陈鹏(水色)研究员

出生年月:1986年1月

学位学历:博士研究生

研究方向:海洋激光遥感

电       话: 0571-81961201

教育背景及工作经历

2023.12—至今   自然资源部第二海洋研究所        研究员

2020.12—2023.12 自然资源部第二海洋研究所     副研究员

2015.06—2020.12 自然资源部第二海洋研究所 助理研究员


社会兼职:

1.中国遥感应用协会海岸带分会 常务理事
2.国际数字地球学会中委会数字海洋专业委员会 委员
3.国际空间科学研究所ISSI 海洋激光国际团队 核心成员
4.国际水色协调组织IOCCG初级生产力专家组 成员
5.《Acta Oceanologica Sinica》青年编辑
6.《海洋学报》青年编辑
7.《大气与环境光学学报》青年编委
8.《PLOS ONE》学术编辑
9.《Frontiers in Marine Science》客座主编
10.《Remote Sensing》客座主编2项
11.《Discover Oceans》客座主编
12.《Frontiers in Remote Sensing》客座主编

科研项目及荣誉奖励

     主持国家自然科学基金优青、面上项目等3项,国家及省重点研发计划课题2项,省自然科学基金重点项目等3项,以及其他项目20余项。发表学术论文100余篇,其中以第一/通讯作者在RSE、ISPRS、TGRS等权威期刊发表SCI论文40余篇、专著2部,专利及软著30余项。目前担任国际空间科学研究所ISSI海洋激光卫星团队核心成员、中国遥感应用协会海岸带分会常务理事、海洋学报中英文青年编委,frmas客座编辑等10余项,担任PNAS、RSE、ISPRS、TGRS、JGR、WRR、OE、OL、JSTARS等20多个期刊审稿人。获得省部级科技奖励2项,其中海洋科学技术奖特等奖1项。


代表性科研成果(论文专著、专利及软件)

第一/通讯作者SCI论文

1.Zhang, Z., et al., Consistency analysis of water diffuse attenuation between ICESat-2 and MODIS in Marginal Sea: A case study in China Sea. Remote Sensing of Environment, 2025. 318: p. 114602.
2.Li, X., et al., Vertical structure observation from spaceborne lidar ICESat-2 in East China Sea. Optics Express, 2025. 33(2): p. 2847-2865.
3.Zhang Z, Zhang S, Behrenfeld M J, Chen P, et al. Combining deep learning with physical parameters in POC and PIC inversion from spaceborne lidar CALIOP[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2024, 212: 193-211.
4.Zhong, C., et al., The use of spaceborne lidar to map Antarctic krill distributions and biomass in the Southern Ocean. Frontiers in Marine Science, 2024. 11.
5.Zhong, C., P. Chen, and S. Zhang, Enhancing Subsurface Phytoplankton Layer Detection in LiDAR Data through Supervised Machine Learning Techniques. Remote Sensing, 2024. 16(11): p. 1953.
6.Zhang, Z., et al., Combining deep learning with physical parameters in POC and PIC inversion from spaceborne lidar CALIOP. ISPRS Journal of Photogrammetry and Remote Sensing, 2024. 212: p. 193-211.
7.Zhang, S., et al., Diurnal global ocean surface pCO2 and air–sea CO2 flux reconstructed from spaceborne LiDAR data. PNAS Nexus, 2024. 3(1).
8.Xie, C., et al., New Reference Bathymetric Point Cloud Datasets Derived From ICESat-2 Observations: A Case in the Caribbean Sea. IEEE Transactions on Geoscience and Remote Sensing, 2024. 62: p. 1-24.
9.Wu, D., et al., A Novel Semi-Analytical Method for Modeling Polarized Oceanic Profiling LiDAR Multiple Scattering Signals. IEEE Transactions on Geoscience and Remote Sensing, 2024. 62: p. 1-17.
10.Wen, Y., et al., Cross-Attention-Based High Spatial-Temporal Resolution Fusion of Sentinel-2 and Sentinel-3 Data for Ocean Water Quality Assessment. Remote Sensing, 2024. 16(24): p. 4781.
11.Sun, M., et al., Seasonal Variability in the Relationship between the Volume-Scattering Function at 180° and the Backscattering Coefficient Observed from Spaceborne Lidar and Biogeochemical Argo (BGC-Argo) Floats. Remote Sensing, 2024. 16(15): p. 2704.
12.Chen, P., et al., Editorial: Lidar and Ocean Color Remote Sensing for Marine Ecology. Frontiers in Remote Sensing, 2024. 5.
13.张思琪, et al., 基于激光数据的北极海水二氧化碳分压研究. 红外与毫米波学报, 2024.
14.Zhang, Z., et al., Chlorophyll and POC in polar regions derived from spaceborne lidar. Frontiers in Marine Science, 2023. 10.
15.Zhang, Z., et al., Retrieving bbp and POC from CALIOP: A deep neural network approach. Remote Sensing of Environment, 2023. 287: p. 113482.
16.Xie, C., et al., Satellite-derived bathymetry combined with Sentinel-2 and ICESat-2 datasets using machine learning. Frontiers in Earth Science, 2023. 11.
17.Sun, M., et al., Evaluation of the CALIPSO Lidar-observed particulate backscattering coefficient on different spatiotemporal matchup scales. Frontiers in Marine Science, 2023. 10.
18.Zhong, C., et al., CPUE retrieval from spaceborne lidar data: A case study in the Atlantic bigeye tuna fishing area and Antarctica fishing area. Frontiers in Marine Science, 2022. 9.
19.Zhang, Z., P. Chen, and Z. Mao, SOLS: An Open-Source Spaceborne Oceanic Lidar Simulator. Remote Sensing, 2022. 14(8): p. 1849.
20.Zhang, S., et al., Carbon Air–Sea Flux in the Arctic Ocean from CALIPSO from 2007 to 2020. Remote Sensing, 2022. 14(24): p. 6196.
21.Zhang, S. and P. Chen, Subsurface phytoplankton vertical structure from lidar observation during SCS summer monsoon onset. Optics Express, 2022. 30(11): p. 17665-17679.
22.Chen, S., et al., Assessments of the Above-Ocean Atmospheric CO2 Detection Capability of the GAS Instrument Onboard the Next-Generation FengYun-3H Satellite. Remote Sensing, 2022. 14(23): p. 6032.
23.Chen, P., C. Jamet, and D. Liu, LiDAR Remote Sensing for Vertical Distribution of Seawater Optical Properties and Chlorophyll-a From the East China Sea to the South China Sea. IEEE Transactions on Geoscience and Remote Sensing, 2022. 60: p. 1-21.
24.Chen, P., Subsurface phytoplankton vertical structure observations using offshore fixed platform-based lidar in the Bohai Sea for offshore responses to Typhoon Bavi. Optics Express, 2022. 30(12): p. 20614-20628.
25.Zhong, C., P. Chen, and D. Pan, An Improved Adaptive Subsurface Phytoplankton Layer Detection Method for Ocean Lidar Data. Remote Sensing, 2021. 13(19): p. 3875.
26.Zhang, Z., et al., A Novel Fast Multiple-Scattering Approximate Model for Oceanographic Lidar. Remote Sensing, 2021. 13(18): p. 3677.
27.Xie, C., et al., Improved Filtering of ICESat-2 Lidar Data for Nearshore Bathymetry Estimation Using Sentinel-2 Imagery. Remote Sensing, 2021. 13(21): p. 4303.
28.Chen, P., et al., Vertical distribution of subsurface phytoplankton layer in South China Sea using airborne lidar. Remote Sensing of Environment, 2021. 263: p. 112567.
29.Chen, P., et al., OLE: A Novel Oceanic Lidar Emulator. IEEE Transactions on Geoscience and Remote Sensing, 2021. 59(11): p. 9730-9744.
30.Zhang, Z., et al., Polarization Properties of Reflection and Transmission for Oceanographic Lidar Propagating through Rough Sea Surfaces. Appl. Sci., 2020. 10(3): p. 1030.
31.Liu, H., et al., Iterative retrieval method for ocean attenuation profiles measured by airborne lidar. Applied Optics, 2020. 59(10): p. C42-C51.
32.Chen, P., et al., Detecting subsurface phytoplankton layer in Qiandao Lake using shipborne lidar. Optics Express, 2020. 28(1): p. 558-569.
33.Chen, P., et al., Semi-Analytic Monte Carlo Model for Oceanographic Lidar Systems: Lookup Table Method Used for Randomly Choosing Scattering Angles. Appl. Sci. , 2019,9(1): p. 48.
34.Chen, P., et al., A Feasible Calibration Method for Type 1 Open Ocean Water LiDAR Data Based on Bio-Optical Models. Remote Sensing, 2019. 11(2): p. 172.
35.Chen, P., et al., Semi-analytic Monte Carlo radiative transfer model of laser propagation in inhomogeneous sea water within subsurface plankton layer. Optics & Laser Technology, 2019. 111: p. 1-5.
36.Chen, P. and D. Pan, Ocean Optical Profiling in South China Sea Using Airborne LiDAR. Remote Sensing, 2019. 11(15): p. 1826.
37.Liu, H., et al., Subsurface plankton layers observed from airborne lidar in Sanya Bay, South China Sea. Optics Express, 2018. 26(22): p. 29134-29147.
38.Chen, P., et al., Coastal and inland water monitoring using a portable hyperspectral laser fluorometer. Marine Pollution Bulletin, 2017. 119(1): p. 153-161.
39.Chen, P., et al., Detection of water quality parameters in Hangzhou Bay using a portable laser fluorometer. Marine Pollution Bulletin, 2015. 93(1–2): p. 163-171.
40.Chen, P., D. Pan, and Z. Mao, Application of a laser fluorometer for discriminating phytoplankton species. Optics & Laser Technology, 2015. 67(0): p. 50-56.
41.Chen, P., D. Pan, and Z. Mao, Fluorescence measured using a field-portable laser fluorometer as a proxy for CDOM absorption. Estuarine, Coastal and Shelf Science, 2014. 146(0): p. 33-41.
42.Chen, P., D. Pan, and Z. Mao, Development of a portable laser-induced fluorescence system used for in situ measurements of dissolved organic matter. Optics & Laser Technology, 2014. 64(0): p. 213-219.


授权专利
(1)陈鹏,毛志华,张镇华,等.一种风生粗糙海面激光反射,透射矩阵计算方法:201910971951[P][2024-03-14].
(2)陈鹏,毛志华,刘航,等.一种基于迭代Klett的机载海洋激光雷达信号处理方法:201910911141[P][2024-03-14].
(3)陈鹏,毛志华,王天愚,et al.一种基于水体叶绿素浓度的星载海洋激光雷达探测能力评估方法:CN202010686197.4[P].CN111965608A[2024-03-14].
(4)陈鹏,张镇华,毛志华,等.一种光子计数星载海洋激光雷达探测仿真方法:CN202111362947.3[P].CN202111362947.3[2024-03-14].
(5)陈鹏,谢丛霜,张镇华,等.基于辐射传输参数应用卷积神经网络的水深地图反演方法:202410004085[P][2024-03-14].
(6)陈鹏,谢丛霜,张镇华,等.基于被动遥感光谱图像应用神经网络的光学浅水分类方法:202410004256[P][2024-08-14].
(7)毛志华,陈鹏,刘航,等.一种基于非对称谱形结构特征提取的赤潮藻区分方法.CN201811132730.1[2024-03-14].
(8)毛志华,袁大鹏,陈鹏,等.一种探测海洋光学参数的高光谱分辨率激光雷达系统:201911080500[P][2024-03-14].
(9)Mao Z, Yuan D, Chen P, et al. DUAL-WAVELENGTH HIGH-SPECTRAL RESOLUTION LIDAR SYSTEM BASED ON DUAL-STAGE VIRTUAL IMAGE PHASED ARRAY:US202117222986[P].US2022163640A1[2024-03-14].
(10)毛志华,袁大鹏,陈鹏,等.基于双级虚像相位阵列的双波长高光谱分辨率激光雷达系统.CN202011313723.9[2024-03-14].
(11)毛志华,袁大鹏,陈鹏,等.一种基于双级虚像相位阵列的布里渊散射测温激光雷达系统.CN201911328888.0[2024-03-14].
(12)陈鹏,谢丛霜,张镇华,等.一种基于自适应DBSCAN的激光雷达回波水下地形检测方法:CN202111232283.9[P].CN202111232283.9[2024-08-14].
(13)陈鹏,谢丛霜,张镇华,等.一种基于星载单光子激光主被动遥感融合的水深反演方法:CN202111232285.8[P].CN202111232285.8[2024-08-14].一种基于高斯卷积的海洋激光雷达快速仿真方法. 202111009955X. 发明专利. 实质审查
(14)陈鹏,张镇华,毛志华,等.一种基于水体漫衰减系数光谱依赖性的星载海洋激光雷达最优波段评估方法:CN202111009706.0[P].CN202111009706.0[2024-08-14].
(15)陈鹏,谢丛霜,张镇华,等.一种激光雷达回波检测海底地形信号异常点去除方法:CN202111233120.2[P].CN202111233120.2[2024-08-14].
(16)陈鹏,张镇华,毛志华,等.一种基于高斯卷积的海洋激光雷达快速仿真方法:202111009955[P][2024-08-14].