能遥感应用》等课程。

电子邮件：dush@cumtb.edu.cn

个人学术主页：https://dushouhang.github.io//

研究方向：

1. 城市大数据智能理解与分析

2. 深度学习遥感影像智能解译

3. 自然资源监测与生态环境评价

代表性科研项目：

1. 国家自然科学基金项目，多模态数据的多维度特征融合与城市功能区精细提取研究，主持

2. 中国博士后科学基金特别资助项目，基于多模态数据融合与自监督对比学习的城市功能区提取，主持

3. 武汉大学测绘遥感信息工程国家重点实验室开放基金，基于全卷积神经网络的单视影像DSM生成方法研究，主持

4. 煤炭开采水资源保护与利用全国重点实验室开放基金，神东矿区高强度开采下“地表变形-植被扰动”时空演化规律研究，主持

5. 国家重点研发计划-政府间国际科技创新合作项目，时空大数据驱动的可持续发展城市人居环境监测评估与应用示范，参与

6. 国家重点研发计划课题，自然资源地表要素精准化遥感监测关键技术研究，参与

7. 北京市自然科学基金重点项目，气象与遥感耦合的多气候带农作物生产风险评估与区划关键技术研究，参与

荣誉奖励：

1. 2025，第八届全国高校GIS青年教师讲课竞赛一等奖

2. 2025，2025年全国高等学校测绘学科教学创新与育才能力大赛-青年教师讲课竞赛一等奖

3. 2025，第23届SuperMap杯高校GIS大赛优秀指导老师

4. 2024，中国矿业大学（北京）优秀班主任

5. 2024，中国矿业大学（北京）青年教师教学优秀奖

6. 2023，地理信息科技进步一等奖：矿山生态大数据挖掘与智能监管关键技术及应用，排名 8/20

7. 2023，绿色矿山科技进步一等奖：复杂场景矿山开采与修复活动卫星遥感智能监测关键技术与应用，排名7/15

8. 2023，中国矿业大学（北京）优秀班主任

9. 2023，第十四届北京市大学生测绘技能竞赛优秀指导教师奖

10. 2023，首届全国煤炭行业矿山AI大模型大赛优秀指导教师奖

11. 2022，地理信息科技进步二等奖：融合星-空-地-众源数据的城市更新重点户识别与动态监管关键技术及应用，排名6/12

12. 2022，中国矿业大学（北京）优秀本科生全程导师奖

13. 2020，高校GIS新秀奖

代表性第一作者/通讯作者论文：

1. Guo, T., Du, S.*, Wang, S., Liu, Z., Zhu, L., Zhang, J., Zhang X. & Du, S. (2026). A function-semantic oriented heterogeneous graph aggregation framework with weighted spatial relationships for urban functional zone mapping. Remote Sensing of Environment, 344, 115507. (SCI, IF= 12.3, JCR一区, 中科院一区TOP)

2. Du, S., Du, S., Liu, B., & Zhang, X. (2021). Mapping large-scale and fine-grained urban functional zones from VHR images using a multi-scale semantic segmentation network and object based approach. Remote Sensing of Environment, 261, 112480. (SCI, IF= 12.3, JCR一区, 中科院一区TOP， ESI高被引)

3. Du, S., Zhang, Y., Zou, Z., Xu, S., He, X., & Chen, S. (2017). Automatic building extraction from LiDAR data fusion of point and grid-based features. ISPRS Journal of Photogrammetry and Remote Sensing, 130, 294-307. (SCI, IF=12.9, JCR一区, 中科院一区TOP)

4. Du, S., Liu, H., Xing, J., Zhang, X., Zhang, J., Guan, X., & Du, S. (2025). Estimating Individual Building Heights by Integrating Spaceborne LiDAR and Multisource Remote Sensing Data: A CNN-Transformer Model and A Semi-Supervised Sample Augmentation Approach. IEEE Transactions on Geoscience and Remote Sensing.(SCI, IF= 9.4, JCR一区, 中科院一区TOP)

5. Du, S., Zhang, Y., Zhu, L., Wang, S., Liu, Z., Zhou, H., Zhang, X., & Du, S. (2025). A Multimodal Data Fusion Framework for Urban Functional Zone Mapping Based on Local-Global Information Enhancement andAdaptive Spatial Units: From Standard Datasets to Global City Validation. International Journal of Applied Earth Observation and Geoinformation.(SCI, IF= 8.2, JCR一区, 中科院一区TOP)

6. Du, S., Liu, H., Xing, J., & Du, S. (2024). Fusing multimodal data of nature-economy-society for large-scale urban building height estimation. International Journal of Applied Earth Observation and Geoinformation, 129, 103809. (SCI, IF= 8.2, JCR一区, 中科院一区TOP)

7. Du, S., Zhang, X., Lei, Y., Huang, X., Tu, W., Liu, B., Meng, Q., & Du, S. (2024). Mapping urban functional zones with remote sensing and geospatial big data: a systematic review. GIScience & Remote Sensing, 61(1), 2404900.(SCI, IF=6.8, JCR一区, 中科院一区TOP)

8. Du, S., Du, S., Liu, B., Zhang, X., & Zheng, Z. (2020). Large-scale urban functional zone mapping by integrating remote sensing images and open social data. GIScience & Remote Sensing, 57(3), 411-430. (SCI, IF=6.8, JCR一区, 中科院一区TOP)

9. Guo, L., Du, S.*, Sun, W., Fan, D., & Wu, Y. (2025). Multi-scale impact of urban building function and 2D/3D morphology on urban heat island effect: a case study in Shanghai, China. Energy and Buildings, 338, 115719.(SCI, IF= 8.0, JCR一区, 中科院二区TOP)

10. Du, S.*, Zhang, Y., Sun, W., & Liu, B. (2024). Quantifying heterogeneous impacts of 2D/3D built environment on carbon emissions across urban functional zones: A case study in Beijing, China. Energy and Buildings, 319, 114513. (SCI, IF= 8.0, JCR一区, 中科院二区TOP)

11. Huang, Y., Du, S.*, Gu, J., Fan, D., Sun, W., & Guo, T. (2026). Layered Scene-Aware Network: Fusing Multimodal Data for Fine-Grained Urban Functional Zone Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.(SCI, IF= 6.3, JCR一区)

12. Du, S., Xing, J., Wang, S., Wei, L., & Zhang, Y. (2024). STMNet: Scene Classification-Assisted and Texture Feature-Enhanced Multi-Scale Network for Large-Scale Urban Informal Settlement Extraction from Remote Sensing Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. (SCI, IF= 6.3, JCR一区)

13. Wang, C., Du, S.*, Sun, W., & Fan, D. (2023). Self-supervised learning for high-resolution remote sensing images change detection with variational information bottleneck. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 5849-5866. (SCI, IF= 6.3, JCR一区,)

14. Du, S., Wang, S., Hua, Y., Peng, S., Qin, F., Li, X., & Wu, Y. (2024). MGLI-Former: a multi-scale and global-local information interactive attention transformer for urban shantytown extraction. International Journal of Digital Earth, 17(1), 1-27. (SCI, IF=5.4, JCR一区)

15. Du, S., Du, S., Liu, B., & Zhang, X. (2021). Incorporating DeepLabv3+ and object-based image analysis for semantic segmentation of very high resolution remote sensing images. International Journal of Digital Earth, 14(3), 357-378. (SCI, IF=5.4, JCR一区)

16. Du, S., Xing, J., Wang, S., Xiao, X., Li, J., & Liu, H. (2024). LUMNet: Land Use Knowledge Guided Multiscale Network for Height Estimation from Single Remote Sensing Images. IEEE Geoscience and Remote Sensing Letters. (SCI, IF= 4.8, JCR一区)

17. Li, J., Xing, J., Du, S.*, Du, S., Zhang, C., & Li, W. (2022). Change detection of open-pit mine based on siamese multiscale network. IEEE Geoscience and Remote Sensing Letters, 20, 1-5. (SCI, IF= 4.8, JCR一区)

18. Du, S., Xing, J., Du, S., Cui, X., Xiao, X., Li, W., & Wang, S. (2023). IMG2HEIGHT: height estimation from single remote sensing image using a deep convolutional encoder-decoder network. International Journal of Remote Sensing, 44(18), 5686-5712. (SCI, IF= 2.6, JCR二区)