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Preliminary verification of Landsat satellite albedo from airborne WIDAS data

  • role： First author第一作者
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

  • Email：yimirs@126.com
  • Introduction：何丹丹，1992年生，女，硕士研究生，研究方向为定量遥感、地表二向性反射和植被结构参数反演。E-mail：yimirs@126.com
Dandan HE1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China

  • Email：jiaozt@bnu.edu.cn
  • Introduction：焦子锑，1970年生，男，副教授，研究方向为定量遥感、地表各向异性反射的建模与应用，多角度信号用于地表分类。E-mail：jiaozt@bnu.edu.cn
Ziti JIAO12*,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

Yadong DONG1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

Xiaoning ZHANG1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

Anxin DING1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

Siyang YIN1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

Lei CUI1,  
  • Affiliation：

    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

Yaxuan CHANG1

Resümee

Surface albedo is one of the key parameters in the investigation of surface energy balance. Accurate inversion of surface albedo is important for the evaluation on climate change. For the multi-angle reflectance data of an airborne Wide-angle Infrared Dual-mode line/area Array Scanner (WIDAS) in Genhe Region, Inner Mongolia, the Bidirectional Reflectance Distribution Function (BRDF) archetype-based algorithm was initially applied in forest experimental area. First, we extracted four BRDF archetypes based on the hotspot-corrected linear kernel-driven BRDF models, i.e., RossThickChen-LiSparseReciprocal and anisotropic flat index, in the experimental region of Genhe. Then, we applied these archetypes as a priori knowledge to the albedo inversion of WIDAS airborne data in the forest of the region. Finally, the albedo of WIDAS and the data observed by surface flux tower were used to verify Landsat albedo. In this study, we analyzed the robustness of the BRDF archetype-based algorithm in retrieving small-angle observations in forest experimental area. The results are as follows. (1) The surface albedo retrieved by the BRDF archetype-based algorithm has high accuracy and stability, and the total Root Mean Square Error (RMSE) of Landsat albedo was approximately 0.02 and deviation was 0.0057. (2) Given the available observation range of WIDAS in the experimental area of Genhe in 2016 was 25°, the BRDF archetype-based algorithm showed robust inversion capability in small observation angles. Therefore, when the multi-angle observation range was narrow, the albedo of airborne WIDAS retrieved by the BRDF archetype-based algorithm can be in good agreement with that of the Landsat, providing a means to effectively address the problem and validate the satellite albedo.

Schlüsselwort

Wide-angle Infrared Dual-mode line/area Array Scanner (WIDAS);kernel-driven BRDF model;AFX;BRDF archetype;Landsat;surface albedo

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