Yadong Dong

Evaluation of BRDF Archetypes for Representing Surface Reflectance Anisotropy Using MODIS BRDF Data

Bidirectional reflectance distribution function (BRDF) archetypes extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo product over the global Earth Observing System Land Validation Core Sites can be used to simplify BRDF models. The present study attempts to evaluate the representativeness of BRDF archetypes for surface reflectance anisotropy. Five-year forward-modeled MODIS multi-angular reflectance (MCD-ref) and aditional actual MODIS multi-angular observations (MCD-obs) in four growing periods in 2008 over three tiles were taken as validation data. First, BRDF archetypes in the principal plane were qualitatively compared with the time-series MODIS BRDF product of randomly sampled pixels. Secondly, BRDF archetypes were used to fit MCD-ref, and the average root-mean-squared errors (RMSEs) over each tile were examined for these five years. Finally, both BRDF archetypes and the MODIS BRDF were used to fit MCD-obs, and the histograms of the fit-RMSEs were compared. The consistency of the directional reflectance between the BRDF archetypes and MODIS BRDFs in nadir-view, hotspot and entire viewing hemisphere at 30° and 50° solar geometries were also examined. The results confirm that BRDF archetypes are representative of surface reflectance anisotropy for available snow-free MODIS data.

An Algorithm for Retrieval of Surface Albedo From Small View-Angle Airborne Observations Through the Use of BRDF Archetypes as Prior Knowledge

Land surface albedo, qualifying the ratio of the radiant flux reflected from the land surface to the incident flux, is a key forcing parameter controlling the Earths energy budget. Previously, several BRDF archetypes were distilled from high-quality MODIS BRDF/Albedo products. In this study, we propose a method that largely relies on matching observed multiangular reflectances with the most appropriate of these prior BRDF archetypes to determine the amplitude and shape of the actual surface BRDFs, when directional signatures are insufficient. This method is first evaluated using an assortment of multisource BRDF data sets to demonstrate its viability for surface albedo estimates, and then is applied to airborne wide-angle infrared dual-mode line/area array scanner (WIDAS) from the Watershed Allied Telemetry Experimental Research (WATER) campaign in the Heihe River Basin of China in 2008. This algorithm makes use of the linear MODIS BRDF model to determine the BRDF archetypes needed as prior knowledge for intrinsic spectral albedo estimates. The intrinsic spectral albedos are then used to estimate actual spectral albedos by considering the proportion of direct and diffuse solar radiation. A spectral-to-broadband conversion is performed to generate the broadband albedo at shortwave regimes through the use of conversion coefficients derived from extensive radiative transfer simulations. A further validation confirms that the estimated albedos are consistent with in situ field measured albedos over available corn crop sites. This method provides a major advantage on utilizing generalized BRDF information derived from MODIS in conjunction with other instrument data that are acquired with less angular variation.

Analysis of Extracting Prior BRDF from MODIS BRDF Data

Many previous studies have attempted to extract prior reflectance anisotropy knowledge from the historical MODIS Bidirectional Reflectance Distribution Function (BRDF) product based on land cover or Normalized Difference Vegetation Index (NDVI) data. In this study, the feasibility of the method is discussed based on MODIS data and archetypal BRDFs. The BRDF is simplified into six archetypal BRDFs that represent different reflectance anisotropies. Five-year time series of MODIS BRDF data over three tiles are classified into six BRDF archetype classes according to the Anisotropy Flat indeX (AFX). The percentage of each BRDF archetype class in different land cover classes or every 0.1-NDVI interval is determined. Nadir BRDF-Adjusted Reflectances (NBARs) and NDVIs simulated from different archetypal BRDFs and the same multi-angular observations are compared to MODIS results to study the effectiveness of the method. The results show that one land cover type, or every 0.1-NDVI interval, contains all the potential BRDF shapes and that one BRDF archetypal class makes up no more than 40% of all data. Moreover, the differences between the NBARs and NDVIs simulated from different archetypal BRDFs are insignificant. In terms of the archetypal BRDF method and MODIS BRDF product, this study indicates that the land cover or NDVI is not necessarily related to surface reflectance anisotropy.

A visualization tool for the kernel-driven model with improved ability in data analysis and kernel assessment

Abstract The semi-empirical, kernel-driven Bidirectional Reflectance Distribution Function (BRDF) model has been widely used for many aspects of remote sensing. With the development of the kernel-driven model, there is a need to further assess the performance of newly developed kernels. The use of visualization tools can facilitate the analysis of model results and the assessment of newly developed kernels. However, the current version of the kernel-driven model does not contain a visualization function. In this study, a user-friendly visualization tool, named MaKeMAT, was developed specifically for the kernel-driven model. The POLDER-3 and CAR BRDF datasets were used to demonstrate the applicability of MaKeMAT. The visualization of inputted multi-angle measurements enhances understanding of multi-angle measurements and allows the choice of measurements with good representativeness. The visualization of modeling results facilitates the assessment of newly developed kernels. The study shows that the visualization tool MaKeMAT can promote the widespread application of the kernel-driven model.

Potential Investigation of Linking PROSAIL with the Ross-Li BRDF Model for Vegetation Characterization

Methods that link different models for investigating the retrieval of canopy biophysical/structural variables have been substantially adopted in the remote sensing community. To retrieve global biophysical parameters from multiangle data, the kernel-driven bidirectional reflectance distribution function (BRDF) model has been widely applied to satellite multiangle observations to model (interpolate/extrapolate) the bidirectional reflectance factor (BRF) in an arbitrary direction of viewing and solar geometries. Such modeled BRFs, as an essential information source, are then input into an inversion procedure that is devised through a large number of simulation analyses from some widely used physical models that can generalize such an inversion relationship between the BRFs (or their simple algebraic composite) and the biophysical/structural parameter. Therefore, evaluation of such a link between physical models and kernel-driven models contributes to the development of such inversion procedures to accurately retrieve vegetation properties, particularly based on the operational global BRDF parameters derived from satellite multiangle observations (e.g., MODIS). In this study, the main objective is to investigate the potential for linking a popular physical model (PROSAIL) with the widely used kernel-driven Ross-Li models. To do this, the BRFs and albedo are generated by the physical PROSAIL in a forward model, and then the simulated BRFs are input into the kernel-driven BRDF model for retrieval of the BRFs and albedo in the same viewing and solar geometries. To further strengthen such an investigation, a variety of field-measured multiangle reflectances have also been used to investigate the potential for linking these two models. For simulated BRFs generated by the PROSAIL model at 659 and 865 nm, the two models are generally comparable to each other, and the resultant root mean square errors (RMSEs) are 0.0092 and 0.0355, respectively, although some discrepancy in the simulated BRFs can be found at large average leaf angle (ALA) values. Unsurprisingly, albedos generated by the method are quite consistent, and 99.98% and 97.99% of the simulated white sky albedo (WSA) has a divergence less than 0.02. For the field measurements, the kernel-driven model presents somewhat better model-observation congruence than the PROSAIL model. The results show that these models have an overall good consistency for both field-measured and model-simulated BRFs. Therefore, there is potential for linking these two models for looking into the retrieval of canopy biophysical/structural variables through a simulation method, particularly from the current archive of the global routine MODIS BRDF parameters that were produced by the kernel-driven BRDF model; however, erectophile vegetation must be further examined.

An approach to improve hot spot effect for the MODIS BRDF/Albedo algorithm

The RossThick-LiSparse-Reciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model has been developped to derive the operational Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo product due to its simplicity and the underlying physics; however, early research showed that this model deficiency mainly comes from its underestimation of the hotspot directional signatures near the Suns illumination direction. In this paper, we developed an approach to improve the hot spot effect for the RTLSR model by improving the volumetric scattering kernel with an exponential approximation of the hot spot kernel (Chen and Cihlar, 1997). Compared with the RTLSR model and the further-developed model that modify the hotspot directional signatures of RTLSR model based on the calculation of an overlay function of the intersection of viewed and sunlit leaf areas (Jupp and Strahler, 1991, thereafter named RTJLSR), this newly-corrected model that modifies the hot spot effect of RTLSR model based on the theory of calculation of a canopy gap size distribution function (Chen and Leblanc, 1997, thereafter named RTCLSR) preserves the linear form of kernel-driven model, but flexibly adjust hotspot magnitude and width through two additional parameters C1 and C2. Initial validation result with airborne cloud absorption radiometer (CAR) data shows that the RTCLSR model can significantly improve the model-observation fits in hotspot region. In near future, we will focus on determining C1/C2 values from spaceborne POLDER BRDF database provided by the POSTEL Service Centre. With C1/C2 are predetermined, the newly-correctly RTCLSR model is promissing for global application with a minor update from the RTLSR model.

To derive BRDF archetypes from POLDER-3 BRDF database

In this study, based on kernel-driven linear BRDF model, a new spectral vegetation index named anisotropic flat index (AFX) and a hotspot kernel function are described. Anisotropic Flat Index (AFX), which is created by normalization of net scattering magnitude with the isotropic scattering, can summarize the variability of basic dome-bowl anisotropic reflectance pattern of the terrestrial surface. The hotspot kernel function is modified with the exponential approximation to generate a so-called RossThickChen kernel (KRTC). Using the POLDER-3 multi-angular observations, a classification scheme for BRDF typology is created and a BRDF archetype data is established. The results show that the AFX effectively summarizes BRDF archetypes that provide additional information on vegetation structures and other anisotropic reflectance characteristics of the land surface. The RTCLSR model can significantly capture the hotspot signatures, the BRDF archetypes derived in this way provides a significantly different hotspot signatures from those derived from the MODIS BRDF product.

Quantifying the Reflectance Anisotropy Effect on Albedo Retrieval from Remotely Sensed Observations Using Archetypal BRDFs

The reflectance anisotropy effect on albedo retrieval was evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution functions (BRDFs) product, and archetypal BRDFs. Shortwave-band archetypal BRDFs were established, and validated, based on the Anisotropy Flat indeX (AFX) and time series MODIS BRDF over tile h11v03. To generate surface albedo, archetypal BRDFs were used to fit simulated reflectance, based on the least squares method. Albedo was also retrieved based on the least root-mean-square-error (RMSE) method or normalized difference vegetation index (NDVI) based prior BRDF knowledge. The difference between those albedos and the MODIS albedo was used to quantify the reflectance anisotropy effect. The albedo over tile h11v03 for day 185 in 2009 was retrieved from single directional reflectance and the third archetypal BRDF. The results show that six archetypal BRDFs are sufficient to represent the reflectance anisotropy for albedo estimation. For the data used in this study, the relative uncertainty caused by reflectance anisotropy can reach up to 7.4%, 16.2%, and 20.2% for sufficient, insufficient multi-angular and single directional observations. The intermediate archetypal BRDFs may be used to improve the albedo retrieval accuracy from insufficient or single observations with a relative uncertainty range of 8–15%.

Analysis of anisotropy variance between the kernel-driven model and the PROSAIL model

The surface anisotropy characteristics have important significance in the quantitative remote sensing inversion. The kernel-driven model can express the surface anisotropy well and widely used in remote sensing, and the PROSAIL model is a mature vegetation canopy model which can describe complex vegetation structure, therefore studying surface anisotropy variance of the two models is a key point to combine them for further research. We simulate surface reflectance data with complex vegetation structure through the PROSAIL model, with the RossThick-LiSparseR(RTLSR) model and its extended model of Chen(RTCLSR) considering hotspot effect, we analyze anisotropy variance. The result shows: (1) The overall fitting effect is good, the average fitting RMSE is about 0.0071 in red band and 0.0342 in near infrared band; (2) AFX is sensitive to some vegetation structure parameters; (3) C1 and C2 in Chen model is inversely proportional to each other in different Hspot, while proportional in different LAI.

A method for kernel-driven model to correct the blended hemispherical diffuse irradiance in multi-angle measurements

Semi-empirical kernel-driven Bidirectional Reflectance Distribution Function (BRDF) model has been developed to retrieve the BRDF shapes of the observed surface from multi-angle measurements. At present, hemispherical diffuse irradiance is usually blended in the multi-angle measurements. The blend of diffuse irradiance will smooth the intrinsic BRDF shapes of observed surface. Therefore, there is a need to correct the diffuse irradiance to get the ideal BRDF shapes when the multi-angle measurements is processed by the kernel-driven model. In this article, we develop a method for kernel-driven model to correct the blended hemispherical diffuse irradiance in the multi-angle measurements. Multi-angle data simulated by the PROSAIL model are used to validate the efficiency of the method. The result indicates that the simulated reflectance after correction agree well with the measurements without diffuse irradiance.