基本介绍
何达，工学博士（摄影测量与遥感专业），长期从事高光谱/多光谱/高分辨率遥感影像智能理解与语义推理、多源数据融合、超分辨率重建、视觉语言大模型、智慧城市等研究。主持国家自然科学基金、国家重点研发计划子课题、广东省自然科学基金、博士后科学基金及GF项目等；获2023年、2024年中国地理信息科技进步二等奖、2021年全国博士后创新创业大赛优胜奖，2018年中国测绘学会测绘科技进步一等奖。近五年，在RSE, JAG, IEEE TGRS, GIS&RS, JRS等遥感领域高水平期刊发表论文30余篇（第一或通讯作者18篇，11篇中科院一区TOP），其中3篇入选ESI高被引论文（前1%）,1篇入选ESI热点论文（前0.1%）；担任 IEEE TGRS, ISPRS P&RS, IEEE JSTAR, IEEE GRSL, IEEE Access, RS等期刊审稿人，担任IEEE Guangzhou Section副主席。
欢迎有遥感、地理信息系统、计算机科学与技术、数学、测绘等专业背景的学生保送（报考）或交流!
更鼓励本科生积极申请报名参与本团队的科学研究，只要有想法、勤编程，就有机会发表SCI论文！
公开数据产品
1.全球1m分辨率大规模多模态遥感标注数据集（Globe230k）
研究方向
- 高光谱/多光谱/高分辨率遥感影像智能处理
- 视觉语言基础模型
- 知识图谱
- 亚像元制图
- 深度学习
- 时空融合
- 变化检测
- 智慧城市
- 智慧农业
教育与研究经历
·2023.7-至今 中山大学 地理科学与规划学院，副教授
2020.8-2023.7 中山大学 地理科学与规划学院，博士后
·2015.9-2020.6 武汉大学 测绘遥感信息工程国家重点实验室，博士
·2011.9-2015.6 武汉大学 遥感信息工程学院 ，学士
教学成果
指导2019级本科生开展深度学习目标检测算法研究、可解释性亚像元制图算法等科学研究发表SCI论文3篇。
[1] Xue Jingqian(2019级中大地理学院本科生), He Da*, Liu Mengwei, Shi Qian. Dual Network Structure With Interweaved Global-Local Feature Hierarchy for Transformer-Based Object Detection in Remote Sensing Image. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, 2022. DOI: 10.1109/JSTARS.2022.3198577.(SCI, IF= 4.7)
[2] He Da, Shi Qian*, Xue Jingqian(2019级中大地理学院本科生), Atkinson Peter M., Liu Xiaoping. Very fine spatial resolution urban land cover mapping using an explicable sub-pixel mapping network based on learnable spatial correlation. Remote Sensing of Environment, 299, 113884, 2023, DOI: 10.1016/j.rse.2023.113884(SCI, 中科院一区Top, IF= 11.1)
[3] Shi Qian, He Da*, Liu Zhengyu, Liu Xiaoping, Xue Jingqian(2019级中大地理学院本科生). Globe230k: A Benchmark Dense-Pixel Annotation Dataset for Global Land Cover Mapping. Journal of Remote Sensing, 3, 0078, 2023. (通讯, SCI, IF= 8.8, 中科院一区Top) (大规模多模态高分辨率遥感标注数据集，新闻宣传链接 https://mp.weixin.qq.com/s/gDC4O62iGS7hHVLhcmmxtg)
鼓励本科生积极申请报名参与本团队的科学研究，只要有想法、肯坚持，就有机会发表SCI论文！
论文专著
[1] He Da, Liu Xiaoping, Shi Qian, Zheng Yue. Visual-language reasoning segmentation (LARSE) of function-level building footprint across Yangtze River Economic Belt of China. Sustainable Cities and Society, 127, 106439, 2025, DOI: 10.1016/j.scs.2025.106439(一作, SCI, IF= 10.5, 中科院一区Top)
[2] He Da, Shi Qian*, Xue Jingqian, Atkinson Peter M., Liu Xiaoping. Very fine spatial resolution urban land cover mapping using an explicable sub-pixel mapping network based on learnable spatial correlation. Remote Sensing of Environment, 299, 113884, 2023, DOI: 10.1016/j.rse.2023.113884(一作, SCI, IF= 11.1, 中科院一区Top)
[3] Shi Qian, He Da*, Liu Zhengyu, Liu Xiaoping, Xue Jingqian. Globe230k: A Benchmark Dense-Pixel Annotation Dataset for Global Land Cover Mapping. Journal of Remote Sensing, 3, 0078, 2023, DOI: 10.34133/remotesensing.0078 (通讯, SCI, IF= 8.8, 中科院一区Top) (大规模多模态高分辨率遥感标注数据集，新闻宣传链接 https://mp.weixin.qq.com/s/gDC4O62iGS7hHVLhcmmxtg)
[4] He Da, Zhong Yanfei*. Deep hierarchical pyramid network with high-frequency-aware differential architecture for super-resolution mapping. IEEE Transactions on Geoscience and Remote Sensing, 61, 5503815, 2023. DOI：10.1109/TGRS.2023.3243927 (一作, SCI, IF=7.5, 中科院一区Top)
[5] Zhou Chengle, Shi Qian, He Da*, Tu Bing, Li Haoyang, Plaza Antonio. Spectral-spatial sequence characteristics-based convolutional transformer for hyperspectral change detection. CAAI Transactions on Intelligence Technology, early excess, 2023. DOI: 10.1049/cit2.12226. (通讯, SCI, IF=8.4, 中科院一区Top)
[6] He Da, Shi Qian*, Liu Xiaoping, Zhong Yanfei, Xia Guisong, Zhangliangpei. Generating annual high resolution land cover products for 28 metropolises in China based on a deep super-resolution mapping network using Landsat imagery. GIScience & Remote Sensing, 59(1), 2022. DOI: 10.1080/15481603.2022.2142727. (一作, SCI, IF=6.0, 中科院一区Top, ESI高被引论文)
[7] He Da, Shi Qian*, Liu Xiaoping, Zhong Yanfei, Zhang Liangpei. Generating 2m fine-scale urban tree cover product over 34 metropolises in China based on deep context-aware sub-pixel mapping network, International Journal of Applied Earth Observation and Geoinformation, 106, 102667, 2022. DOI: 10.1016/j.jag.2021.102667 (一作, SCI, IF= 7.6, 中科院一区Top, ESI高被引论文)
[8] He Da, Shi Qian*, Liu Xiaoping, Zhong Yanfei, Zhang Xinchang. Deep Sub-Pixel Mapping based on Semantic Information Modulated Network for Urban Land Use Mapping, IEEE Transactions on Geoscience and Remote Sensing, 59(12), 10628 - 10646, 2021. DOI：10.1109/TGRS.2021.3050824 (SCI, IF=7.5, 中科院一区Top, ESI高被引论文，ESI热点论文)
[9] He Da, Zhong Yanfei*, Zhang Liangpei. Deep convolutional neural network framework for sub-pixel mapping, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, issue 11, 9518 - 9539, 2020. DOI: 10.1109/TGRS.2020.3032475 (一作, SCI, IF=7.5, 中科院一区Top, ESI高被引论文)
[10] He Da, Zhong Yanfei*, Zhang Liangpei. Spectral-spatial-temporal MAP-based sub-pixel mapping for land-cover change detection, IEEE Transactions on Geoscience and Remote Sensing, vol. 58, issue 3, pp.1696- 1717, 2020. DOI: 10.1109/TGRS.2019.2947708. (一作, SCI, IF=7.5, 中科院一区Top)
[11] He Da, Zhong Yanfei*, Zhang Liangpei. Spatiotemporal Subpixel Geographical Evolution Mapping. IEEE Transactions on Geoscience and Remote Sensing, vol. 57, issue 4, pp.2198-2220, 2019. DOI: 10.1109/TGRS.2018.2872081. (一作, SCI, IF=7.5, 中科院一区Top)
[12] Liu Zihong, He Da*, Shi Qian, Cheng Xiao. NDVI time-series data reconstruction for spatial-temporal dynamic monitoring of Arctic vegetation structure. Geo-spatial Information Science, 2024, DOI: 10.1080/10095020.2024.2336602 (通讯作者, SCI, 中科院二区, IF=4.4)
[13] Chai Zhuoqun, Liu Mengxi, Shi Qian, Zhang Yuanyuan, Zuo, Minglin, He Da*. Fine-grained urban village extraction by mask transformer from high-resolution satellite images in pearl river delta. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 13657–13668, 2024, DOI: 10.1109/JSTARS.2024.3434487(通讯作者, SCI, 中科院二区Top, IF=4.7)
[14] Xue Jingqian, He Da*, Liu Mengwei, Shi Qian. Dual Network Structure With Interweaved Global-Local Feature Hierarchy for Transformer-Based Object Detection in Remote Sensing Image. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, 2022. DOI: 10.1109/JSTARS.2022.3198577.((通讯作者, SCI, 中科院二区Top, IF=4.7)
[15] He Da, Zhong Yanfei*, Shi Qian, Liu Xiaoping, Zhang Liangpei. Generating continuous fine-scale land cover mapping by edge-guided maximum a posteriori based spatiotemporal sub-pixel mapping. Science of Remote Sensing, 10041, 2022. DOI: 10.1016/j.srs.2022.100041.(一作, SCI, IF=5.7, 中科院二区)
[16] He Da, Shi Qian, Liu Xiaoping, Zhong Yanfei, Liu Xiaoding. Spectral-spatial Fused Sub-pixel Mapping Based on Deep Neural Network, IEEE Geoscience and Remote Sensing Letters, 19, 6004105, 2021. DOI：10.1109/LGRS.2021.3101499 (一作, SCI, IF=4.0, 中科院三区)
[17] Zhong Yanfei, He Da*, Luo Bin, Zhang Liangpei. Contemporary liquid brine exploration on Mars: From spectral unmixing to subpixel mapping. Earth and Space Science, vol.6, issue 3，pp.433-466, 2019. DOI: 10.1029/2018EA000526. (通讯, SCI, IF=2.9, 中科院三区)
[18] He Da, Zhong Yanfei*, Feng Ruyi, et al. Spatial-Temporal Sub-Pixel Mapping Based on Swarm Intelligence Theory. Remote Sensing, vol. 8, issue 12, pp.894, 2016. DOI: 10.3390/rs8110894. (一作, SCI, IF=4.2, 中科院二区)
[19] Li Bingjie, Xu Xiaocong, Liu Xiaoping, Shi Qian, Zhuang Haoming, Cai Yaotong, He Da. An improved global land cover mapping in 2015 with 30m resolution (GLC-2015) based on a multisource product-fusion approach, Earth System Science Data, 1-35, 2022. (SCI, IF=11.2, 中科院一区Top)
[20] Song Mi, Zhong Yanfei, Ma Ailong, He Da, Zhang Liangpei. Multiobjective Spatiotemporal Subpixel Mapping for Remote Sensing Imagery. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-17, 2024. (SCI, IF=7.5, 中科院一区Top)
[21] Mengxi Liu, Qian Shi, Andrea Marinoni, Da He, Xiaoping Liu, Liangpei Zhang. Super-resolution-based Change Detection Network with Stacked Attention Module for Images with Different Resolutions, IEEE Transactions on Geoscience and Remote Sensing, 2021. (SCI, IF=7.5, 中科院一区Top)
[22] Xue Jingqian, Zhang Ziheng, Zhou Yan, Yuan Lina, He Da, Liu Xiaoping, Geographic Prior Guided Sub-Pixel Mapping for Fine-Grained Urban Tree Cover Reconstruction, IEEE Geoscience and Remote Sensing Letters, 2025. (SCI, IF=4.0, 中科院三区)
[23] Zhou Wen, Ma Ailong, He Da, Zhong Yanfei. Learning Global Context and Fine Structures for Enhanced Hyperspectral Subpixel Mapping, IEEE Geoscience and Remote Sensing Letters, 2025. (SCI, IF=4.0, 中科院三区)
[24] Ma Ailong, Zhong Yanfei*, He Da, Zhang Liangpei. Multiobjective subpixel land-cover mapping. IEEE Transactions on Geoscience and Remote Sensing, vol. 56, issue 1, pp.422-435, 2017. DOI: 10.1109/TGRS.2017.2748701. (SCI, IF=7.5, 中科院一区Top)
[25] Feng Ruyi, Zhong Yanfei*, Wu Yunyun, He Da, et al. Nonlocal Total Variation Subpixel Mapping for Hyperspectral Remote Sensing Imagery. Remote Sensing, vol. 8, issue 3, pp.250, 2016. DOI: 10.3390/rs8030250. (SCI, IF=7.5, 中科院二区)
[26] He Da, Zhong Yanfei, Shi Qian and Liu Xiaoping. Rethinking the High Frequency Components in Deep Sub-Pixel Mapping Network. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2021, pp. 5366-5369. DOI: 10.1109/IGARSS47720.2021.9553075.(EI)
[27] He Da, Zhong Yanfei, Zhang Liangpei. Sub-pixel intelligence mapping considering spatial-temporal attraction for remote sensing imagery. IEEE Geoscience and Remote Sensing Symposium (IGARSS), 2017. DOI: 10.1109/IGARSS.2017.8127025. (EI)
[28] He Da, Zhong Yanfei, Zhang Liangpei. Land cover change detection based on spatial-temporal sub-pixel evolution mapping: a case study for urban expansion. IEEE Geoscience and Remote Sensing Symposium (IGARSS), 2018. DOI: 10.1109/IGARSS.2018.8518423. (EI)
[29] Feng Ruyi, He Da, Zhong Yanfei, et al. Sparse representation based subpixel information extraction framework for hyperspectral remote sensing imagery. IEEE Geoscience and Remote Sensing Symposium(IGARSS), 2016. DOI: 10.1109/IGARSS.2016.7730832. (EI)
[30] Zhang Xinchang, Shi Qian, Sun Yin, Huang Jianfeng, He Da. The Review of Land Use/Land Cover Mapping AI Methodology and Application in the Era of Remote Sensing Big Data, Journal of Geodesy & Geoinformation Science, 7(3), 2024.
主要科研项目
[1] 国家自然科学基金青年科学基金项目，基于深度自注意力的高光谱遥感影像亚像元制图方法研究，项目编号 42201340，2023.01-2025.12, 主持。
[2] 国家科技部重点研发计划课题，任务驱动的多模态遥感大数据智能语义分析，2022.12-2026.12, 子课题负责人。
[3] 广东省自然科学基金面上项目，高光谱遥感影像神经关联推演亚像元制图方法研究，2025.1-2027.12，主持。
[4] 广东省基础与应用基础研究基金区域联合基金青年基金项目，顾及细节保真的遥感影像时空亚像元制图方法研究，项目编号 2020A1515110708，2020.10-2023.09，主持。
[5] 华东师范大学地理信息科学教育部重点实验室开放基金, 遥感影像城市树冠亚像元制图方法研究, 2023.07-2025.06, 主持。
[6] 中国博士后基金项目, 高光谱遥感影像混合像元深度分解与亚像元制图，项目编号 2020M683053, 2020.07-2022.06, 主持。
[7] 国家国防科技工业局项目, GFJG- 基于预训***识别技术, 2024.1-2025.12, 主持。
[8] 国家自然科学基金面上项目：“面向城乡融合的珠三角地区都市农业地域系统功能演化、空间重组及环境效应研究”, 项目编号42171193，2022.01-2025.12, 参与。
[9] 国家自然科学基金面上项目：“高光谱遥感影像深度非线性亚像元制图方法研究”，项目编号 42071350，2021.01-2024.12，参与。
[10] 国家自然科学基金优秀青年科学基金项目：“高光谱遥感地物识别与场景理解”，时间：2017.01-2019.12，参与。
[11] 国家重点研发计划课题：“国土资源与生态环境安全应急响应关键技术”，时间：2017.07-2021.07，参与。
[12] 中科院上海高等研究所项目：“光谱微纳卫星数据产品生产算法研究”，时间：2017.02-2017.12，参与。
[13] 广东省国土资源技术中心横向项目，卫星影像数据处理能力提升，时间：2024.4-2024.12，参与。
[14] 自然资源执法监测智能感知技术能力及土地卫片执法能力提升和立体感知服务系统顶层设计技术服务项目（二次）（包一：土地卫片执法及查处整改内业智能审核能力提升技术研究服务项目）, 2021.07-2023.07, 参与。
[15] 《基于深度学习的多源遥感信息桉树林精确自动提取方法研究》委托技术服务, 2021.03-2023.03, 参与。
获奖情况
[1] 中国地理信息产业协会地理信息科技进步奖，“工程建设项目用地智能审批与精准管控关键技术及应用”，二等奖，2024年。
[2] 东莞市高新技术产业协会，创新东莞科技进步奖二等奖，2024年。
[3] 中国地理信息产业协会地理信息科技进步奖，“特大城市国土空间规划智能监测与精准管控关键技术”，二等奖，2023年。
[4] 全国博士后创新创业大赛，创业赛赛道，“低空影像数据智能认知与决策”，优胜奖，2021年。
[5] 测绘科技进步一等奖“高光谱遥感数据分类关键技术及其典型应用”，2018年。
获奖情况
[1] 何达; 刘小平; 石茜 ; 基于视觉语言知识推理的建筑物功能识别方法、装置、设备及介质, 2024-11-25, 中国, CN202411688817.2
[2] 刘小平; 何达; 石茜 ; 一种基于地理实体的多模态遥感大数据智能语义分析系统, 2024-5-16, 中国, CN202410606707.0
