Effect of soil surface roughness and scene components on soil surface bidrectional reflectance factor

被引:18
作者
Wang, Z. [1 ]
Coburn, C. A. [2 ]
Ren, X. [1 ]
Teillet, P. M. [1 ]
机构
[1] Univ Lethbridge, Dept Phys & Astron, Lethbridge, AB T1K 3M4, Canada
[2] Univ Lethbridge, Dept Geog, Lethbridge, AB T1K 3M4, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Bidirectional reflectance factor; goniometer; soil reflectance; remote sensing; BIDIRECTIONAL REFLECTANCE; VEGETATION; MODEL; GONIOMETER; BRDF; CANOPIES; FIELD;
D O I
10.4141/CJSS2011-069
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
Wang, Z., Coburn, C. A., Ren, X. and Teillet, P. M. 2012. Effect of soil surface roughness and scene components on soil surface BRF. Can. J. Soil Sci. 92: 297-313. Bidirectional Reflectance factor (BRF) data of both rough [surface roughness index (SRI) of 51%] and smooth soil surfaces (SRI of 5%) were acquired in the laboratory under 300 illumination zenith angle using a Specim V10E imaging spectrometer and an Ocean Optics non-imaging spectrometer mounted on the University of Lethbridge Goniometer System version 2.5 (ULGS-2.5) and version 2.0 (ULGS-2.0), respectively. Under controlled laboratory conditions, the rough soil surface exhibited higher spectral reflectance than the smooth surface for most viewing angles. The BRF of the rough surface varied more than the smooth surface as a function of the viewing zenith angle. The shadowing effect was stronger for the rough surface than for the smooth surface and was stronger in the forward-scattering direction than in the backscattering direction. The pattern of the BRF generated with the non-image based data was similar to that generated with the whole region of interest (ROI) of the image-based data, and that of the whole ROI of the image-based data was similar to that of the illuminated scene component. The BRF of the smooth soil surface was dominated by illuminated scene component, i.e., the sunlit pixels, whereas the shaded scene component, i.e., the shaded pixels, was a larger proportion of the BRF of the rough soil surface. The image-based approach allowed the characterization of the contribution of spatial components in the field of view to soil BRF and improved our understanding of soil reflectance.
引用
收藏
页码:297 / 313
页数:17
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