郑超磊，男，副研究员，主要从事基于遥感观测的气候变化对生态水文过程的影响及地表水热通量观测和模拟研究工作，在遥感蒸散发算法、全球蒸散发估算及产品和系统、干旱区气候变化及植被水分利用策略等方面取得了重要研究进展。

教育背景

2010.10-2013.09，日本国静冈大学，环境与能源系统专业，理学博士

2006.09-2009.07，中国科学院地理科学与资源研究所，自然地理学专业，理学硕士

2002.09-2006.07，河南大学，地理科学专业，理学学士

 

工作经历

2023.03-至今，中国科学院空天信息创新研究院，遥感科学国家重点实验室，副研究员

2023.05-2023.11，荷兰代尔夫特理工大学，访问学者

2020.03-2023.03，中国科学院空天信息创新研究院，遥感科学国家重点实验室，助理研究员

2014.04-2020.03，中国科学院遥感与数字地球研究所，遥感科学国家重点实验室，助理研究员

（1)国家自然科学基金面上项目：基于遥感的青藏高原蒸散发时空变化驱动机制及反馈作用研究, 项目负责人, 2022.01—2025.12

（2)国家自然科学基金重大项目：陆地水循环关键参量时空多尺度智慧化遥感, 子课题负责人, 2021.01—2025.12

（3)国家自然科学基金青年项目：多源遥感高分辨率时空连续地表实际蒸散发算法研究, 项目负责人, 2019.01—2021.12

（4)国家重点研发计划：面向水资源管理的天然水循环要素遥感监测技术研究子课题-蒸散发遥感反演, 子课题负责人, 2017.07—2020.12

（5)国家重点研发计划：大尺度全球变化数据产品快速生成方法子课题-全球ET产品快速生成方法研究, 子课题负责人, 2016.07—2021.01

（6)中国科学院先导专项子课题：全球中低分辨率时序空间信息产品, 子任务负责人, 2018.01—2022.12

（7)遥感科学国家重点实验室自由探索/青年人才项目：面向高分辨率地表实际蒸散发的时空数据融合研究, 负责人, 2016.06—2017.12

（8)可持续发展大数据国际研究中心开放研究计划项目：全球陆地生态系统耗水及水分利用效率估算方法及产品, 参与, 2023.01—2024.12

（9)“一带一路”国际科学组织联盟（ANSO）联合研究合作专项：北非地区水资源及农业用水监测与评估, 参与, 2022.12—2025.12

（10)第二次青藏科考研究专题：亚洲水塔区水循环动态监测与模拟, 参与, 2022.11—2024.10

（1）2022年度优秀共享开放遥感数据集十大最受欢迎年度数据集“ETMonitor 全球 1 公里分辨率地表实际蒸散发数据集”（排名第一）

（2）2021年度优秀共享开放遥感数据集十大最具价值年度数据集“中国与东盟1km分辨率地表蒸散发数据集”（排名第三）

1.学术论文

[1]Zheng C., Jia L., Zhao T., 2023. A 21-year dataset (2000–2020) of gap-free global daily surface soil moisture at 1-km grid resolution. Sci. Data 10, 1–14. https://doi.org/10.1038/s41597-023-01991-w.

[2]Mi P., Zheng C.(*), Jia L., Bai Y., 2023. Reconstruction of Global Long-Term Gap-Free Daily Surface Soil Moisture from 2002 to 2020 Based on a Pixel-Wise Machine Learning Method. Remote Sens. 15. https://doi.org/10.3390/rs15082116.

[3]Bennour A., Jia L., Menenti, M., Zheng C., Zeng Y., Barnieh B.A., Jiang M., 2023. Assessing impacts of climate variability and land use/land cover change on the water balance components in the Sahel using Earth observations and hydrological modelling. J. Hydrol. Reg. Stud. 47, 101370. https://doi.org/10.1016/j.ejrh.2023.101370.

[4]郑超磊, 贾立, 胡光成.高分一号卫星遥感数据驱动ETMonitor模型估算16 m分辨率蒸散发及验证. 遥感学报, 2023, 27(3): 758-768. DOI: 10.11834/jrs.20232477. 

[5]Zheng C., Jia L., Hu G., 2022. Global land surface evapotranspiration monitoring by ETMonitor model driven by multi-source satellite earth observations. J. Hydrol. 613, 128444. https://doi.org/10.1016/j.jhydrol.2022.128444.

[6]Bennour, A., Jia L., Menenti M., Zheng C., Zeng Y., Asenso B. B., Jiang M., 2022. Calibration and Validation of SWAT Model by Using Hydrological Remote Sensing Observables in the Lake Chad Basin. Remote Sens. 14, 1511. https://doi.org/10.3390/rs14061511.

[7]Du D., Jia L., Zheng C., Chen Q., Jiang M., Hu G., Lu J., 2022. Estimation of cropland gross primary productivity by integrat- ing water availability factor in light-use-efficiency-based model and satellite observations. Remote Sens. 1–24.

[8]Zheng C., Jia L., 2022. Evaluation of Different Methods for Soil Heat Flux Estimation at Large Scales Using Remote Sensing Observations. Int. Geosci. Remote Sens. Symp. 2022-July, 6081–6084. https://doi.org/10.1109/IGARSS46834.2022.9883851.

[9]Xu L., Zheng C.(*), Ma Y., 2021. Variations in precipitation extremes in the arid and semi-arid regions of China. Int. J. Climatol. 41, 1542–1554. https://doi.org/10.1002/joc.6884.

[10]Gan G., Liu Y., Chen D., Zheng C., 2021. Investigation of a nonlinear complementary relationship model for monthly evapotranspiration estimation at global flux sites. J. Hydrometeorol. 22. https://doi.org/10.1175/JHM-D-20-0224.1.

[11]Menenti M., Li X., Jia L., Yang K., Pellicciotti F., Mancini M., Shi J., Escorihuela M.J., Zheng C., et al., 2021. Multi-source hydrological data products to monitor high asian river basins and regional water security. Remote Sens. 13, 1–29. https://doi.org/10.3390/rs13245122.

[12]Paciolla N., Corbari C., Hu G., Zheng C., Menenti M., Jia L., Mancini M., 2021. Evapotranspiration estimates from an energy-water-balance model calibrated on satellite land surface temperature over the Heihe basin. J. Arid Environ. 188. https://doi.org/10.1016/j.jaridenv.2021.104466.

[13]Zhou J., Jia L., Menenti M., van Hoek M., Lu J., Zheng C., Wu H., Yuan X., 2021. Characterizing vegetation response to rainfall at multiple temporal scales in the Sahel-Sudano-Guinean region using transfer function analysis. Remote Sens. Environ. 252. https://doi.org/10.1016/j.rse.2020.112108.

[14]郑超磊, 胡光成, 陈琪婷, 贾立.遥感土壤水分对蒸散发估算的影响研究. 遥感学报, 2021, 25(4): 990-999. DOI: 10.11834/jrs.20210038.

[15]赵天杰,施建成,徐红新, 孙彦龙, 陈德清, 崔倩, 贾立, 黄硕, 牛升达, 李秀伟, 阎广建, 陈良富, 柳钦火, 赵凯, 郑兴明, 赵利民, 郑超磊, 等.闪电河流域水循环和能量平衡遥感综合试验. 遥感学报, 2021, 25(04):871-887.

[16]Zheng C., Jia L., 2020. Global canopy rainfall interception loss derived from satellite earth observations. Ecohydrology 13. https://doi.org/10.1002/eco.2186.

[17]Lu J., Jia L., Zheng C., Tang R., Jiang Y., 2020. A scheme to estimate diurnal cycle of evapotranspiration from geostationary meteorological satellite observations. Water 12. https://doi.org/10.3390/W12092369.

[18]van Hoek M., Zhou J., Jia L., Lu J., Zheng C., Hu G., Menenti M., 2020. A prototype web-based analysis platform for drought monitoring and early warning. Int. J. Digit. Earth 13, 817–831. https://doi.org/10.1080/17538947.2019.1585978.

[19]Zhao T., Shi J., Lv L., Xu H., Chen D., Cui Q., Jackson T.J., Yan G., Jia L., Chen L., Zhao K., Zheng X., Zhao L., Zheng C., Ji D., Xiong C., Wang T., Li R., Pan J., Wen J., Yu C., Zheng Y., Jiang L., Chai L., Lu H., Yao P., Ma J., Lv H., Wu J., Zhao W., Yang N., Guo P., Li Y., Hu L., Geng D., Zhang Z., 2020. Soil moisture experiment in the Luan River supporting new satellite mission opportunities. Remote Sens. Environ. 240. https://doi.org/10.1016/j.rse.2020.111680.

[20]Menenti M., Jia L., Mancini M., Li X., …, Zheng C., et al., 2020. High Elevation Energy and Water Balance: the Roles of Surface Albedo and Temperature. Journal of Geodesy and Geoinformation Science, 3(4): 70-78.

[21]胡光成, 周杰, 卢静, 郑超磊, 贾立.中国西南地区历年月度干旱指数（1951-2016）和8天频率土壤湿度（2007-2016）数据集.全球变化数据学报(中英文), 2020, 4(03):248-256.

[22]Zheng C., Jia L., Hu G., Lu J., 2019. Earth observations-based evapotranspiration in Northeastern Thailand. Remote Sens. 11. https://doi.org/10.3390/rs11020138.

[23]Chen Q., Jia L., Menenti M., Hutjes R., Hu G., Zheng C., Wang K., 2019. A numerical analysis of aggregation error in evapotranspiration estimates due to heterogeneity of soil moisture and leaf area index. Agric. For. Meteorol. 269–270, 335–350. https://doi.org/10.1016/j.agrformet.2019.02.017.

[24]Xu L., Zheng C., Wang Z.C, Nyongesah M.J., 2019. A digital camera as an alternative tool for estimating soil salinity and soil surface roughness. Geoderma 341. https://doi.org/10.1016/j.geoderma.2019.01.028.

[25]Zheng C., Jia L., Hu G., Lu J., 2019. Evapotranspiration estimation in tropical monsoon regions using improved ETMonitor algorithm, in: IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, pp. 6891–6894.

[26]Lu J., Zheng C., Jia L., Hu G. 2019. Adaptability of Six Global Drought Indices Over China. 2019 IEEE International Geoscience and Remote Sensing Symposium, 9922-9925. DOI: 10.1109/IGARSS.2019.8899184.

[27]卢静, 贾立, 郑超磊, 胡光成. 遥感水分收支对区域水资源估算潜能. 遥感技术与应用, 2019, 34(03):630-638. DOI: 10.11873/j.issn.1004-0323.2019.3.0630.

[28]Lu J., Jia L., Menenti M., Yan, Y., Zheng C., Zhou J., 2018. Performance of the Standardized Precipitation Index Based on the TMPA and CMORPH Precipitation Products for Drought Monitoring in China. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 11, 1387–1396. https://doi.org/10.1109/JSTARS.2018.2810163.

[29]Sun Y., Jia L., Chen Q., Zheng C., 2018. Optimizing window length for turbulent heat flux calculations from airborne eddy covariance measurements under near neutral to unstable atmospheric stability conditions. Remote Sens. 10, 1–27. https://doi.org/10.3390/rs10050670.

[30]柳钦火, 吴俊君, 李丽, 俞乐, 李静, 辛晓洲, 贾立, 仲波, 牛铮, 徐新良, 孟庆岩, 赵静, 张海龙,胡光成, 郑超磊. “一带一路”区域可持续发展生态环境遥感监测.遥感学报, 2018, 22(4):686-708. DOI:10.11834/jrs.20187264. 

[31]Zheng C., Jia L., Hu G., Menenti M., Lu J., Zhou J., Wang K., Li Z., 2017. Assessment of Water Use in Pan-Eurasian and African Continents by ETMonitor with Multi-Source Satellite Data, in: IOP Conference Series: Earth and Environmental Science. https://doi.org/10.1088/1755-1315/57/1/012050.

[32]Wang N., Jia L., Zheng C., Menenti M., 2017. Estimation of subpixel snow sublimation from multispectral satellite observations. J. Appl. Remote Sens. 11. https://doi.org/10.1117/1.JRS.11.046017.

[33]贾立*, 胡光成, 郑超磊, 周杰, 王昆, 李占胜, 柳钦火. 中国-东盟1 km分辨率地表蒸散发数据集（2013）, 全球变化数据学报, 2017, 1(3): 282-289. DOI: 10.3974/geodp.2017.03.05.

[34]Zheng C., Wang Q., Li P., 2016. Coupling SEBAL with a new radiation module and MODIS products for better estimation of evapotranspiration. Hydrol. Sci. J. 61, 1535–1547. https://doi.org/10.1080/02626667.2015.1031762.

[35]Lu J., Jia L., Zheng C., Zhou J., van Hoek M., Wang K., 2016. Characteristics and trends of meteorological drought over China from remote sensing precipitation datasets, in: IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. pp. 7581–7584.

[36]van Hoek M., Jia L., Zhou J., Zheng C., Menenti M., 2016. Early drought detection by spectral analysis of satellite time series of precipitation and Normalized Difference Vegetation Index (NDVI). Remote Sens. 8. https://doi.org/10.3390/rs8050422.

[37]Zheng C., Jia L., Hu G., Lu J., Wang K., Li Z.L., 2016. Global Evapotranspiration Derived by ETMonitor Model based on Earth Observations, in: International Geoscience and Remote Sensing Symposium (IGARSS). pp. 222–225.

[38]Zheng C., Jia L., 2016. Global rainfall interception loss derived from multi-source satellite earth observations, in: International Geoscience and Remote Sensing Symposium (IGARSS). pp. 3532–3534. https://doi.org/10.1109/IGARSS.2016.7729913.

[39]Zheng C., Jia L., Hu G., Menenti M., Lu J., Zhou J., Wang K., Li Z., 2016. Assessment of Water Use in Pan-Eurasian and African Continents by ETMonitor with Multi-Source Satellite Data. J. Phys. Conf. Ser. 755. https://doi.org/10.1088/1742-6596/755/1/011001.

[40]Menenti M., Jia L., Mousivand A., Hu G. C., Zheng C., Lu J. 2016. Evaluation of ET data products: Parameterizations, rate limiting process and influential surface properties. 2016 IEEE International Geoscience and Remote Sensing Symposium: 214-217. DOI: 10.1109/IGARSS.2016.7729047. 

[41]Menenti M., Jia L., Hu G., Liu Q., Xin X., Roupioz L., Zheng C., et l., 2016. Terrestrial water cycle in South and East Asia: Hydrospheric and cryospheric data products. 2016 IEEE International Geoscience and Remote Sensing Symposium: 3814-3817. DOI: 10.1109/IGARSS.2016.7729989. 

[42]Zheng C., Wang Q., 2015. Seasonal and annual variation in transpiration of a dominant desert species, Haloxylon ammodendron, in Central Asia up-scaled from sap flow measurement. Ecohydrology 8, 948–960. https://doi.org/10.1002/eco.1547.

[43]Zheng C., Wang Q., 2015. Spatiotemporal pattern of the global sensitivity of the reference evapotranspiration to climatic variables in recent five decades over China. Stoch. Environ. Res. Risk Assess. 29, 1937–1947. https://doi.org/10.1007/s00477-015-1120-7.

[44]Cao, Z., Wang Q., Zheng C., 2015. Best hyperspectral indices for tracing leaf water status as determined from leaf dehydration experiments. Ecol. Indic. 54, 96–107. https://doi.org/10.1016/j.ecolind.2015.02.027.

[45]Zheng C., Wang Q., 2014. Spatiotemporal variations of reference evapotranspiration in recent five decades in the arid land of Northwestern China. Hydrol. Process. 28. https://doi.org/10.1002/hyp.10109.

[46]Zheng C., Wang Q., 2014. Water-use response to climate factors at whole tree and branch scale for a dominant desert species in central Asia: Haloxylon ammodendron. Ecohydrology 7, 56–63. https://doi.org/10.1002/eco.1321.

[47]Li N., Jia L., Zheng C., 2014. Evaluation of the harmonic-analysis method for surface soil heat flux estimation: a case study in Heihe River Basin, in: Land Surface Remote Sensing II. p. 926043. https://doi.org/10.1117/12.2069270.

[48]周琪, 李平衡, 王权, 郑超磊, 徐璐. 西北干旱区荒漠生态系统通量贡献区模型研究. 中国沙漠, 2014, 31(1): 98-107.

[49]贾立, 胡光成, 郑超磊, 周杰, 王昆, 李占胜, 柳钦火. 中国-东盟1 km分辨率地表蒸散发数据集（2013）, 全球变化数据学报, 2017, 1(3): 282-289. 

[50]Shu C., Liu S.X, Mo X.G., Wang K., Zheng C.L., Zhang S.H. 2010. The Simulation of Hydrological Processes in an Ungauged Alpine Basin by using Xinanjiang Model(新安江模型在高寒无资料地区的水文过程模拟). Journal of Resources and Ecology, 1(2), 186-192. https://doi.org/10.3969/j.issn.1674-764x.2010.02.011.

[51]郑超磊, 刘苏峡, 舒畅, 张守红. 尼曲河道内最小生态需水研究. 长江流域资源与环境, 2010, 19: 329-334. 

[52]郑超磊, 刘苏峡, 舒畅等. 基于生态需水的水资源供需平衡分析. 人民黄河, 2010, 32: 48-49. 

[53]舒畅，刘苏峡，莫兴国，郑超磊，张守红，邱建秀. 基于变异性范围法(RVA)的河流生态流量估算. 生态环境学报, 2010, 19(5):1151-1155. 

[54]张守红，刘苏峡, 莫兴国, 舒畅, 郑超磊, 侯博. 降雨和水保措施对无定河流域径流和产沙量影响. 北京林业大学学报, 2010, 32(4):161-168. 

[55]刘苏峡, 夏军, 蔡强国, 王随继, 舒畅, 郑超磊. 汶川特大地震灾后山洪灾害预估与应对措施. 中国水土保持科学, 2008, 6(5):7-10. 

 

2.专著和报告（参与撰写）

(1)Jia L., Zheng C., Hu G.C., Menenti M., 2018. Evapotranspiration, in: Comprehensive Remote Sensing. pp. 25–50. https://doi.org/10.1016/B978-0-12-409548-9.10353-7.(专著章节)

(2)贾立, 郑超磊, 等. 陆表能量与水分交换过程的遥感观测与模拟》第7章陆表蒸散发遥感, 科学出版社, 2023，ISBN 978-7-03-074897-3. (专著章节)

(3)《地球观测优秀应用百佳案例》，“ETMonitor蒸散发数据助力“一带一路”区域水资源监测”案例，中国GEO, 2022. 

(4)《地球大数据支撑可持续发展目标报告(2023)》，“SDG 6 清洁饮水和卫生设施：全球农田用水效率变化”案例, 中国科学院, 2023. 

(5)《地球大数据支撑可持续发展目标报告(2022)》，“SDG 6 清洁饮水和卫生设施：中国三大粮食作物水分利用效率变化评估”案例, 中国科学院, 2022. 

(6)《地球大数据支撑可持续发展目标报告(2021)》，“SDG 6 清洁饮水和卫生设施：全球农作物水分利用效率变化评估”案例, 中国科学院, 2021.

(7)《地球大数据支撑可持续发展目标报告(2020):“一带一路”篇》，“摩洛哥作物水分生产力评估案例”, 科学出版社2021. 

(8)遥感监测绿皮书《中国可持续发展遥感监测报告（2021）》, 社会科学文献出版社, 2021. 

(9)遥感监测绿皮书《中国可持续发展遥感监测报告（2019）》, 社会科学文献出版社, 2020.

(10)遥感监测绿皮书《中国可持续发展遥感监测报告（2017）》, 社会科学文献出版社, 2018.

(11)遥感监测绿皮书《中国可持续发展遥感监测报告（2016）》, 社会科学文献出版社, 2017.

(12)《全球生态环境遥感监测2017年度报告—“一带一路”生态环境状况》, 国家科学技术部发布, 2018.

(13)《全球生态环境遥感监测2014年度报告—中国-东盟生态环境状况》, 国家科学技术部发布, 2015.

 

 

3.专利和软著

(1)郑超磊. 2021. 基于风云卫星遥感数据的陆表蒸散发估算软件. 软件著作权登记编号: 2021SR0638223. （软件著作权）

(2)郑超磊., 贾立, 胡光成, 等. 2023. 基于国产高分一号卫星遥感数据的陆表蒸散发估算软件. 软件著作权登记编号: 2023SR0348829. （软件著作权）

(3)贾立，郑超磊，胡光成. 2021. 地表蒸散发量的确定方法及装置. 专利申请号: 202110386815.8.（发明专利）

(4)胡光成，贾立，郑超磊，陈琪婷. 2023. 地表蒸散发量的确定方法及装置. 专利申请号: 202311065046.7.（发明专利）

 

4.发布数据集

(1)郑超磊,贾立,胡光成. 2023. 全球陆表蒸散发产品(2000-2021 年，1 公里分辨率)(ETMonitor-1km_2000-2021). 可持续发展大数据国际研究中心, DOI: 10.12237/casearth.640f012a819aec3f2b52a4b6. （入选赠送联合国全球水资源数据产品 2023版）

(2)郑超磊, 贾立, 胡光成. 2022. ETMonitor全球1公里分辨率地表实际蒸散发数据集. 国家青藏高原科学数据中心, DOI:10.11888/RemoteSen.tpdc.272831. (入选2022年度优秀共享开放遥感数据集十大最受欢迎年度数据集)

(3)郑超磊,贾立,胡光成. 2022. 2000-2019年全球1km地表实际蒸散发. 地球大数据科学工程数据共享服务系统, DOI: 10.12237/casearth.6253cddc819aec49731a4bc2. 

(4)郑超磊, 贾立, 赵天杰. 2022. 全球1公里分辨率地表土壤湿度数据集（2000-2020）. 国家青藏高原科学数据中心, DOI: 10.11888/RemoteSen.tpdc.272760.

(5)郑超磊, 贾立, 胡光成. 2019. 全球陆表实际蒸散发数据集(2013-2014). 国家青藏高原科学数据中心, DOI: 10.11888/Hydro.tpdc.270298. 

(6)胡光成, 贾立, 郑超磊, 崔要奎. 2021. 中国黑河流域蒸散发日序列1-km栅格数据集（2000-2015）. 全球变化数据仓储电子杂志(中英文). DOI:10.3974/geodb.2021.10.07.V1.

(7)胡光成, 周杰, 卢静, 郑超磊, 贾立等. 2020. 中国西南地区历年月度干旱指数（1951-2016）和8 天频率土壤湿度（2007-2016）数据集. 全球变化数据仓储电子杂志(中英文). DOI: 10.3974/geodb.2020.04.17.V1.

(8)赵天杰, 姚盼盼, 崔倩, 蒋玲梅, 柴琳娜, 郑超磊, 卢麾, 等. 2021. 滦河上游地区土壤温湿度地面同步观测数据集（2018）. 国家青藏高原科学数据中心, DOI: 10.11888/Soil.tpdc.271551. 

(9)贾立, 郑超磊, 胡光成, 周杰, 卢静, 王昆. 2017. “一带一路”及其毗邻区域地表蒸散发数据集2015. 全球变化数据仓储电子杂志(中英文). DOI:10.3974/geodb.2017.04.11.V1. 

(10)贾立, 胡光成, 郑超磊, 周 杰 ,王 昆 ,李占胜 ,柳钦火. 2017. 中国-东盟1 km分辨率地表蒸散发数据集（2013）. 全球变化数据仓储电子杂志(中英文). DOI: DOI:10.3974/geodb.2015.01.11.V1. （入选首届优秀共享开放遥感数据集“十大最具价值年度数据集”）