Development of a snow kernel to better model the anisotropic reflectance of pure snow in a kernel-driven BRDF model framework

Jiao, Ziti; Ding, Aili; Kokhanovsky, Alexander A.; Schaaf, Crystal B.; Bréon, François‐Marie; Dong, Yadong; Wang, Zhuosen; Liu, Yan; Zhang, Xiaoning; Yin, Shuai; Cui, Lei; Mei, Linlu; Chang, Yaxuan

doi:10.1016/j.rse.2018.11.001

Cited by 68 publications

(74 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The POLDER BRDF database was described in detail in previous studies [1,15,32,34,35,50] and the database had a spatial resolution of approximately 6 × 7 km. The POLDER radiometer onboard the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from Lidar (PARASOL) satellite acquired data in 9 spectral channels, in which 3 of which (490, 670 and 865 nm) measured the polarized reflectance of the incident light.…”

Section: Polder Brdf Databasementioning

confidence: 99%

“…For the purpose of this study, we also selected pure snow data. Additionally, we removed the datasets with SZAs > 70 • and VZAs > 70 • [32]. Finally, 682 pixels were selected for model comparison.…”

Section: Polder Brdf Databasementioning

confidence: 99%

“…Recently, Jiao et al proposed a snow kernel in the kernel-driven BRDF model framework to consider snow scattering characteristics [32]. Thus, we further improve the RTR model by replacing the GO scattering kernel with the snow kernel in Equation (2) to characterize snow scatterings (hereafter referred to as the RTS model).…”

Section: Rts Modelmentioning

confidence: 99%

“…The original semi-empirical, kernel-driven BRDF models have been extensively utilized in many aspects of remote sensing due to their global applicability and physically-based algorithms [1,13,[32][33][34][35][36][37], such as generating global albedo products. Despite their wide applications, recent studies have indicated that kernel-driven BRDF models that were originally derived based on simplified scenarios for the continuous and discrete vegetation canopies of soil-vegetation systems must be further developed for snow scatterings.…”

Section: Introductionmentioning

confidence: 99%

“…To characterize strong forward-scattering behaviours at large illuminating and viewing geometries, Qu et al added a forward-scattering kernel through the simplification of the RPV model to the kernel-driven BRDF model framework to estimate the surface albedo from multi-angle reflectances of the top of the atmosphere [38]. Recently, Jiao et al derived a snow kernel from the ART model in the kernel-driven BRDF model framework to better model the anisotropic reflectance of the snow surface [32], as the RPV model was not specifically developed for investigating snow scattering properties. This snow kernel in the kernel-driven BRDF model framework has been validated by a variety of snow BRDF data and has been reported to have high accuracy in capturing the snow bidirectional signatures.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Evaluation of the Snow Albedo Retrieved from the Snow Kernel Improved the Ross-Roujean BRDF Model

Ding¹,

Jiao²,

Dong³

et al. 2019

Remote Sensing

View full text Add to dashboard Cite

The original kernel-driven bidirectional reflectance distribution function (BRDF) models were developed based on soil-vegetation systems. To further improve the ability of the models to characterize the snow surface scattering properties, a snow kernel was derived from the asymptotic radiative transfer (ART) model and used in the kernel-driven BRDF model framework. However, there is a need to further evaluate the influence of using this snow kernel to improve the original kernel-driven models in snow albedo retrieval applications. The aim of this study is to perform such an evaluation using a variety of snow BRDF data. The RossThick-Roujean (RTR) model is used as a framework for taking in the new snow kernel (hereafter named the RTS model) since the Roujean geometric-optical (GO) kernel captures a neglectable hotspot effect and represents a more prominent dome-shaped BRDF, especially at a small solar zenith angle (SZA). We obtained the following results: (1) The RTR model has difficulties in reconstructing the snow BRDF shape, especially at large SZAs, which tends to underestimate the reflectance in the forward direction and overestimate reflectance in the backward direction for various data sources. In comparison, the RTS model performs very well in fitting snow BRDF data and shows high accuracy for all data. (2) The RTR model retrieved snow albedos at SZAs = 30°–70° are underestimated by 0.71% and 0.69% in the red and near-infrared (NIR) bands, respectively, compared with the simulation results of the bicontinuous photon tracking (bic-PT) model, which serve as “real” values. However, the albedo retrieved by the RTS model is significantly improved and generally agrees well with the simulation results of the bic-PT model, although the improved model still somewhat underestimates the albedo by 0.01% in the red band and overestimates the albedo by 0.05% in the NIR band, respectively, at SZAs = 30°–70°, which may be negligible. (3) The albedo derived by these two models shows a high correlation (R2 > 0.9) between the field-measured and Polarization and Directionality of the Earth's Reflectances (POLDER) data, especially for the black-sky albedo. However, the albedo derived using the RTR model is significantly underestimated compared with the RTS model. The RTR model underestimates the black-sky albedo (white-sky albedo) retrievals by 0.62% (1.51%) and 0.93% (2.08%) in the red and NIR bands, respectively, for the field-measured data. The shortwave black-sky and white-sky albedos derived using the RTR model for the POLDER data are underestimated by 1.43% and 1.54%, respectively, compared with the RTS model. These results indicate that the snow kernel in the kernel-driven BRDF model frame is more accurate in snow albedo retrievals and has the potential for application in the field of the regional and global energy budget.

show abstract