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Remote sensing retrieval of high-spatial-resolution land surface albedo

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：zhaocongcong20@mails.ucas.ac.cn
  • Introduction：赵聪聪，研究方向为定量遥感。E-mail： zhaocongcong20@mails.ucas.ac.cn
ZHAO Congcong12,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：wenjg@irsa.ac.cn
  • Introduction：闻建光，研究方向为遥感辐射传输建模与试验遥感。E-mail： wenjg@irsa.ac.cn
WEN Jianguang12*,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

YOU Dongqin1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

TANG Yong1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

CHEN Xi1,  
  • Affiliation：

    College of Global Change and Earth System Science, Beijing Normal University. Beijing 100875, China

LIU Qiang3

résumé

Land surface albedo is an important variable for controlling Earth radiation budget. It is also recognized as an Essential Climate Variable by the Global Climate Observing System. The progress of the high-spatial-resolution satellite development allows high-spatial-resolution albedo to provide important data for the research of local radiation and energy balance, regional climate, and ecological environment. However, albedo is a variable related to solar angle, wavelength, and atmospheric status. Thus, the estimation of high-spatial-resolution land surface albedo becomes challenging. Different methods of land surface albedo remote sensing estimation have been developed in the last two decades. These methods greatly improve the high-resolution albedo mapping ability. Summarizing and analyzing the proposed methods of high-spatial-resolution albedo are important to improve the accuracy of its product estimation further.Two fundamental problems of insufficient multiangle observation and multisensor band information for high-resolution albedo estimation are proposed by analyzing the basic principle of the existing albedo estimation. Four main methods of high-spatial-resolution albedo are summarized in the characteristics of the algorithm and application cases according to how the problem of insufficient understanding of land surface reflectance anisotropy is overcome. Lastly, the conclusion and prospect of the high-spatial-resolution albedo method development are also summarized.According to whether the land surface anisotropic reflection characteristics are considered, the current high-resolution albedo retrieval methods are divided into two basic types: the method of narrowband to broadband conversions and the method of Bidirectional Reflectance Distribution Functionconsideration. The latter type considers the surface anisotropic reflection characteristics in different ways. It also includes estimation based on high-resolution multiangle reflectance data, estimation based on combining high-resolution reflectance data with low-resolution reflectance data, and estimation based on empirical knowledge of BRDF/albedo.These proposed methods of obtaining high-spatial-resolution land surface albedo with the surface bidirectional reflection characteristic information directly or indirectly are still the mainstream idea. They alleviate the problem of missing high-resolution valid data to a certain extent. However, they are still limited because of the lack of effective data, such as the angle and band of the high-resolution remote sensing data and the lack of high-resolution BRDF a priori knowledge information. The development of a high-resolution albedo algorithm is a prospect for future research. It can potentially provide theoretical support for high-resolution land surface albedo product development.

mots-clés

land surface albedo;Bidirectional Reflectance Distribution Function (BRDF);remote sensing retrieval;narrowband to broadband;high spatial resolution satellite

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