滦河流域碳、水循环和能量平衡遥感综合试验总体设计
Comprehensive remote sensing experiment of carbon cycle, water cycle and energy balance in Luan River Basin
- 2021年25卷第4期 页码:856-870
纸质出版日期: 2021-04-07
DOI: 10.11834/jrs.20210341
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纸质出版日期: 2021-04-07 ,
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阎广建,赵天杰,穆西晗,闻建光,庞勇,贾立,张永光,陈德清,姚崇斌,曹志宇,雷永荟,姬大彬,陈良富,柳钦火,吕利清,陈镜明,施建成.2021.滦河流域碳、水循环和能量平衡遥感综合试验总体设计.遥感学报,25(4): 856-870
Yan G J, Zhao T J, Mu X H, Wen J G, Pang Y, Jia L, Zhang Y G, Chen D Q, Yao C B, Cao Z Y, Lei Y H, Ji D B, Chen L F, Liu Q H, Lyu L Q, Chen J M and Shi J C. 2021. Comprehensive remote sensing experiment of carbon cycle, water cycle and energy balance in Luan River Basin. National Remote Sensing Bulletin, 25(4):856-870
始于20世纪80年代的系列大型遥感试验开始系统研究地表物质和能量交换过程,对遥感与地球系统科学研究的结合起到重要作用,但是尚无综合利用多源遥感数据解决碳、水、能量循环问题的有效方案。遥感科学国家重点实验室于滦河上游地区组织开展基础性、多学科、多尺度的“碳、水循环和能量平衡遥感综合试验”。本次试验面向地球系统科学对遥感观测的最新要求,以遥感如何服务地—气过程研究为关键科学问题,开展星—机—地多尺度遥感综合观测和地面测量,论证中国自主设计的碳、水、能量相关卫星的技术指标,基于大场景真实结构模拟和多尺度综合观测构建虚拟遥感试验场,验证全波段遥感机理模型和复杂地表辐射传输机理。核心试验区位于地势较为平坦的闪电河流域和地形复杂的小滦河流域。闪电河流域主要地类为农田和草地,开展的试验以水循环和能量平衡遥感综合观测为主。小滦河流域主要地类为森林和草地,以碳循环遥感综合观测为主。两个试验区都开展了系统性的多架次飞行试验,并同步开展地面全波段、主被动协同观测。特别设计了一次长达165 km的大跨度飞行试验,横跨两个试验区,包含了地表类型和海拔高度的逐渐过渡。从2017年的预实验开始,整个试验为期5年。基于科学目标驱动、开放、协作、共享的原则,本次试验吸引了10个大型国家科研项目,4个卫星计划团队,19家单位200人次参加,是中国主导的又一次具有明确科学目标的大型多学科交叉遥感综合试验。
A series of large remote sensing experiments that began in the 1980s systematically studied the exchanges of matter and energy at the land surface
which played an important role in the integration of remote sensing and Earth system science. However
there are few effective solutions to comprehensively solve energy balance
carbon
and water cycles by using multi-source remote sensing data. The State Key Laboratory of Remote Sensing Science organized a fundamental
multi-disciplinary
multi-scale “Comprehensive Remote Sensing Experiment of Carbon Cycle
Water Cycle and Energy Balance in Luan River Basin” in the upper stream of Luan River. This experiment is oriented to the newly challenging requirements of Earth system science for remote sensing
and it is aimed to the scientific issue that how remote sensing can improve the Earth-atmosphere processes modelling. During the experiment
the spaceborne
airborne and ground-based (multi-scale) remote sensing and ground measurements were carried out to demonstrate China’s self-designed satellite missions related to the carbon cycle
water cycle and energy balance. The experimental data would be used to verify the full-band remote sensing models and the complex surface radiative transfer mechanism based on the real structure simulation over large-scale scenes. The core experimental area includes a relatively flat Shandian River basin and a complex Xiaoluan River basin. The experiments conducted in the Shandian River basin are mainly focused on comprehensive remote sensing observations of water cycle and energy balance with the main land cover types of cropland and grassland. While the experiments in the Xiaoluan River basin are mainly aimed to comprehensive remote sensing observations of carbon cycle with the main land cover types of forest and grassland. Systematic multi-sort airborne experiments and simultaneously full-band
active and passive ground-based observations were carried out at both experimental areas. A 165 km long-span flight
which spans the two experimental areas
was specially designed to cover the gradual transition of land cover types and altitude. Starting from the preliminary experiment in 2017
the entire experiment will last for five years. This experiment is scientific goal-driven
open
collaborative
and shared
and attracted 10 national-level scientific research projects
four satellite mission project teams
and 200 participants from 19 research institutes/universities. It is a China’s self-led scientific research on remote sensing and Earth system science
and it would promote multidisciplinary collaboration to address science challenges in Earth system science.
遥感试验碳循环水循环能量平衡滦河流域全波段主被动协同
remote sensing experimentcarbon cyclewater cycleenergy balanceLuan River basinfull-bandactive and passive synergy
Andre J C, Goutorbe J P, Perrier A, Becker F, Bessemoulin P, Bougeault P, Brunet Y, Brutsaert W, Carlson T and Cuenca R. 1988. Evaporation over Land-Surfaces: First Results from Hapex-Mobilhy Special Observing Period. An-nales Geophysicae, European Geosciences Union, 6: 477-492
Bach H, Mauser W. 2003. Methods and examples for remote sensing data assimilation in land surface process modeling. IEEE Transactions on Geoscience and Remote Sensing, 41(7): 1629-1637 [DOI: 10.1109/TGRS.2003.813270http://dx.doi.org/10.1109/TGRS.2003.813270]
Bauer P, Thorpe A and Brunet G. 2015. The Quiet Revolution of Numerical Weather Prediction. Nature, 525:47-55 [DOI: 10.1038/nature/4956http://dx.doi.org/10.1038/nature/4956]
Chahine M T. 1992. Gewex: The Global Energy and Water Cycle Experiment. Eos, Transactions American Geophysical Union, 73: 9-14 [DOI: 10.1029/91EO00007http://dx.doi.org/10.1029/91EO00007]
Chen Y M, Liang S, Wang J, Kim H Y and Martonchik J. 2008. Validation of Misr Land Surface Broadband Albedo. International journal of remote sensing, 29: 6971-6983 [DOI: 10.1080/01431160802199876http://dx.doi.org/10.1080/01431160802199876]
Fang H, Wei S and Liang S. 2012. Validation of Modis and Cyclopes Lai Products Using Global Field Measurement Data. Remote Sensing of Environment, 119: 43-54 [DOI: 10.1016/j.rse.2011.12.006http://dx.doi.org/10.1016/j.rse.2011.12.006]
Garrigues S, Lacaze R, Baret F, Morisette J, Weiss M, Nickeson J, Fernandes R, Plummer S, Shabanov N and Myneni R. 2008. Validation and Intercomparison of Global Leaf Area Index Products Derived from Remote Sensing Data. Journal of Geophysical Research: Biogeosciences, 113 [DOI: 10.1029/2007JG000635http://dx.doi.org/10.1029/2007JG000635]
Goutorbe J P, Lebel T, Tinga A, Bessemoulin P, Brouwer J, Dolman A J, Engman E T, Gash J H C, Hoepffner M, Kabat P, Kerr Y H, Monteny B, Prince S, Said F, Sellers P and Wallace J S. 1994. Hapex-Sahel: A Large-Scale Study of Land-Atmosphere Interactions in the Semiarid Tropics. Annales Geophysicae-Atmospheres Hydrospheres and Space Sciences, 12: 53-64 [DOI: 10.1007/s00585-994-0053-0http://dx.doi.org/10.1007/s00585-994-0053-0]
Grin A M and Mikhalenko Y A. 1993. International KUREX-91 subsatellite experiment. Mapping Sciences and Remote Sensing, 30(4): 334-337 [DOI: 10.1080/07493878.1993.10641946http://dx.doi.org/10.1080/07493878.1993.10641946]
Justice C O, Román M O, Csiszar I, Vermote E F, Wolfe R E, Hook S J, Friedl M, Wang Z, Schaaf C B and Miura T. 2013. Land and Cryosphere Products from Suomi Npp Viirs: Overview and Status. Journal of Geophysical Research: Atmospheres, 118: 9753-9765 [DOI: 10.1002/jgrd.50771http://dx.doi.org/10.1002/jgrd.50771]
Liang S. 2005. Quantitative Remote Sensing of Land Surfaces. John Wiley & Sons
Qi J, Xie D, Yin T, Yan G, Gastellu-Etchegorry J P, Li L, Zhang W, Mu X, Norford L K. 2019. LESS: LargE-Scale remote sensing data and image simulation framework over heterogeneous 3D scenes. Remote Sensing of Environment, 221:695-706 [DOI: 10.1016/j.rse.2018.11.036http://dx.doi.org/10.1016/j.rse.2018.11.036]
Sellers P J, Hall F G, Asrar G, Strebel D E and Murphye E. 1992. An Overview of the First International Satellite Land Surface Climatology Project (Islscp) Field Experiment (Fife). Journal of Geophysical Research, 97, 18: 345-318,371 [DOI: 10.1029/92JD02111http://dx.doi.org/10.1029/92JD02111]
Sellers P J, Hall F G, Kelly R D, Black A, Baldocchi D, Berry J, Ryan M, Ranson K J, Crill P M, Lettenmaier D P, Margolis H, Cihlar J, Newcomer J, Fitzjarrald D, Jarvis P G, Gower S T, Halliwell D, Williams D, Goodison B, Wickland D E and Guertin F E. 1997. Boreas in 1997: Experiment Overview, Scientific Results, and Future Directions. Journal of Geophysical Research-Atmospheres, 102: 28731-28769 [DOI: 10.1029/97jd03300http://dx.doi.org/10.1029/97jd03300]
Tian X,Li Z,Chen E,Liu Q,Yan G,Wang J,Niu Z,Zhao S,Li X,Pang Y,Su Z,Tol C,Liu Q,Wu C,Xiao Q,Yang L,Mu X,Bo Y,Qu Y,Zhou H,Gao S,Chai L,Huang H,Fan W,Li S,Bai J,Jiang L and Zhou J,The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE),PLos One,2015,10(9) [DOI:10.1371/journal.pone.0137545http://dx.doi.org/10.1371/journal.pone.0137545]
Wu X, Xiao Q, Wen J, You D and Hueni A. 2019. Advances in Quantitative Remote Sensing Product Validation: Overview and Current Status. Earth-Science Reviews, 196: 102875
Yan G, Chu Q, Tong Y, Mu X, Qi J, Zhou Y, Liu Y, Wang T, Xie D, Zhang W, Yan K, Chen S, Zhou H. 2020. An Operational Method for Validating the Downward Shortwave Radiation Over Rugged Terrains. IEEE Transactions on Geoscience and Remote Sensing, 59(1): 714-731 [DOI: 10.1109/TGRS.2020.2994384http://dx.doi.org/10.1109/TGRS.2020.2994384]
Zhao X, Liang S, Liu S, Yuan W, Xiao Z, Liu Q, Cheng J, Zhang X, Tang H and Zhang X. 2013. The Global Land Surface Satellite (Glass) Remote Sensing Data Processing System and Products. Remote Sensing, 5: 2436-2450 [DOI: 10.3390/rs5052436http://dx.doi.org/10.3390/rs5052436]
Geng D Y, Zhao T T, Shi J C, Hu L, Xu H and Hu J F. 2021. Surface Microwave Scattering Model Evaluation and Soil Moisture Retrieval based on Ground-based Radar Data. National Remote Sensing Bulletin, 25(4): 929-940
耿德源, 赵天杰, 施建成, 胡路, 徐红新, 胡建峰. 2021. 基于地基雷达的微波面散射模型对比与土壤水分反演. 遥感学报, 25(4): 929-940 [DOI: 10.11834/jrs.20219305http://dx.doi.org/10.11834/jrs.20219305]
Li X, Ma M, Wang J, Liu Q, Che T, Hu Z, Xiao Q, Liu Q, Su P, Chu R, Jin R, Wang W, Ran Y. 2008. Simultaneous Remote Sensing and Ground-based Experiment in the Heihe River Basin: Scientific Objectives and Experiment Design. Advances in Earth Science, 23(9): 897-914
李新, 马明国, 王建, 刘强, 车涛, 胡泽勇, 肖青, 柳钦火, 苏培玺, 楚荣忠, 晋锐, 王维真 and 冉有华. 2008. 黑河流域遥感—地面观测同步试验:科学目标与试验方案. 地球科学进展, 23(9):897-914
Li X, Liu S M, Ma M G, Xiao Q, Liu Q H, Jin R, Che T, Wang W Z, Qi Y, Li H Y, Zhu G F, Guo J W, Ran Y H, Wen J G and Wang S G. 2012b. HiWATER: An integrated remote sensing experiment on hydrological and ecological processes in the Heihe River Basin. Advances in Earth Science, 27(5): 481-498
李新, 刘绍民, 马明国, 肖青, 柳钦火, 晋锐, 车涛, 王维真, 祁元, 李弘毅, 朱高峰, 郭建文, 冉有华, 闻建光, 王树果. 2012. 黑河流域生态-水文过程综合遥感观测联合试验总体设计. 地球科学进展, 27(5): 481-498
Su Y, Li N, Luan Y, Zhao T, Xu H, Zhao F, Yao C, Lv L, Hu L, Geng D. 2021. Radiometric calibration of a new airborne microwave sensor for soil moisture mapping at L-band. National Remote Sensing Bulletin, 25(4): 918-928
孙彦龙,李恩晨,栾英宏,赵天杰,徐红新,赵峰,姚崇斌,吕利清,胡路,耿德元. 2021. 机载土壤水分微波探测仪定标技术研究. 遥感学报, 25(4): 918-928 [DOI: 10.11834/jrs.20210358http://dx.doi.org/10.11834/jrs.20210358]
Mu X, Yan G, Zhou H, Pang Y, Qiu F, Zhang Q, Zhang Y, Zhong B, Song J, Sun R, Jiang L, Jiao Z, Zhang W, Li F. 2021. Airborne comprehensive remote sensing experiment of forest and grass resources in Xiaoluanhe River Basin. National Remote Sensing Bulletin, 25(4): 888-903
穆西晗,阎广建,周红敏,庞勇,邱凤,张乾,张永光,仲波,宋金玲,孙睿,蒋玲梅,焦子锑,张吴明, 李凡. 2021. 小滦河流域复杂地表碳循环遥感综合试验. 遥感学报, 25(4): 888-903 [DOI: 10.11834/jrs.20210305http://dx.doi.org/10.11834/jrs.20210305]
Pang Y, Liang X, Jia W, Si L, Yan G, Shi J, 2021. Airborne comprehensive remote sensing experiment of forest and grass resources in Xiaoluanhe River Basin. National Remote Sensing Bulletin, 25(4): 904-917
庞勇, 梁晓军, 荚文, 斯林, 阎广建, 施建成. 2021. 小滦河流域林草资源机载综合遥感实验. 遥感学报, 25(4): 904-917 [DOI: 10.11834/jrs.20210222http://dx.doi.org/10.11834/jrs.20210222]
Wang J M. 1999. Land surface progress experiments and interaction study in China——from HEIFE to IMGRASS and GAME-Tibet/TIPEX. Plateau Meteorology, 18(3): 280-294
王介民. 1999. 陆面过程实验和地气相互作用研究——从HEIFE到IMGRSASS和GAME-Tibet/TIPEX. 高原气象, 18(3): 280-294
Zheng C, Hu G, Chen Q, Jia L. 2021. Impact of Remote Sensing Soil Moisture on the Evapotranspiration Estimation. National Remote Sensing Bulletin, 25(4): 911-1000
郑超磊, 胡光成, 陈琪婷, 贾立. 2021. 遥感土壤水分对蒸散发估算的影响研究. 遥感学报, 25(4): 911-1000 [DOI: 10.11834/jrs.20210038http://dx.doi.org/10.11834/jrs.20210038]
Zheng D and Chen S. 2001. Progress and disciplinary frontiers of geographical research. Advances in Earth Science. 16(5): 599-606.
郑度, 陈述彭. 2001. 地理学研究进展与前沿领域. 地球科学进展, 16(5): 599-606
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