个人简况
学历 博士
职称 教授
籍贯 湖北
Email yke@cnu.edu.cn
研究方向 多源遥感数据融合、人工智能及数据挖掘方法、生态水文遥感应用
教育背景
2005-2009年，美国纽约州立大学环境与林业学院（SUNY ESF），理学博士
2002-2005年，北京大学遥感与地理信息系统研究所，理学硕士
1998-2002年，武汉大学资源与环境学院，理学学士
工作经历
2013-现在，威尼斯9499登录入口资源环境与旅游学院
2010-2012，美国西北太平洋国家实验室（PNNL）
2009，加拿大XEOS Imaging公司
主要科研项目
1.国家自然科学基金面上项目，尺度效应支持下的黄河三角洲湿地互花米草扩张机制研究，2021-2024，项目负责人
2.北京市科技计划京津冀协同创新推动专项，张家口坝上地区湿地生态系统保护修复关键技术集成与示范，2020-2022，课题负责人
3.北京市自然科学基金，面上项目，永定河流域多尺度生态系统时空演化规律研究，2017-2019，项目负责人
4.国家重点研发课题，河口湿地生物连通修复技术，2017-2020，课题骨干
5.国家自然科学基金青年项目，基于时序InSAR与灰色马尔科夫模型的北京市地面沉降预测研究，2015-2017，项目负责人
6.北京市科技新星项目，基于InSAR新技术的北京地面沉降时空预测模型研究，2015-2017，项目负责人
7.教育部留学回国人员科研启动基金，基于地面沉降遥感监测的京津城际铁路运行风险研究，2015-2017，项目负责人
8.教育部博士点基金，城市复杂环境对高分辨率遥感提取多尺度植被信息的影响研究-以北京为例，2014-2016，项目负责人
代表论文
1．Liyue Cui, Yinghai Ke*, Yukui Min, Yue Han, Mengyao Zhang, Demin Zhou (2024). Effects of tidal creeks on Spartina Alterniflora expansion: a perspective from multi-scale remote sensing. Ecological Indicators. 160, 111842. https://doi.org/10.1016/j.ecolind.2024.111842.
2．Yinghai Ke*, Yue Han, Liyue Cui, Peiyu Sun, Yukui Min, Zhanpeng Wang, Zhaojun Zhuo, Qingqing Zhou, Xiaolan Yin, Demin Zhou (2024). Suaeda salsa spectral index for Suaeda salsa mapping and fractional cover estimation in intertidal wetlands. ISPRS Journal of Photogrammetry and Remote Sensing. 207, 104–121, https://doi.org/10.1016/j.isprsjprs.2023.11.018.
3．Yukui Min, Liyue Cui, Jinyuan Li, Yue Han, Zhaojun Zhuo, Xiaolan Yin, Demin Zhou, Yinghai Ke* (2023). Detection of large-scale Spartina alterniflora removal in coastal wetlands based on Sentinel-2 and Landsat 8 imagery on Google Earth Engine. International Journal of Applied Earth Observation and Geoinformation. 125 (2023): 103567. https://doi.org/10.1016/j.jag.2023.103567.
4．尹小岚,谭程月,柯樱海*等.1973—2020年黄河三角洲滨海盐沼湿地景观格局演化模式和驱动因素[J/OL].生态学报, 2024 (01) : 1-14. https://doi.org/10.20103/j.stxb.202211203355. [Xiaolan Yin, Chengyue Tan, Yinghai Ke, Demin Zhou (2023). Evolution and driving factors of saltmarsh wetland landscape pattern in the Yellow River Delta in 1973-2020. Acta Ecological Sinica, 2024, 44(1).
5．Yuhang Wang, Xifei Wang, Shahbaz Khan, Demin Zhou*, Yinghai Ke* (2023). Evaluation of mangrove restoration effectiveness using remote sensing indices - a case study in Guangxi Shankou Mangrove National Natural Reserve, China. Frontiers in Marine Science 10:1280373. https://doi.org/10.3389/fmars.2023.1280373.
6．Cun Du, Shahbaz Khan, Yinghai Ke*, Demin Zhou (2023). Assessment of Spatiotemporal Dynamics of Mangrove in Five Typical Mangrove Reserve Wetlands in Asia, Africa and Oceania. Diversity 15, no. 2: 148. https://doi.org/10.3390/d15020148.
7．Peng Li, Shenliang Chen*, Hongyu Ji, Yaoshen Fan, Yutao Fu, Baichuan Ran, Yinghai Ke (2023). Detecting the magical yellow-blue demarcation off the Yellow River Estuary from the space. Frontiers in Marine Science. 10:1234631. https://doi.org/10.3389/fmars.2023.1234631.
8．闵钰魁，柯樱海，韩月，尹小岚，周德民.2023.融合Sentinel-2和GF-1时序影像的入侵植物互花米草清除动态监测.遥感学报，27(6): 1467-1479. DOI：10.11834/jrs.20232279. Min Y K，Ke Y H，Han Y，Yin X L and Zhou D M. 2023. Dynamic monitoring of invasive Spartina alterniflora clearance via fusion of Sentinel-2 and GF-1 time series images. National Remote Sensing Bulletin， 27（6）：1467-1479 DOI：10.11834/jrs.20232279.
9．Zhanpeng Wang, Yinghai Ke*, Demin Zhou, Xiaojuan Li, Lin Zhu, Huili Gong (2023), Virtual image-based cloud removal for Landsat images, GIScience & Remote Sensing,60(1), https://doi.org/10.1080/15481603.2022.2160411.
10．Zhanpeng Wang, Yinghai Ke*, Dan Lu, Zhaojun Zhuo, Qingqing Zhou, Yue Han, Peiyu Sun, Zhaoning Gong and Demin Zhou (2022), Estimating fractional cover of saltmarsh vegetation species in coastal wetlands in the Yellow River Delta, China using ensemble learning model, Frontiers in Marine Science, 2613, https://doi.org/10.3389/fmars.2022.1077907
11．Qingqing Zhou, Yinghai Ke*, Xinyan Wang, Junhong Bai, Demin Zhou, Xiaojuan Li* (2022), Developing seagrass index for long term monitoring of Zostera japonica seagrass bed: A case study in Yellow River Delta, China. ISPRS Journal of Photogrammetry and Remote Sensing. 194 (2022), 286-301. DOI: 10.1016/j.isprsjprs.2022.10.011
12．Xiaoran Han, Yiming Wang, Yinghai Ke*, Tianqi Liu, Demin Zhou (2022). Phenological heterogeneities of invasive Spartina alterniflora salt marshes revealed by high-spatial-resolution satellite imagery. Ecological Indicators, 144 (2022) 109492, DOI: 10.1016/j.ecolind.2022.109492.
13．Lijuan Zhu, Yinghai Ke*, Jianming Hong*, Yuhu Zhang, Yun Pan (2022). Assessing degradation of lake wetlands in Bashang Plateau, China based on long-term time series Landsat images using wetland degradation index. Ecological Indicators, 139 (2022), 108903. DOI: 10.1016/j.ecolind.2022.108903.
14．卓昭君，柯樱海*，洪剑明，朱丽娟，张玉虎(2022). 2000年以来张家口坝上高原生态系统服务价值及其变化.湿地科学，DOI: 10.13248/j.cnki.wetlandsci.2022.02.004
15．Yue Han, Yinghai Ke*, Lijuan Zhu, Hui Feng, Qun Zhang, Zhao Sun & Lin Zhu (2021) Tracking vegetation degradation and recovery in multiple mining areas in Beijing, China, based on time-series Landsat imagery, GIScience & Remote Sensing, 58:8, 1477-1496, DOI: 10.1080/15481603.2021.1996319
16．韩月，柯樱海*，王展鹏，梁德印，周德民(2021). 资源一号02D卫星高光谱数据黄河三角洲湿地景观分类.遥感学报，DOI：10.11834/jrs.20211071.
17．Wang, Z., Ke, Y.*, Chen, M., Zhou, D., Zhu, L. Bai, J (2021). Mapping coastal wetlands in Yellow River Delta, China during 2008-2019: impacts of valid observations, harmonic regression, and critical months. International Journal of Remote Sensing. Accepted.
18．Xu, R., Zhao S., Ke, Y.* (2020). A Simple Phenology-Based Vegetation Index for Mapping Invasive Spartina alterniflora Using Google Earth Engine. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020, 190 –201.
19．Jiang, Y., Wang Y., Zhou, D*., Ke, Y.*, Bai, J., Li, W., Yan, J. (2020). The Impact Assessment of Hydro-Biological Connectivity changes on the Estuary Wetland through the Ecological Restoration Project in the Yellow River Delta, China. Science of the Total Environment. 2020, 11, https://doi.org/10.1016/j.scitotenv.2020.143706.
20．Li, P., Ke, Y.*, Chen, M., Lyu, M., Zhou, D* (2020).Human impact on suspended particulate matter in the Yellow River Estuary, China: Evidence from remote sensing data fusion using an improved spatiotemporal fusion method. Science of the Total Environment. 750, 141612.
21．Chen, M., Ke, Y.*, Li, P., Lyu, M., Zhou, D* (2020). Monitoring early stage invasion of exotic Spartina alterniflora using deep-learning super-resolution techniques based on multisource high-resolution satellite imagery: A case study in the Yellow River Delta, China. International Journal of Applied Earth Observation and Geoinformation, 92, 102180.
22．Fan, Y., Zhou, D. *, Ke, Y.*, Wang, Y., Wang, Q., Zhang, L. (2020). Quantifying the Correlated Spatial Distributions between Tidal Creeks and Coastal Wetland Vegetation in the Yellow River Estuary. Wetlands. https://doi.org/10.1007/s13157-020-01292-7.
23．Liu, M.; Ke, Y.*; Yin, Q.; Chen, X.; Im, J (2019). Comparison of Five Spatio-Temporal Satellite Image Fusion Models over Landscapes with Various Spatial Heterogeneity and Temporal Variation. Remote Sensing, 11, 2612. https://doi.org/10.3390/rs11222612.
24．Lyu, M., Ke, Y.*, Guo, L., Li, X., Zhu, L., Gong, H.; Constantinos, C (2019). Change in regional land subsidence in Beijing after south-to-north water diversion project observed using satellite radar interferometry. GIScience & Remote Sensing, 10, 1-17. https://doi.org/10.1080/15481603.2019.1676973.
25．Li, P., Ke, Y.*, Bai, J., Zhang, S., Chen, M., & Zhou, D. (2019). Spatiotemporal dynamics of suspended particulate matter in the Yellow River Estuary, China during the past two decades based on time-series Landsat and Sentinel-2 data. Marine Pollution Bulletin, 149, 110518. https://doi.org/10.1016/j.marpolbul.2019.110518.
26．Yin, Q.; Liu, M.; Cheng, J.; Ke, Y.*; Chen, X (2019). Mapping Paddy Rice Planting Area in Northeastern China Using Spatiotemporal Data Fusion and Phenology-Based Method. Remote Sensing, 11, 1699. https://doi.org/10.3390/rs11141699.
27．Wang, M.; Du, L.; Ke, Y.*; Huang, M.; Zhang, J.; Zhao, Y.; Li, X.; Gong, H (2019). Impact of Climate Variabilities and Human Activities on Surface Water Extents in Reservoirs of Yongding River Basin, China, from 1985 to 2016 Based on Landsat Observations and Time Series Analysis. Remote Sensing, 2019, 11, 560.
28．Yang, Q.; Ke, Y.*; Zhang, D.; Chen, B.; Gong, H.; Lv, M.; Zhu, L.; Li, X (2018). Multiscale Analysis of the Relationship between Land Subsidence and Buildings: A Case Study in an Eastern Beijing Urban Area Using the PS-InSAR Technique. Remote Sensing, 10, 1006. https://doi.org/10.3390/rs10071006.
29．Zhang, P.; Ke, Y.*; Zhang, Z.; Wang, M.; Li, P.; Zhang, S (2018). Urban Land use and Land Cover Classification Using Novel Deep Learning Models Based on High Spatial Resolution Satellite Imagery. Sensors, 18, 3717. https://doi.org/10.3390/s18113717.
30．Liu, Y., Zhang, Z.*, Zhong, R., Chen, D., Ke, Y., Peethambaran, J., Sun, L. (2018). Multilevel Building Detection Framework in Remote Sensing Images Based on Convolutional Neural Networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 99, 1-13.
31．Ke, Y., Im, J.*, Park, S., & Gong, H. (2017). Spatiotemporal downscaling approaches for monitoring 8-day 30m actual evapotranspiration. ISPRS Journal of Photogrammetry and Remote Sensing, 126, 79-93.
32．Deng, Z., Ke, Y.*, Gong, H., Li, X., & Li, Z. (2017). Land subsidence prediction in Beijing based on PS-InSAR technique and improved Grey-Markov model. GIScience & Remote Sensing, 1-22. https://doi.org/10.1080/15481603.2017.1331511.
33．Ke, Y., Im, J.*, Park, S., & Gong, H. (2016). Downscaling of MODIS One kilometer evapotranspiration using Landsat-8 data and machine learning approaches. Remote Sensing, 8(3), 215.
34．Li, D., Ke, Y.*, Gong, H., & Li, X. (2015). Object-based urban tree species classification using bi-temporal worldview-2 and worldview-3 images. Remote Sensing, 7(12), 16917-16937.
35．Ke, Y., Im, J.*, Lee, J., Gong, H., & Ryu, Y. (2015). Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observations. Remote Sensing of Environment, 164, 298-313.
36．Ke, Y., Leung, L. R.*, Huang, M., & Li, H. (2013). Enhancing the representation of subgrid land surface characteristics in land surface models. Geoscientific Model Development, 6(5), 1609-1622.
37．Ke, Y.*, Coleman, A. M., & Diefenderfer, H. L. (2013). Temporal land cover analysis for net ecosystem improvement. Ecohydrology & Hydrobiology, 13(1), 84-96.
38．Ke, Y., Leung, L. R.*, Huang, M., Coleman, A. M., Li, H., & Wigmosta, M. S. (2012). Development of high resolution land surface parameters for the Community Land Model. Geoscientific Model Development, 5(6), 1341-1362.
39．Ke, Y., and Quackenbush, L.J.* (2011). A comparison of three methods for automatic tree crown detection and delineation from high spatial resolution imagery. International Journal of Remote Sensing, 32, 3625-3647.
40．Ke, Y., and Quackenbush, L.J*., (2011). A review of methods for automatic individual tree crown detection and delineation. International Journal of Remote Sensing, 32, 4725-4747.
41．Ke, Y., Quackenbush, L.J.*, Im, J. (2010). Synergistic use of QuickBird multispectral imagery and LIDAR data for object-based forest species classification. Remote Sensing of Environment, 114(6), 1141 –1154.
42．Ke, Y., Zhang, W. and Quackenbush, L.J.* (2010). Active contour and hill-climbing for tree crown detection and delineation. Photogrammetric Engineering and Remote Sensing, 76(10): 1169 –1181.
43．Zhang, W., Ke, Y., Quackenbush, L.J.* and Zhang, L. (2010). Using error-in-variable regression to predict tree diameter and crown width from remotely sensed imagery. Canadian Journal of Forest Research, 2010, 40:1095-1108.
44．Huang, M., Hou, Z., Leung, L. R., Ke, Y., Liu, Y., Fang, Z., & Sun, Y. (2013). Uncertainty analysis of runoff simulations and parameter identifiability in the community land model: evidence from MOPEX basins. Journal of Hydrometeorology, 14(6), 1754-1772.
45．Li, H., Wigmosta, M. S., Wu, H., Huang, M., Ke, Y., Coleman, A. M., & Leung, L. R. (2013). A physically based runoff routing model for land surface and earth system models. Journal of Hydrometeorology, 14(3), 808-828.
46．李丹,柯樱海*，宫辉力，李小娟，邓曾(2015). 基于高分辨率遥感影像的城市典型乔木树种分类研究[J].地理与地理信息科学.32(1),42-46.
47．邓曾,柯樱海*,吴燕晨,李小娟,宫辉力(2015). 基于改进SVM算法的高分辨率遥感影像分类[J].国土资源遥感. 28(3), 12-18.
48．李映辰,柯樱海*,宫辉力,李小娟,陈蓓蓓.DEM对PS-InSAR地面沉降监测的影响[J].测绘科学,2018,43(01):124-134.
49．张婉婉,柯樱海*,邓曾,陈蓓蓓,宫辉力,李小娟(2018).基于多源SAR数据的京津高铁北京段垂向形变监测[J].中国科技论文, 13(02):235-240.
50．杨琴,柯樱海*,李小娟,宫辉力,邹君.湖南省水资源脆弱性时空演变研究[J].河南理工大学学报(自然科学版),2018,37(03):79-85.
专著和教材
1．柯樱海，李小娟，宫辉力.遥感技术在自动化森林资源清查中的应用.中国环境出版社，2015
2．柯樱海，甄贞，李小娟，宫辉力.《遥感导论（中文导读）》（ISBN：9787517061090），2018年，中国水利水电出版社.
3．甄贞，姜立春，柯樱海，高利.《地理信息科学专业英语》（ISBN：9787567417038），2019年，东北林业大学出版社.
专利
1．一种通过数据融合提取水体信息的方法，国家发明专利，第一发明人，申请号：202011201586.X
2．一种基于多输出机器学习重建高时空分辨率地面沉降信息的方法，国家发明专利，第一发明人，2021
3．通过长时序卫星遥感评价湿地退化的方法，国家发明专利，第一发明人，申请号：202110165443.6
4．通过无人机上高光谱传感器反演河口湿地水环境要素方法，国家发明专利，第一发明人，专利号：ZL 2018 1 1652831.1
5．互花米草新生斑块的动态监测方法，国家发明专利，第一发明人，专利号：ZL 2019 1 0270990.3
6．一种描述地面沉降时序演变的方法，国家发明专利，第一发明人，专利号：ZL 2018 1 1614224.6
7．一种表征地面沉降时空特征的方法，国家发明专利，第二发明人，专利号：ZL 2018 1 124049.9
8．一种区域地面沉降时空预测方法，国家发明专利，第一发明人，专利号：ZL 2017 1 0025455.2
获奖及荣誉
1．2018年，高分辨率遥感公路交通设施健康检测技术及应用示范，地理信息科技进步奖，一等奖，排名5
2．2017年，第四届全国GIS青年教师讲课大赛特等奖
3．2017年，2017年全国自然地理学大会优秀青年论文（指导教师）
4．2017年，威尼斯9499登录入口青年教师教学基本功大赛二等奖
5．2016年，科技部遥感中心青年科技创新人才
6．2015年，北京市科技新星
教学
1．2020-2023年，《测绘与地理信息概论》辅修专业课
2．2019-2023年，《测绘与地理信息概论》本科生专业基础课
3．2017年至今，GI Science留学生专业必修课
4．2015年至今，《遥感与地理信息系统应用建模》研究生专业方向课
5．2014年至今，GI Science 研究生专业选修课
6．2013-2018年，《空间信息技术基础（双语）》本科生专业基础课
7．2013年，《空间信息技术基础》本科生通识课
社会服务
1．2016至今，GIScience & Remote Sensing期刊（SCI）编委
2．2016年，EORSA国际会议分会主席
3. 2019年，第一届全国湿地遥感大会共同主席
4. 2020年，第二届全国湿地遥感大会共同主席
研究生培养
