سابِق|تال

Airborne comprehensive remote sensing experiment of forest and grass resources in Xiaoluan River Basin

  • role： First author第一作者
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

  • Email：muxihan@bnu.edu.cn
  • Introduction：穆西晗，1981年生，男，副教授, 研究方向为多角度植被遥感。E-mail: muxihan@bnu.edu.cn
MU Xihan1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

  • Email：gjyan@bnu.edu.cn
  • Introduction：阎广建，1972年生，男，教授，研究方向为定量遥感。E-mail： gjyan@bnu.edu.cn
YAN Guangjian1*,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

ZHOU Hongmin1,  
  • Affiliation：

    Institute of Forest Resource Information Technique, Chinese Academy of Forestry, Beijing 100091, China

    Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China

PANG Yong23,  
  • Affiliation：

    International Institute for Earth System Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210023, China

QIU Feng45,  
  • Affiliation：

    International Institute for Earth System Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210023, China

ZHANG Qian45,  
  • Affiliation：

    International Institute for Earth System Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210023, China

ZHANG Yongguang45,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

XIE Donghui1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

ZHOU Yingji1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences,Beijing 100094, China

ZHAO Tianjie6,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences,Beijing 100094, China

ZHONG Bo6,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

SONG Jinling1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

SUN Rui1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

JIANG Lingmei1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

YIN Siyang1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

LI Fan1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

JIAO Ziti1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing;Engineering Research Center for Globe Land Remote Sensing Products, Beijing 100875, China

QU Yonghua1,  
  • Affiliation：

    School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China

    Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai), Zhuhai 519080, China

ZHANG Wuming78,  
  • Affiliation：

    Saihanba Mechanical Forest Farm of Hebei Province, Chengde 068450, China

CHENG Shun9,  
  • Affiliation：

    Saihanba Mechanical Forest Farm of Hebei Province, Chengde 068450, China

CUI Tongxiang9

ملخص

Comprehensive remote sensing experiments play an important role in the development of remote sensing science and technology. Both the fundamental research and application of remote sensing need to be supported by experiments. The State Key Laboratory of Remote Sensing Science (SLRSS) has organized a large remote sensing experiment for the studies of carbon cycle over complex land surfaces in the upper reaches of the Xiaoluan River basin since 2018. This paper is targeted to introduce the objectives, study regions, observation parameters, methods and prospects of the experiment and to provide a useful reference for the design of remote sensing experiments.The experiment adopted the satellite, airborne, and ground-based remote sensing, collected the data from the satellites in orbit and the remote sensing products covering the study region. The aerial and Unmanned Aerial Vehicle (UAV) remote sensing experiments were carried out with optical sensors to obtain key parameters of water cycle, carbon cycle and energy flow. Ground observation experiments were synchronously carried out to monitor the key parameters of atmosphere, vegetation and soil.Rich amount of remote sensing data were collected from ground observation experiments, UAV and aerial remote sensing experiments. Driven by the experiment, the SLRSS set up a number of comprehensive observation towers in the experimental area in 2020, equipped with a variety of observation instruments and started long time series observation task. The construction of the large scale virtual scenery for remote sensing experiment and the operation of the BEPS (Boreal Ecosystem Productivity Simulator) model are being carried out.The comprehensive experiment on carbon cycle at complex surfaces in Xiaoluan River basin has effectively obtained the key parameters of surface water, energy and carbon cycles by using the satellite, airborne, and ground-based remote sensing. The experiment provides the important basic data for the development of remote sensing mechanism model, inversion method and scale transformation research. It has been used to establish a comprehensive validation platform for remote sensing mechanism models, to improve the applicability of remote sensing products at complex surfaces, and to clarify the physical process of carbon-water coupling on watershed scale.

مفهوم

remote sensing;comprehensive experiment;watershed scale;carbon cycle;Xiaoluan River;Saihanba

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