地球科学进展 ›› 2019, Vol. 34 ›› Issue (8): 842 -854. doi: 10.11867/j.issn.1001-8166.2019.08.0842

综述与评述 上一篇    下一篇

无人机涡动相关通量观测技术研究综述
孙义博 1, 2( ),苏德 1, 2( ),全占军 1,商豪律 3,耿冰 4,林兴稳 5,荆平平 6,包扬 1, 2,赵艳华 1, 2,杨巍 1, 2   
  1. 1. 中国环境科学研究院 中国环境科学研究院环境生态科学研究所 环境基准与风险评估国家重点实验室 国家环境保护区域生态过程与功能评估重点实验室,北京 100021
    2. 井冈山生态环境综合观测研究站,江西 井冈山 343699
    3. 中国科学院空天信息研究院数字地球重点实验室,北京 100094
    4. 中国社会科学院城市发展与环境研究所,北京 100028
    5. 浙江师范大学地理与环境科学学院,浙江 金华 321004
    6. 国家海洋技术中心,天津 300112
  • 收稿日期:2019-04-21 修回日期:2019-06-26 出版日期:2019-08-10
  • 通讯作者: 苏德 E-mail:sunyb68@163.com;sude@craes.org.cn;sunyb68@163.com
  • 基金资助:
    国家重点研发计划项目“长三角城市群生态安全评估与风险预测预警技术”(2016YFC0502702);生态环境部生态环境保护监管项目“生物多样性调查与评估”(2019HJ2096001006)

Overview of the UAV—Based Eddy Covariance Fluxes Measurements Technique

Yibo Sun 1, 2( ),De Su 1, 2( ),Zhanjun Quan 1,Haolü Shang 3,Bing Geng 4,Xingwen Lin 5,Pingping Jing 6,Yang Bao 1, 2,Yanhua Zhao 1, 2,Wei Yang 1, 2   

  1. 1. Institute of Environmental Ecology, State Key Laboratory of Environmental Criteria and Risk Assessment, State Environment Protection Key Laboratory of Regional Eco-Process and Function Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100021, China
    2. Integrated Ecological Observation and Research Station of Jinggangshan, Jinggangshan Jiangxi 343699, China
    3. Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    4. Institute for Urban and Environment Studies, Chinese Academy of Social Sciences, Beijing 100028, China
    5. College of Geography and Environment Science, Zhejiang Normal University, Jinhua Zhejiang 321004, China
    6. National Ocean Technology Center, Tianjin 300112, China
  • Received:2019-04-21 Revised:2019-06-26 Online:2019-08-10 Published:2019-10-11
  • Contact: De Su E-mail:sunyb68@163.com;sude@craes.org.cn;sunyb68@163.com
  • About author:Sun Yibo (1988-), male, Ordos City, Inner Mongolia Autonomous Region, Postdoctor. Research areas include observation and modeling of land-surface process. E-mail: sunyb68@163.com |Sun Yibo (1988-), male, Ordos City, Inner Mongolia Autonomous Region, Postdoctor. Research areas include observation and modeling of land-surface process. E-mail: sunyb68@163.com
  • Supported by:
    the National Key Research and Development Program of China "Ecological security assessment;risk prediction and early warning technology for the Yangtze Delta Urban Agglomeration"(2016YFC0502702);The Ecology and Environment Protection and Supervision Project of the Ministry of Ecology and Environment;China "The biodiversity survey and assessment"(2019HJ2096001006)

机载涡动相关方法是进行区域尺度地表通量观测最有效的方式之一,其观测的空间尺度与陆面过程模式的网格尺度以及遥感影像的像元尺度一致,对区域及全球尺度地表通量模拟等研究具有重要意义。基于无人机的涡动相关方法能够实现对地表通量的多时段和多架次观测,成本低廉且观测结果可靠,是机载通量观测技术的一个重要发展方向。在介绍机载涡动相关方法主要技术特点的基础上,综述了现有无人机通量观测系统的研究进展,包括无人机特征及搭载的主要观测仪器类型,典型无人机通量观测系统的集成方式及其观测案例的讨论和分析。然后介绍了影响无人机通量观测的主要不确定性来源,最后对目前无人机通量观测系统的不足进行了总结,并对其发展前景进行了展望。

Airborne Eddy Covariance (EC) method is one of the most effective ways to measure the turbulent fluxes over regional scale directly. The turbulent fluxes from airborne EC method have the same spatial scale with the pixel scale of remote sensing image and the grid scale of land-surface models, which is very important for the simulation of regional or global land-surface fluxes. UAV-based eddy covariance method could achieve the observation of turbulent fluxes in a multi-period and multi-sorties way, and the observation result is reliable and the application is inexpensive. It is an important development direction for airborne flux observation technique. After the introduction of the main technical characteristics of the airborne EC method, this paper reviewed the worldwide progress in UAV-based fluxes measurements system from these aspects of the specifications of the UAVs, the integrated instruments, and the analysis of the application cases. Then, the main sources of uncertainty affecting the UAV-based fluxes measurements were discussed. At last, the shortcomings of the current UAV-based flux observation system were summarized. A brief outlook about UAV-based fluxes measurements technique was also given.

中图分类号: 

图1 机载涡动相关方法数据处理流程
Fig.1 The flowchart of airborne Eddy Covariance method
图2 湍流探头坐标系与地球坐标系转换示意图
Fig.2 Diagram of coordinate transformation between turbulent probe coordinate system and Earth coordinate system
图3 SUMO无人机通量观测设备[ 42 ]
Fig.3 SUMO instrumented for turbulence fluxes measurements [ 42 ]
图4 SUMO观测的三维风速方差与湍流动能的均值与60 m观测塔超声风速计观测结果的对比[ 43 ]
Fig.4 Averaged standard deviations of 3-dimension wind ( σ U , σ V , σ W ) and averaged Turbulence Kinetic Energy (TKE) from SUMO against the observed results from sonic anemometer of the 60 m meteorological tower [ 43 ]
表1 用于涡动相关观测的中型无人机的主要性能
Table 1 Specifications of medium UAV used in Eddy Covariance fluxes observation
表2 中型无人机搭载的涡动相关观测仪器及其他观测设备汇总
Table 2 Summary of the major Eddy Covariance payload and other sensors carried on the medium UAV
图5 M2AV无人机通量观测设备[ 48 ]
Fig.5 M2AV instrumented for turbulence fluxes measurements [ 48 ]
图6 M2AV观测的温度(a)、湿度(b)和风速(c)廓线与塔、廓线雷达、微波辐射计以及无线电探空仪观测的对比[ 49 ]
Fig.6 Vertical profiles of virtual temperature(a), relative humidity(b) and wind speed(c) measured by M2AV, sodar/RASS, wind profiler/RASS, tower, microwave radiometer profiler and radiosonde [ 49 ]
表3 用于涡动相关通量观测的大型无人机主要性能指标
Table 3 Specifications of large UAV used in Eddy Covariance fluxes observation
表4 大型无人机搭载的主要涡动相关观测仪器及其他观测设备汇总
Table 4 Summary of the major Eddy Covariance payload and other sensors carried on the large UAV
型号 风速 位置姿态 温度 湿度 压强 其他传感器 主要观测变量
UMARS2 5孔湍流探头 IMU (xsense MTi-G) 热电偶,热敏电阻 露点湿度计 (Meteolabor AG 'Snow White') 5孔湍流探头 感热、风速、风向、相对湿度、大气压强
Manta 5孔湍流探头 GPS/INS (C-Migits-Ⅲ) 电阻式湿度传感器(Honeywell HIH-4602-C)

氪湿度计(Campbell),

电阻式湿度传感器(Honeywell HIH-4602-C)

5孔湍流探头 激光测高仪 潜热、风速、风向、大气温度/湿度、气压
Manta C1 9孔湍流探头 IMU (Honeywell, HG1700 AG58),GPS (NovAtel OEMV-3 RTK-DGPS),NovAtel SPAN circuitry(用于GPS和IMU数据耦合) 光纤温度探针,温湿传感器探针(Vaisala, HMP45C)

氪湿度计(Campbell),

温湿传感器探针(Vaisala, HMP45C)

9孔湍流探头 激光测高仪、辐射传感器、数码相机 感热、潜热、风速、风向、大气温度/湿度、气压、辐射
ScanEagle 9孔湍流探头 IMU (Northrop Grumman, LN200),GPS (NovAtel OEMV-3 RTK-DGPS),NovAtel SPAN circuitry(同于GPS和IMU数据耦合) 光纤温度探针,温湿传感器探针(Vaisala, HMP45C)

氪湿度计(Campbell),

温湿传感器探针(Vaisala,HMP45C)

9孔湍流探头 辐射传感器、数码相机、红外相机、海面温度传感器、激光测高仪 感热、潜热、风速、风向、大气温度/湿度、气压、辐射、海面温度
ALADINA 5孔湍流探头 GPS/IMU (SBG, IG500N) 热电偶,铂电阻温度计,温湿传感器探针(Vaisala, HMP110) 温湿传感器探针(Vaisala,HMP110) 5孔湍流探头 气溶胶测量装置、黑炭测量装置、辐射测量传感器 感热、风速、风向、大气温度/湿度、气压、辐射
图7 Manta C1无人机通量观测设备[ 28 ]
Fig.7 Manta C1 instruments for turbulence fluxes measurements [ 28 ]
图8 Manta C1观测的动量通量(ab)和潜热通量(c)与2套地面涡相关设备(Sonic 1, Sonic 2)观测的对比[ 28 ]
Fig. 8 Comparison of the momentum (a, b) and latent heat (c) fluxes measured by Manta C1 with those measured by instruments of ground-based Eddy Covariance (Sonic 1, Sonic 2) during ground-vehicle-based tests [ 28 ]
表5 主要无人机风速测量的多孔机载湍流探头汇总
Table 5 Summary of the multi-hole probe used by UAV-based wind measurement
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