Rugged terrain, including mountains, hills, and some high lands are typical land surfaces around the world. As a physical parameter for characterizing the anisotropic reflectance of the land surface, the importance of the bidirectional reflectance distribution function (BRDF) has been gradually recognized in the remote sensing community, and great efforts have been dedicated to build BRDF models over various terrain types. However, on rugged terrain, the topography intensely affects the shape and magnitude of the BRDF and creates challenges in modeling the BRDF. In this paper, after a brief introduction of the theoretical background of the BRDF over rugged terrain, the status of estimating land surface BRDF properties over rugged terrain is comprehensively reviewed from a historical perspective and summarized in two categories: BRDFs describing solo slopes and those describing composite slopes. The discussion focuses on land surface reflectance retrieval over mountainous areas, the difference in solo slope and composite slope BRDF models, and suggested future research to improve the accuracy of BRDFs derived with remote sensing satellites.

Heterogeneous terrain significantly complicates signals received by airborne or satellite sensors. It has been demonstrated that both solar direct beam and diffuse skylight illumination conditions are significant factors influencing the anisotropy of reflectance over mountainous areas. Several models and methods have been developed to account for topographic effects on surface reflectance at the pixel level in remote sensing. However, subtopographic effects are generally neglected for low-spatial-resolution pixels due to the complex law of radiative transfer and the limitations of higher spatial resolution digital elevation models, which can lead to deviations in reflectance estimation. Accurately estimating the subtopographic effects on anisotropic reflectance over composite sloping terrain under different illumination conditions presents a challenge for remote sensing models and applications. In this paper, the diffused equivalent slope model (dESM) was developed, which is an anisotropic reflectance simulation model coupled with diffuse skylight over composite sloping terrain. The corresponding subtopographic impact factor was also proposed to exhibit how microslope topography affects reflectance over composite sloping terrain under different illumination conditions. Simulated reflectance data sets simulated by the radiosity method and Moderate Resolution Imaging Spectroradiometer reflectance data were used to evaluate the performance of the dESM model. The results reveal that the dESM model can accurately capture the reflectance anisotropy over composite sloping terrain under different illumination conditions, and the subtopographic impact factor can account for the effects of microslope topography, shadow, and illumination conditions.

Topography complicates the modeling and retrieval of land surface albedo due to shadow effects and the redistribution of incident radiation. Neglecting topographic effects may lead to a significant bias when estimating land surface albedo over a single slope. However, for rugged terrain, a comprehensive and systematic investigation of topographic effects on land surface albedo is currently ongoing. Accurately estimating topographic effects on land surface albedo over a rugged terrain presents a challenge in remote sensing modeling and applications. In this paper, we focused on the development of a simplified estimation method for snow-free albedo over a rugged terrain at a 1-km scale based on a 30-m fine-scale digital elevation model (DEM). The proposed method was compared with the radiosity approach based on simulated and real DEMs. The results of the comparison showed that the proposed method provided adequate computational efficiency and satisfactory accuracy simultaneously. Then, the topographic effects on snow-free albedo were quantitatively investigated and interpreted by considering the mean slope, subpixel aspect distribution, solar zenith angle, and solar azimuth angle. The results showed that the more rugged the terrain and the larger the solar illumination angle, the more intense the topographic effects were on black-sky albedo (BSA). The maximum absolute deviation (MAD) and the maximum relative deviation (MRD) of the BSA over a rugged terrain reached 0.28 and 85%, respectively, when the SZA was 60° for different terrains. Topographic effects varied with the mean slope, subpixel aspect distribution, SZA and SAA, which should not be neglected when modeling albedo.

In situ albedo measurement over sloped surfaces is pivotal to a wide range of remote sensing applications, such as the estimation and evaluation of surface energy budget at regional and global scales. However, existing albedo measurements over rugged terrain are limited and controversial and remain a major challenge. In this paper, two commonly measured broadband albedos, which depend on incoming/outgoing geometric conditions, were characterized over sloped surfaces and illustrated. These albedos are the horizontal/horizontal sloped surface albedo (HHSA) and inclined/inclined sloped surface albedo (IISA). 3‐D Discrete Anisotropic Radiative Transfer (DART) model simulations over varying slopes were utilized to quantify differences in the albedos. In particular, the effects of the slope, aspect, the solar zenith angle (SZA) and the proportion of diffuse skylight were investigated. The results show that absolute (relative) biases between HHSA and IISA are significant, reaching up to 0.026 (61.8%), 0.134 (62.4%), and 0.114 (62.3%) in the visible (VIS), near‐infrared (NIR), and shortwave (SW) broadbands, respectively. In addition, the diurnal cycle differences between HHSA and IISA were also compared using DART simulations and in situ observations over four typical slopes. Comparisons reveal that topographic parameters (e.g., slope and aspect) and atmospheric conditions (e.g., diffuse skylight and atmospheric visibility) are the primary factors, while the optical and structural parameters have a relatively smaller effect.

A rigorous and reliable validation is the prerequisite and basis to properly understand the accuracy of satellite surface albedo products. However, the representativeness error of point‐scale in situ measurements, which mainly results from the spatial mismatch between in situ and satellite measurements as well as the surface heterogeneities, generally hinders an effective validation of satellite surface albedo products based on the conventional direct comparison method. Triple collocation (TC) technique has been recognized as a powerful tool to estimate the errors of satellite products without requiring the truth. Here, we evaluated the effectiveness of both the direct comparison and extended triple collocation (ETC) methods in tackling with the representativeness error of in situ measurements and characterizing the performances of satellite surface albedo products (MCD43A3 (V006), GLASS and NPP VIIRS albedos) given whether the in situ‐based pixel‐scale albedo was available or not. The ETC method is shown to be advantageous over the direct comparison based on single “point” in situ measurements, because it is less affected by representativeness errors. However, it shall not substitute for the direct comparison method based on in situ‐based pixel‐scale albedo measurements, because its effectiveness in solving representativeness errors and estimating product errors is very limited and dependent on the choice of the data in the triplets. Furthermore, the ETC technique cannot be used to estimate the true physical errors of satellite surface albedo products.