基本介绍
- 石茜,国家自然科学基金优秀青年基金获得者,博士生导师。从事遥感图像智能解译工作,荣获WGDC2022全球青年科学家称号。目前已发表SCI期刊论文50余篇(共计Google引用1000余次)。主持国家自然科学基金项目3项、广东省自然科学面上项目1项,广州市基础与应用研究项目1项,中国博士后科学基金面上项目1项,参与国家自然科学基金重点、国际合作、重大研究计划多项,担任IEEE GRSL、Remote Sensing 和IEEE JSTARS的期刊编委与副主编,当选IEEE地球科学与遥感学会广州分会主席。
了解更多信息请关注公众号:IMARS遥感大数据智能挖掘与分析(内附遥感影像目标检测数据集、场景分类数据集,语义分割数据集,变化检测数据集,全地类图斑数据,全国建筑物矢量数据集,已发表论文链接及代码)
数据分享09期|东亚区域建筑物矢量数据 (中国,日本,韩国,朝鲜和蒙古 链接:https://pan.baidu.com/s/1OLoK0pGHxbwpLSYrGzlQ6w 提取码:8ju2)
核心理念
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点滴积累,让时间见证卓越
研究方向
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智慧农业
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农业种植大模型
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农作物表型识别
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农业标准化种植
教育与研究经历
- 2023/05—至今 中山大学 地理科学与规划学院 教授 博导
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2018/08—2023/05 中山大学 地理科学与规划学院 副教授 博导
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2015/09—2018/07 中山大学 地理科学与规划学院 博士后 (合作导师:刘小平教授)
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2010/09—2015/06 测绘遥感信息工程国家重点实验室(武汉大学) 博士 (导师:张良培教授,杜博教授)
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2006/09—2010/07 武汉大学 遥感信息工程学院 学士
相关新闻链接:从“99次失败”到副教授,中山大学老师说出了成功的打开方式
IMARS课题组,加入我们~~~~
主要代表性论文
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Sun, L, Yang, T, Lou, Y, Shi, Q*(通讯作者), Zhang, L. Paddy Rice Mapping Based on Phenology Matching and Cultivation Pattern Analysis Combining Multi-Source Data in Guangdong, China. J Remote Sens. 2024;4:0152. DOI:10.34133/remotesensing.0152. (IF=9.1, 中科院JCR1区)
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Shi, Q*(通讯作者), Zhu, J, Liu, Z, Guo, H, Gao, S, Liu, M, Liu, Z, Liu, X. The Last Puzzle of Global Building Footprints—Mapping 280 Million Buildings in East Asia Based on VHR Images. J Remote Sens. 2024;4:0138. DOI:10.34133/remotesensing.0138. (IF=9.1, 中科院JCR1区)
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Liu, M., Lin, S., Zhong, Y., Shi, Q*(通讯作者), Li, J. A Memory-Guided Network and a Novel Dataset for Cropland Semantic Change Detection. IEEE Trans Geosci Remote Sens. 2024;62:4410013. DOI: 10.1109/TGRS.2024.3421654. (IF=8.5, 中科院JCR1区)
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Cai, Y, Shi, Q*(通讯作者), Liu, X. Spatiotemporal Mapping of Surface Water Using Landsat Images and Spectral Mixture Analysis on Google Earth Engine. J Remote Sens. 2024;4:0117.DOI:10.34133/remotesensing.0117 (IF=9.1, 中科院JCR1区)
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Li H, Jiang Q, Liu L, Shi, Q*(通讯作者), “Integrating bi-temporal VHR optical and long-term SAR images for built-up area change detection”. International Journal of Digital Earth, 2024, 17(1): 2316109.(IF=5.3,中科院JCR1区)
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Sun L, Lou Y, Shi, Q*(通讯作者), Zhang L. 2024. “Spatial domain transfer: Cross-regional paddy rice mapping with a few samples based on Sentinel-1 and Sentinel-2 data on GEE”. International Journal of Applied Earth Observation and Geoinformation, 128: 103762. (IF= 6.2, 中科院JCR1区)
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Shi, Q*(通讯作者), He, D, Liu, Z, Liu,X, Xue, J. Globe230k: A Benchmark Dense-Pixel Annotation Dataset for Global Land Cover Mapping. J Remote Sens. 2023;3:0078.DOI:10.34133/remotesensing.0078 (IF=9.1, 中科院JCR1区)
- Cai,Y, Shi, Q*(通讯作者), Xu, X, Liu, X A novel approach towards continuous monitoring of forest change dynamics in fragmented landscapes using time series Landsat imagery, International Journal of Applied Earth Observation and Geoinformation, Volume 118, 2023,103226, ISSN 1569-8432,https://doi.org/10.1016/j.jag.2023.103226. (IF= 6.2, 中科院JCR1区)
- He D, Shi, Q*(通讯作者), Xue J, Atkinson P M, Liu X. 2023. "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. (IF= 14.2,中科院JCR1区)
- Shi, Q., Liu, M., Marinoni, A., and Liu, X.: UGS-1m: fine-grained urban green space mapping of 31 major cities in China based on the deep learning framework, Earth System Science Data, 15, 555–577, 2023, https://doi.org/10.5194/essd-15-555-2023. (IF=10.1,中科院JCR1区)
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Liu, M, Shi, Q*(通讯作者),Li, J and Chai, Z, "Learning Token-aligned Representations with Multi-model Transformers for Different-resolution Change Detection," in IEEE Transactions on Geoscience and Remote Sensing, 2022, doi: 10.1109/TGRS.2022.3200684.
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Liu, M, Shi, Q*(通讯作者), Chai, Z and Li, J, "PA-Former: Learning Prior-aware Transformer for Remote Sensing Building Change Detection," in IEEE Geoscience and Remote Sensing Letters, 2022, doi: 10.1109/LGRS.2022.3200396.
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He, D, Shi, Q*(通讯作者), Liu, X, Zhang, L, Zhong, Y, Generating 2m fine-scale urban tree cover product over 33 metropolises in China based on deep context-aware sub-pixel mapping network, International Journal of Applied Earth Observation and Geoinformation, 2021. (IF= 5.993, 中科院JCR1区)
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Xu, X, Liu, X, Li, X, Shi, Q*(通讯作者), Chen, Y, Ai, B. Global Snow Depth Retrieval from Passive Microwave Brightness Temperature with Machine Learning Approach, IEEE Transactions on Geoscience and Remote Sensing, 2021. (IF= 5.855 中科院JCR2区)
- Guo, H, Shi, Q*(通讯作者), Marinoni, A, Du, B, Zhang, L, Deep building footprint update network: A semi-supervised method for updating existing building footprint from bi-temporal remote sensing images, Remote Sensing of Environment, Volume 264, 2021.(IF= 13.5,中科院JCR1区)
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Yang, J, Shi, Q*(通讯作者), Menenti, M, Wong, M, Wu, Z, Zhao, Q, Abbas, S, Xu, Y, Observing the impact of urban morphology and building geometry on the thermal environment by high spatial resolution thermal images, Urban Climate, 2021. (IF= 3.834, 中科院JCR2区)
- Liu, M, Shi, Q*(通讯作者), He, D, Liu, X and Zhang, L. Super-resolution-based Change Detection Network with Stacked Attention Module for Images with Different Resolutions, IEEE Transactions on Geoscience and Remote Sensing, 2021,doi:10.1109/TGRS.2021.3091758. (IF= 5.855 中科院JCR2区)
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Shi, Q, Liu, M, Liu, X, Wang, F, Zhang, L. A Deeply-supervised Attention Metric-based Network and an Open Aerial Imagery Dataset for Remote Sensing Change Detection, IEEE Transactions on Geoscience and Remote Sensing, 2021, doi:10.1109/TGRS.2021.3085870 (IF= 5.855 中科院JCR2区)
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Deng, W, Shi, Q*(通讯作者) and Li,J, "Attention Gate Based Encoder-Decoder Network for Automatical Building Extraction," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.14, pp. 2611 - 2620, 2021. doi: 10.1109/JSTARS.2021.3058097. (IF= 3.827, 中科院2区)
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He, D, Shi, Q*(通讯作者), Liu, X, Zhong, Y, Deep Sub-Pixel Mapping based on Semantic Information Modulated Network for Urban Land Use Mapping, IEEE Transactions on Geoscience and Remote Sensing, 2021. doi:10.1109/TGRS.2021.3050824. (IF = 5.855, 中科院JCR2区)
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Chen, X, Yu, S, Gong, X, Shi Q*(通讯作者). EC-SAGINs: Edge Computing-enhanced Space-Air-Ground Integrated Networks for Internet of Vehicles, IEEE Internet of Things Journal, 2021.doi:10.1109/JIOT.2021.3052542 (IF = 9.936, 中科院JCR1区)
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Shi, Q, Tang, X, Yang, T, Liu, R*. Hyperspectral Image Denoising Using a 3D Attention Denoising Network, IEEE Transactions on Geoscience and Remote Sensing, 2020. doi: 10.1109/TGRS.2020.3045273. ( IF = 5.855, 中科院JCR2区)
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Shi, Q and Chen, X, "Carpool for Big Data: Enabling Efficient Crowd Cooperation in Data Market for Pervasive AI," in IEEE Transactions on Vehicular Technology, vol.69, no.7, pp. 7778 - 7789, 2020.(IF= 5.855 中科院JCR2区)
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Shi, Q, Liu,M, Liu, X, Liu, P*, "Domain Adaption for Fine-grained Urban Village Extraction from Satellite Images," IEEE Geoscience and Remote Sensing Letters, vol.17, no.8, pp.1430-1434, 2020.(IF= 3.534, 中科院JCR2区)
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Sun,S, Shi Q*(通讯作者), Global spatio-temporal assessment of changes in multiple ecosystem services under four IPCC SRES land-use scenarios, Earth's Future, vol.8 no.10, 2020.(IF = 6.141, 中科院JCR1区)
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Liu, S, Shi Q*(通讯作者), Zhang, L, Few-Shot Hyperspectral Image Classification with Unknown Classes Using Multitask Deep Learning, IEEE Transactions on Geoscience and Remote Sensing, 2020. doi: 10.1109/TGRS.2020.3018879. ( IF = 5.855, 中科院JCR2区)
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Liu, S, Shi, Q*(通讯作者), Local Climate Zone Mapping as Remote Sensing Scene Classification Using Deep Learning: A Case Study of Metropolitan China, ISPRS Journal of Photogrammetry and Remote Sensing , vol.164, pp. 229-242, 2020.(IF= 7.319, 中科院JCR1区)
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Guo, H, Shi, Q*(通讯作者), Du, B, Zhang, L, Scene-Driven Multitask Parallel Attention Network for Building Extraction in High-Resolution Remote Sensing Images, IEEE Transactions on Geoscience and Remote Sensing, 2020, doi:10.1109/TGRS.2020.3014312. (IF= 5.855, 中科院JCR2区)
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Dou, X, Li, C, Shi, Q*(通讯作者), Liu, M. Super-Resolution for Hyperspectral Remote Sensing Images Based on the 3D Attention-SRGAN Network. Remote Sensing, vol.12, no.7, 1024, 2020.(IF = 4.509 中科院JCR2区)
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Liu S, Shi Q*(通讯作者), Multitask Deep Learning With Spectral Knowledge for Hyperspectral Image Classification, IEEE Geoscience and Remote Sensing Letters, vol. 17, no.12, pp. 2110 - 2114, 2020,doi: 10.1109/LGRS.2019.2962768..(IF= 3.833, 中科院JCR2区)
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Liu S, Luo H, Shi Q*(通讯作者), Active Ensemble Deep Learning for Polarimetric Synthetic Aperture Radar Image Classification, IEEE Geoscience and Remote Sensing Letters, pp.1-6, 2020.(IIF= 3.833 中科院JCR2区)
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He, Z, Shi Q*(通讯作者), “Object-oriented Mangrove Species Classification using Hyperspectral Data and 3D Siamese Residual Network”, IEEE Geoscience and Remote Sensing Letters, vol. 17, no.12, pp. 2150 - 2154, 2020. (IF= 3.534, 中科院JCR2区)
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Liu, P, Liu, X, Liu, M, Shi, Q*(通讯作者), Yang, J, Xu, X, and Zhang,Y, "Building Footprint Extraction from High-Resolution Images via Spatial Residual Inception Convolutional Neural Network," Remote Sensing, vol. 11, no.7, 2019.(IF = 4.118, 中科院JCR2区, ESI)
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Xiao, G, Wu, M, Shi, Q*(通讯作者), Zhou, Z, and Chen, X . "DeepVR: Deep Reinforcement Learning for Predictive Panoramic Video Streaming," IEEE Transactions on Cognitive Communication and Networking, vol.5, no,4, 2019. (IF= 5.646, 中科院JCR2区)
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Shi, Q, Zhang, Y, Liu X, Zhao, K. Regularized Transfer Learning for Hyperspectral Image Classification. IET Computer Vision, vol. 13, no.2, pp.188-193, 2019.
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Chen, X, Shi, Q*(通讯作者), Yang, L, and Xu. J. “ThriftyEdge: Resource-Efficient Edge Computing for Intelligent IoT Applications,” IEEE Networks, vol. 32, no.1, pp, 61 - 65, 2018. (IF=7.503, 中科院JCR1区)
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Shi, Q, Liu, X*, Li, X. “Road Detection from Remote Sensing Images by Generative Adversarial Networks. ” IEEE Access, vol. 6, pp. 25486-25494, 2018. (IF= 4.098, 中科院JCR2区)
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Shi, Q, Liu, X*, Huang, X*. “An Active Relearning Framework for Remote Sensing Image Classification,” IEEE Transactions on Geoscience and Remote sensing, vol. 56, no.6, pp.3468-3486, 2018. (IF=5.855, 中科院JCR2区)
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Shi, Q, Li, Jia., and Huang, X. Active learning approach for remote sensing imagery classification using spatial information, IEEE International Geoscience and remote sensing symposium(IGARSS), p1520-1523, 2016.
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Xu, X, Liu, X, Li, X, Xin, Q, Chen, Y, Shi, Q and Ai, B. Global snow cover estimation with microwave brightness temperature measurements and one-class in situ, observations. Remote Sensing of Environment, vol,182, pp.227-251, 2016. (IF= 13.5,中科院JCR1区)
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Xu, X, Li, X, Liu, X, Shen, H, and Shi, Q. Multimodal registration of remotely sensed images based on jeffrey’s divergence. Isprs Journal of Photogrammetry & Remote Sensing, vol.122, pp.97-115, 2016. (IF=10.6,中科院JCR1区)
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Shi, Q, Zhang, L*, and Du, B. "A Spatial Coherence based Batch-mode Active learning method for remote sensing images Classification”, IEEE Transactions on Image Processing, vol.24, no.7, pp.2037-2050, 2015. (IF = 6.79, 中科院JCR2区)
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Shi, Q, Zhang, L*, and Du, B. "Domain Adaptation Method with Low-Rank Reconstruction and Instance weighting label propagation for Remote Sensing Image Classification.". IEEE Transactions on Geoscience and Remote Sensing, vol.53, no.10, pp.1-13, 2015. (IF=8.2, 中科院JCR1区)
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Liu, X., Hu, G., Ai, B., Li, X and Shi, Q. A normalized urban areas composite index (nuaci) based on combination of dmspols and modis for mapping impervious surface area. Remote Sensing, vol.7, no.12, pp.17168-17189, 2015. (IF=4.2,中科院JCR2区)
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Shi, Q, Zhang, L*., and Du, B. "Semi-Supervised Discriminative Locally Enhanced Alignment for Hyperspectral Image Classification." IEEE Transactions on Geoscience and Remote Sensing, vol.51, no.9, pp.4800-4815, Sept. 2013.( IF = 8.2, 中科院JCR1区)
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Shi, Q, Zhang, L., and Du, B. "Spatial correlated information based batch mode active learning method for remote sensing image classification”. IEEE International Geoscience and remote sensing symposium(IGARSS), pp.3148-3151, 2013.
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Shi, Q., Zhang, L., Du, B. An novel active learning strategy for hyperspectral image classification. Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2012 4rd Workshop on , pp. 2341-2345, June 2012.
- 石茜,张良培,杜博,2012,一种基于局部判别正切空间排列的高光谱遥感图像降维方法,测绘学报,2012,41(3):417-420.
讲授课程
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遥感概论
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高光谱分析(双语)
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机器学习和地理数据挖掘
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遥感与地理信息系统导论
主要科研项目
[1] 国家自然科学基金优秀青年科学基金项目, 遥感图像分类与样本时空迁移, 项目编号42222106, 2023.1-2025.12, 200万,主持
[2] 国家自然科学基金面上项目,遥感图像数据与社会感知数据自适应深度融合的土地利用分类研究,项目编号61976234,2020.1-2023.12,61万元,主持。
[3] 广东省自然科学基金面上项目,基于遥感数据与社会感知数据融合的土地利用分类研究 ,项目编号2019A1515011057,2020.1-2022.9,10万元,主持。
[4] 广州市基础与应用基础研究项目,乡村振兴战略下空间优化布局研究,2020.1-2022.12,20万元,主持。
[5] 《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, 2021.3-2022.3,14.9万元,主持
[6] 耕地动态监测技术研究及监测结果分析评价采购项目(包1:耕地动态监测技术研究),2022.6-2024.6,99.8万元,主持
[7] 基于自然资源土地执法的照片样本库和自动识别技术研究项目,2022.12-2024.6,60万元,主持
[8] 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),2021.7-2023.7,29.986万元,主持
[9] 清远市裸露地表监测,2021.10-2021.12,26万元,主持
[10] 面向多云多雨地区的农作物类型识别算法研发,2022.3-2023.5,20万元,主持
[11] 面向建筑工程精细化自动识别系统开发及应用示范,2021.10-2023.12,200万元,主持
[12] GFJG-基于多源***研究服务,2020.6-2021.11,9.6万元,主持
[13] GFJG-1 融合***准确识别,2021.11-2023.10,300万元,主持