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Investigation of Sentinel-2 Bidirectional Reflectance Hot-Spot Sensing Conditions
摘要： Directional reflectance effects, often described by the bidirectional reflectance distribution function (BRDF), occur in Sentinel-2 multispectral instrument reflectance. The bidirectional hot-spot is a special case of the BRDF used to describe the increased backscatter reflectance that occurs over most surfaces when the solar and viewing directions coincide. A global year of Sentinel-2A metadata extracted using the Committee on Earth Observation Satellite Visualization Environment (COVE) tool and an established astronomical model were used to quantify the range of solar geometry and scattering angles expected in Sentinel-2A data. The established astronomical model was adapted to be Sentinel-2A specific and was parameterized as a function of the sensor acquisition date and nadir latitude. Solar zenith angles varied from 15.335° to 91.454°, and the scattering angles varied from 84.714° to 173.967°. To confirm the global COVE results, the scattering angles of a sample of Sentinel-2A data were examined and differed by less than 0.17° with respect to the COVE data. Given that hot-spots are only apparent when the scattering angle is close to 180°, we conclude that hot-spot will not occur in Sentinel-2A data. Equations and software to predict the scattering angle at the Sentinel-2A swath edge as a function of acquisition date and nadir latitude are provided so users may obtain data over a range of scattering angles in support of their BRDF studies.
关键词： bidirectional reflectance distribution function (BRDF),Bidirectional hot-spot,scattering angle,solar geometry,Sentinel-2
更新于2025-09-23 15:23:52
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Development of a snow kernel to better model the anisotropic reflectance of pure snow in a kernel-driven BRDF model framework
摘要： The linear kernel-driven RossThick-LiSparseReciprocal (RTLSR) bidirectional reflectance distribution function (BRDF) model was originally developed from the simplified scenarios of continuous and discrete vegetation canopies, and has been widely used to fit multiangle observations of vegetation-soil systems of the land surface in many fields. Although this model was not developed explicitly for snow surfaces, it can capture the geometric-optical effect caused by the shadowing of rugged or undulating snow surfaces. However, in this study, this model has been further developed to better characterize the scattering properties of snow surface, which can also exhibit strongly forward-scattering behavior. This study proposes a new snow kernel to characterize the reflectance anisotropy of pure snow based on the asymptotic radiative transfer (ART) model that assumes snow can be modeled as a semi-infinite, plane-parallel, weakly absorbing light scattering layer. This new snow kernel adopts a correction term with a free parameter α to correct the analytic form of the ART model that has been reported to underestimate observed snow reflectance in the forward-scattering direction in the principal plane (PP), particularly in cases of a large viewing zenith angle (> 60°). This snow kernel has now been implemented in the kernel-driven RTLSR BRDF model framework in conjunction with two additional kernels (i.e., the volumetric scattering kernel and geometric-optical scattering kernel) and is validated using observed and simulated multiangle data from three data sources. Pure snow targets were selected from the extensive archive of the Polarization and Directionality of the Earth's Reflectance (POLDER) BRDF data. Antarctic snow field measurements, which were taken from the top of a 32-m-tall tower at Dome C Station and include 6336 spectral bidirectional reflectance factors (BRFs), were also utilized. Finally, a set of simulated BRFs, generated by a hybrid scattering snow model that combines the geometric optics with vector radiative transfer theory, were used to further assess the proposed method. We first retrieve the value of the free parameter α for a comprehensive analysis using single multiangle snow data with a sufficient BRDF sampling. Then, we determine the optimally fixed value of the α parameter as prior information for potential users. The new snow kernel method is shown to be quite accurate, presenting a high correlation coefficient (R2 = ~0.9) and a negligible bias between the modeled BRFs and the various snow BRDF validation data. The finding demonstrates that this snow kernel provides an improved potential compared to that of the original kernel-driven model framework for a pure snow surface in many applications, particularly those involving the global water cycle and radiation budget, where snow cover plays an important role.
关键词： Kernel-driven model,POLDER BRDF data,Bidirectional reflectance distribution function (BRDF),Asymptotic radiative transfer (ART) model,Snow,Forward scattering,RTLSR model
更新于2025-09-09 09:28:46
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Improved Vegetation Profiles with GOCI Imagery Using Optimized BRDF Composite
摘要： The purpose of this study was to optimize a composite method for the Geostationary Ocean Color Imager (GOCI), which is the first geostationary ocean color sensor in the world. Before interpreting the sensitivity of each composite with ground measurements, we evaluated the accuracy of bidirectional reflectance distribution function (BRDF) performance by comparing modeled surface reflectance from BRDF simulation with GOCI-measured surface reflectance according to composite period. The root mean square error values for modeled and measured surface reflectance showed reasonable accuracy for all of composite days since each BRDF composite period includes at least seven cloud-free angular sampling for all BRDF performances. Also, GOCI-BRDF-adjusted NDVIs with four different composite periods were compared with field-observation NDVI and we interpreted the sensitivity of temporal crop dynamics of GOCI-BRDF-adjusted NDVIs. The results showed that vegetation index seasonal profiles appeared similar to vegetation growth curves in both field observations from crop scans and GOCI normalized difference vegetation index (NDVI) data. Finally, we showed that a 12-day composite period was optimal in terms of BRDF simulation accuracy, surface coverage, and real-time sensitivity.
关键词： bidirectional reflectance distribution function (BRDF),vegetation profiles,Geostationary Ocean Color Imager (GOCI),composite period,normalized difference vegetation index (NDVI)
更新于2025-09-04 15:30:14