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Review of optical multi-angle quantitative remote sensing

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

  • Email：gjyan@bnu.edu.cn
  • Introduction：阎广建，1972年生,男，教授，研究方向为多角度遥感、地表辐射收支、植被结构参数卫星反演与地面测量。E-mail: gjyan@bnu.edu.cn
YAN Guangjian,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

JIANG Hailan,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

YAN Kai,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

CHENG Shiyu,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

SONG Wanjuan,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

TONG Yiyi,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

LIU Yanan,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

QI Jianbo,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

MU Xihan,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

ZHANG Wuming,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

XIE Donghui,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Land Surface Remote Sensing Data Product Engineering Technology Research Center, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

ZHOU Hongmin

Resümee

With the development of remote sensing technology, two or more viewing directions become available for the same target, and thus a new research field – multi-angle remote sensing appears. Compared with the traditional remote sensing which only views the ground surface in one direction, multi-angle remote sensing provides angle-dimensional information and improves the capability of obtaining vegetation structure parameters. It helps to improve the retrieval accuracy of key biophysical parameters and provides better data support for the research of ecological environment and climate change. After a detailed analysis of the publications in multi-angle remote sensing, we summarize the basic concepts, characteristics, advantages and developments of multi-angle remote sensing. Multi-angle remote sensing platforms vary from ground-based, airborne to spaceborne observation equipment. The first ground-based observation equipment appeared in 1952. All the ground-based equipment is classified as the fixed field of view mode or the changeable field of view mode. For the airborne or spaceborne platforms, only the fixed field of view mode is acceptable due to the heterogeneity of the land surfaces. With the development of UAV technique, the airborne multi-angle remote sensing is becoming more and more popular due to its flexibility and high spatial resolution. The multi-angle models play important roles in parameters inversion. Classic multi-angle remote sensing models include radiative transfer models, geometric optical models, hybrid models, and computer simulation models. They are all physical models which are developed based on some assumptions and theoretical analysis. Semi-empirical models combine the advantages of the empirical model and the physical model, as a result, they are simple and stable in inversion. The most widely used semi-empirical model is the linear kernel driven model used by the operational MODIS BRDF/albedo products algorithm. With the development of observing equipment and models, multi-angle remote sensing is widely used in many applications. Due to the anisotropic reflection characteristic, land surface albedo can only be retrieved by multi-angle remote sensing with high accuracy. Multi-angle remote sensing shows great potentials in vegetation structural parameters inversion which include the clumping index, LAI, FVC profile and canopy height. It has been found to be superior in vegetation type identification than the traditional vertical observation. Multi-angle remote sensing is also very useful in the cloud and aerosol parameters retrieval, such as the cloud albedo, height and types, as well as the aerosol optical depth and shapes. Large difference of optical scattering between the cloud and ice/snow in different viewing directions makes the identification of these covers easier with multi-angle remote sensing. The sea ice roughness can also be retrieved by multi-angle observations. In the last of this paper, we put forward the prospects of multi-angle optical quantitative remote sensing. As the multi-angle remote sensing observation data based on spaceborne, airborne, and ground platforms become more and more abundant, the main research direction of multi-angle remote sensing in the future should focus on the following aspects: developing multi-angle reflection/radiation models for complex surfaces, enhancing the preprocessing capabilities of multi-angle remote sensing data, and promoting the comprehensive abilities of multi-source data integration in application, etc.

Schlüsselwort

multi-angle remote sensing;Bidirectional Reflectance Distribution Function (BRDF);sensor;radiative transfer model;geometric optical model

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