王雷，中国科学院空天信息创新研究院，研究员。担任中国科学院-发展中国家科学院空间减灾卓越中心秘书长，可持续发展大数据国际研究中心学术建设委员会、世界工程组织联合会减灾委员会等学术组织委员。主要从事森林扰动遥感监测与分析的科研工作，围绕森林扰动“时空分布检测、扰动因子判识、影响效用分析”等开展了系统性的研究。主持国家重点研发计划项目子课题、中国科学院A类先导专项专题等科研项目10余项；在Lancet、Science Advances、Remote Sensing of Environment等期刊发表SCI论文60余篇，其中第一/通讯作者在SCI论文25篇；授权发明专利4项，其中国际发明专利2项（美国、澳大利亚）；获国际及国内奖项3项。
工作经历：
2025.01-至今 中国科学院空天信息创新研究院 研究员
2020.03-2024.12 中国科学院空天信息创新研究院 副研究员
2013.05-2018.05 美国马里兰大学地理科学系 访问学者
2013.04-2020.02 中国科学院遥感与数字地球研究所 副研究员
2010.10-2013.03 清华大学地球系统科学系 博士后
2009.07-2013.03 中国科学院遥感应用研究所 助理研究员
森林扰动遥感监测与分析
（1）学术论文
[1] Yu B, Zhu M, Chen F*, Wang N, Zhao H, Wang L*, 2024. Multi-scale differential network for landslide extraction from remote sensing images with different scenarios. International Journal of Digital Earth, 17, 2441920. https://doi.org/10.1080/17538947.2024.2441920
[2] Chen F, Sun Y, Wang L*, Wang N, Zhao H, Yu B*, 2024. HRTBDA: a network for post-disaster building damage assessment based on remote sensing images. International Journal of Digital Earth, 17, 2418880. https://doi.org/10.1080/17538947.2024.2418880
[3] Chen F, Wang L#, Wang Y*, Zhang H, Wang N, Ma P, Yu B*, 2024. Retrieval of dominant methane (CH4) emission sources, the first high resolution (1–2m) dataset of storage tanks of China in 2000–2021. Earth System Science Data, 16, 3369–3382. https://doi.org/10.5194/essd-16-3369-2024
[4] Wang N, Chen F, Yu B, Zhang H, Zhao H, Wang L*, 2024. Delineation of Intermittent Rivers and Ephemeral Streams Using a Hybrid Method. Remote Sensing, 16, 2489. https://doi.org/10.3390/rs16132489
[5] Wang L, Ye C, Chen F*, Wang N, Yu B*, 2024. SOENet: a multi-resolution network for sheep extraction from high-resolution remote sensing images. International Journal of Digital Earth, 17(1), 2368707. http://doi.org/10.1080/17538947.2024.2368707
[6] Chen F, Wang L#, Wang N*, Guo H, Chen C, Ye C, Dong Y, Liu T, Yu B*, 2024. Evaluation of road network power conservation based on SDGSAT-1 glimmer imagery. Remote Sensing of Environment, 311, 114273. https://doi.org/10.1016/j.rse.2024.114273
[7] Wang L, Chen C, Chen F*, Wang N, Li C, Zhang H, Wang Y, Yu B*, 2024. UGTransformer: A Sheep Extraction Model from Remote Sensing Images for Animal Husbandry Management. IEEE Transactions on Geoscience and Remote Sensing, 62, 5402614. https://doi.org/10.1109/TGRS.2024.3355925
[8] Wang L, Ye C, Chen F*, Wang N, Li C, Zhang H, Wang Y, Yu B*, 2024. CG-CFPANet: a multi-task network for built-up area extraction from SDGSAT-1 and Sentinel-2 remote sensing images. International Journal of Digital Earth, 17(1), 2310092. https://doi.org/10.1080/17538947.2024.2310092
[9] Zhang H, Chen F, Wang L*, Wang N, Yu B*, 2023. Reservoir inventory for China in 2016 and 2021. Scientific Data, 10: 609. https://doi.org/10.1038/s41597-023-02515-2
[10] Li C, Chen F*, Wang N, Yu B, Wang L*, 2023. SDGSAT-1 nighttime light data improve village-scale built-up delineation. Remote Sensing of Environment, 297: 113764. https://doi.org/10.1016/j.rse.2023.113764
[11] Yu B, Chen F*, Ye C, Li Z, Dong Y, Wang N, Wang L*, 2023. Temporal expansion of the nighttime light images of SDGSAT-1 satellite in illuminating ground object extraction by joint observation of NPP-VIIRS and sentinel-2A images. Remote Sensing of Environment, 295: 113691. https://doi.org/10.1016/j.rse.2023.113691
[12] Li H, Song XP*, Hansen MC, Becker-Reshef I, Adusei B, Pickering J, Wang L, Wang L, Lin ZY, Zalles V, Potapov P, Stehman SV, Justice C, 2023. Development of a 10-m resolution maize and soybean map over China: Matching satellite-based crop classification with sample-based area estimation. Remote Sensing of Environment, 294: 113623. https://doi.org/10.1016/j.rse.2023.113623
[13] Yu B, Chen F*, Wang N, Wang L, Guo H, 2023. Assessing changes in nighttime lighting in the aftermath of the Turkey-Syria earthquake using SDGSAT-1 satellite data. The Innovation, 4(3): 100419. https://doi.org/10.1016/j.xinn.2023.100419
[14] Yu B, Xu C, Chen F, Wang N, Yang L, Yang H, Wang L*, 2022. MSFTrans: A multi-task frequency-spatial learning Transformer for building extraction from high spatial resolution remote sensing images. GIScience & Remote Sensing, 59:1, 1978-1996. http://doi.org/10.1080/15481603.2022.2143678
[15] Wang L, Yu B, Chen F, Li C, Li B, Wang N*, 2022. A Cluster-Based Partition Method of Remote Sensing Data for Efficient Distributed Image Processing. Remote Sensing, 14(19): 4964. https://doi.org/10.3390/rs14194964
[16] Yu B, Yang AQ, Chen F, Wang N, Wang L*, 2022. SNNFD, spiking neural segmentation network in frequency domain using high spatial resolution images for building extraction. International Journal of Applied Earth Observation and Geoinformation, 11: 102930. https://doi.org/10.1016/j.jag.2022.102930
[17] Yu B, Xu C, Chen F, Wang N, Wang L*, 2022. HADeenNet: A hierarchical-attention multi-scale deconvolution network for landslide detection. International Journal of Applied Earth Observation and Geoinformation, 11: 102853. https://doi.org/10.1016/j.jag.2022.102853
[18] Chen F*, Wang N, Yu B, Wang L, 2022. Res2-Unet, a New Deep Architecture for Building Detection from High Spatial Resolution Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15: 1494-1501. https://doi.org/10.1109/JSTARS.2022.3146430
[19] Huang N, Wang L*, Song XP, Black TA, Jassal RS, Myneni RB, Wu CY, Wang L, Song WJ, Ji DB, Yu SS, Niu Z 2020. Spatial and temporal variations in global soil respiration and their relationships with climate and land cover. Science Advances, 6(41): eabb8508. https://doi.org/10.1126/sciadv.abb8508
[20] Hansen MC*, Wang L, Song XP, Tyukavina A, Turubanova S, Potapov PV, Stehman SV, 2020. The Fate of Tropical Forest Fragments. Science Advances, 6(11): eaax8574. http://doi.org/10.1126/sciadv.aax8574
[21] Sun ZC*, Xu R, Du WJ, Wang L, Lu DS, 2019. High-Resolution Urban Land Mapping in China from Sentinel 1A/2 Imagery Based on Google Earth Engine . Remote Sensing, 11(7): 752. https://doi.org/10.3390/rs11070752
[22] Ying Q*, Hansen MC, Potapov PV, Tyukavina A, Wang L, Stehman SV, Moore R, Hancher M, 2017. Global bare ground gain from 2000 to 2012 using Landsat imagery. Remote Sensing of Environment, 194: 161-176. https://doi.org/10.1016/j.rse.2017.03.022
[23] Li C, Wang J, Wang L, Hu LY, Gong P*, 2014. Comparison of Classification Algorithms and Training Sample Sizes in Urban Land Classification with Landsat Thematic Mapper Imagery. Remote Sensing, 6(2): 964-983. http://doi.org/10.3390/rs6020964
[24] Wang L, Li CC, Ying Q, Cheng X, Wang XY, Li XY, Hu LY, Liang L, Yu L, Huang HB, Gong P*, 2012. China’s urban expansion from 1990 to 2010 determined with satellite remote sensing. Chinese Bulletin of Sciences, 57 (22): 2802-2812. https://doi.org/10.1007/s11434-012-5235-7
[25] Gong P, Liang S, Carlton EJ, Jiang QW, WU JY, Wang L, Remais JV*, 2012. Urbanisation and health in China. Lancet, 379: 843-852. https://doi.org/10.1016/S0140-6736(11)61878-3
[26] Wang L, Gong P*, Ying Q, Yang ZZ, Cheng X, Ran Q, 2010. Settlement extraction in the North China Plain using Landsat and Beijing-1 multispectral data with an improved watershed segmentation algorithm. International Journal of Remote Sensing, 31(6), 1411-1426. https://doi.org/10.1080/01431160903475332
（2）专著
[1] 陈方，李斌，王雷，贾慧聪，于博，鹿琳琳，张美美，陈玉，林政阳，闫继宁；灾害遥感信息提取的理论、方法与应用；科学出版社，202202，ISBN 9787030713919
[2] 刘涛，彭荣熙，王雷，张海英；村镇社区生态空间评价方法与应用；北京大学出版社，202306，ISBN 9787301340462
研究队伍