Bidirectional Reflectance Distribution Function Characteristics Research Articles

BRDF Data for Coniferous Forests Acquired from Multispectral Camera Onboard a Unmanned Aerial Vehicle

Bidirectional reflectance distribution function (BRDF) is a distribution of directional reflectance for varying viewing and solar geometry. BRDF of a target is important in processing optical image data from satellites, because the observed radiance has great dependency on the direction (or angle) of reflection. It is desirable that the BRDF of any targets is characterized for rigorous BRDF correction of satellite data, since the sun-sensor-target geometry of satellites often varies in a very limited range, limiting the full characterization of target BRDF. This study provides BRDF data set for typical coniferous forests in Korea, by using a multispectral camera onboard a unmanned aerial vehicle (UAV). By operating the UAV in a goniometer-like way, reflectance data for all possible viewing zenith and azimuth angles were obtained. The BRDF data collected from the 3 campaigns in different days were visualized in a polar-coordinate, together with the standard deviation calculated for each zenith/azimuth bin made in 1˚ interval. The data sets demonstrated reflectance distribution over the wide range of angles with sound data quality, suggesting commonly known BRDF characteristics for forests such as strong back-scattering and hot spot area in the viewing zenith angle near the solar zenith angle. This data set is expected to be utilized for the BRDF correction of various satellites including Agro-forest satellite of Korea which is to be launched in 2025 that has similar spectral bands with the ones used in this study.

A Kalman-filtering-based BRDF online measurement method for variable temperature surfaces

Bidirectional Reflectance Distribution Function (BRDF) at variable temperature is important in many applications such as thermal imaging and target detection. However, ensuring long-term stable high temperature control is complex and energy consuming, making online measurements essential. Existing BRDF systems are mainly designed for room temperature measurements, and the widely used quadrature demodulator requires a large amount of stored measurement data and complicate post-processing calculations. In this paper, the Kalman-based demodulator was modified by adding a forgetting factor to improve the demodulation speed and flexibility. This demodulator was implemented on FPGA in both numerical simulations and experiments. The detection of BRDF was demodulated online, reducing measurement time and resource consumption by half compared to the quadrature demodulator. The proposed demodulator can be utilized for further analysis of high-temperature BRDF characteristics of material surfaces.

BRDF characteristics of different textured fabrics in visible and near-infrared band.

The directional reflection characteristics of fabrics with various texture structures is an important and challenging topic in computer graphics and visual simulation. In the present study, the Bidirectional Reflectance Distribution Function (BRDF) of four different textured fabrics is measured via a self-designed Scatterometry to analyze the effect of surface textures and illuminated wavelengths. Furthermore, a fast and simple BRDF model is provided, and optimal model parameters for fabric BRDF calculation were obtained via a genetic algorithm. The results indicate that the reflected distribution of fabrics is dominated by diffuse reflection and is modulated by surface textures and irradiated wavelengths.

Assessment of bidirectional reflectance effects on desert and forest for radiometric cross-calibration of satellite sensors

Cross-calibration is a wildly used approach to radiometrically calibrate satellite sensors to meet uncertainty requirements. However, its accuracy is greatly influenced by bidirectional reflectance distribution function (BRDF) effects. To understand such influences, we analyzed the long-term BRDF characteristics of two commonly used cross-calibration targets (‘bright’ desert and ‘dark’ forest) using long-term (2002 – 2016) Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF products. BRDF characteristics derived by MODIS observations of both land cover types had 365-day cycles. Furthermore, both solar and sensor zenith angles showed more influence on BRDF than relative azimuth angles, and BRDF variations were approximately 10 times sensitive when solar or sensor zenith angles surpassed the boundary of 75°, which is therefore not recommended for selecting image pairs between target and reference satellite sensors for cross-calibration. Due to cloud cover, three prevailing interpolation methods (nearest, linear, and spline interpolation) were also assessed in their capacity to fill temporally missing BRDF products. Linear interpolation was preferred when valid MODIS scenes were more than two in five days, while nearest interpolation outperformed the other two methods for no more than two valid MODIS scenes in five days. In addition, BRDF look up tables (LUTs) were established for radiometrically cross-calibrating satellite sensors when BRDF products were unavailable. The LUTs were further validated with Landsat-8/Operational Land Imager (OLI) top of atmosphere (TOA) radiance simulated by the Second Simulation of the Satellite Signal in the Solar Spectrum model (6S) with BRDF effects corrected using the BRDF LUTs and MODIS BRDF products for typical geometries at two sites. High consistency was achieved with mean biases less than 0.3%, which suggests that BRDF LUTs could be used as alternatives when BRDF products are unavailable. These results provide guidelines to improve the accuracy of cross-calibration including image-matchup selecting criteria, efficient BRDF effect removal, and selection of potential calibration sites.

The additional thermal effect of main tube with BRDF surface in space solar telescope

The absorbance, scattering and reflectance characteristics of main tube (MT) surface are critical elements in thermal scheme and scattering suppression of large aperture & small field of view (LASFOV) solar telescopes. With application of Space Solar Telescope (SST), surface of MT with bidirectional reflectance distribution function (BRDF) characteristics can cause additional thermal effect on the primary mirror (PM), field stop (FS) and MT, based on SST scattering elimination scheme. Considering space environment with solar radiation and heat conduction, micro-facets are added on MT to represent its BRDF characteristics, and the homeostatic thermal models of MT are developed with micro-facets to investigate their additional thermal effect. In practical, six series of MT with different micro-facets (height Hc and Hb, distance Dc and Db, angle δ and θ) are developed to estimate the temperature distribution of SST with thermal analysis software. Thermal analysis shows six parameters representing BRDF characteristics have obvious additional thermal effect on temperature distribution of PM, FS and MT. Therefore, thermal-scattering (TS) integrated design of MT surface with BRDF characteristics is practical and worthy for critical surfaces to obtain ideal TS performance. It is a guidance to optimize critical surfaces in LASFOV solar telescopes to minimizing theirs thermal characteristics and scattering characteristics.

Seasonal change of bidirectional reflectance distribution function in mature Japanese larch forests and their phenology at the foot of Mt. Yatsugatake, central Japan

We constructed a bi-directional reflectance distribution function (BRDF) observation system on a 25-m-high tower surrounded by mature larch forests at the foot of Mt. Yatsugatake, central Japan. The BRDF feature (strong/weak reflections in a backward/forward scattering areas) is related closely to the 3D structure and biophysical parameters of forests. However, because of the difficulty of observations, observational BRDF data of mature forests are scarce, except for those of Boreal Ecosystem –Atmosphere Study (BOREAS). We made BRDF observations 10 times during 2007 to ascertain BRDF characteristics in each season. For comparison to these BRDF data, a semi-empirical BRDF model (Ross–thick Li–sparse kernel model) was introduced. This model can reproduce the BRDF data fairly well under identical solar conditions in each season. Then, seasonal changes of the vegetation structure and possible relations with BRDF were discussed. They are summarized as follows: (1) The forest BRDF changes distinctly and seasonally depending on the phenology. (2) The forest BRDF is influenced primarily by clarity of the geometrical profile on the forest surface, which is affected by shadow. However, the forest BRDF might be influenced by other factors such as the physiological characteristics of leaves and slight change of vegetation structure such as forest floor conditions and leaf angles during summer. (3) Features of forest BRDF must therefore appear during summer when the crown shape is distinctive. Furthermore, BRDF features appear distinctly as seasons progress, e.g., by autumn leaves and defoliation, when the unevenness of forests increases. These findings can promote monitoring of vegetation using multi-angular satellite observations.

Influence of the canopy BRDF characteristics and illumination conditions on the retrieval of solar-induced chlorophyll fluorescence

ABSTRACTThe Fraunhofer line discrimination (FLD) principle is the main approach used for the retrieval of solar-induced chlorophyll fluorescence (SIF). The basic assumption of the FLD principle is that the apparent reflectance spectra without SIF in-filling are smooth in the region of the absorption bands. However, in fact, this assumption is not valid due to the so-called ‘direct radiation in-filling’ effect caused by the nonlinear contribution of direct and diffuse radiation at the oxygen absorption bands, which are widely used for ground-based SIF retrieval. In this study, we first analysed the physical mechanism of the direct radiation in-filling effect on the oxygen absorption bands and found that the bias in the SIF retrieval caused by the direct radiation in-filling effect at the oxygen-A (O2-A) band was less than 20% based on the use of a simulated data set. Second, we established a simple correction model of the direct radiation in-filling effect. We found that the direct radiation in-filling effect at the O2-A band was directly proportional to the difference between the reflectance of the direct and diffuse radiation, and that the coefficient of proportionality was well correlated with the diffuse-to-global radiation ratio in the form of a quadratic function, with a coefficient of determination (R2) of 0.97. Finally, the model was validated using both simulated and field data sets. The validation results show that the bias in the SIF retrieval caused by the direct radiation in-filling effect can be efficiently corrected using the model proposed in this article. This study thus provides a possible approach to estimating and correcting for the direct radiation-infilling effect using prior knowledge of the bidirectional reflectance distribution function characteristics of direct and diffuse radiation for specific targets.

Estimation of crop gross primary production (GPP): I. impact of MODIS observation footprint and impact of vegetation BRDF characteristics

Accurate estimation of gross primary production (GPP) is essential for carbon cycle and climate change studies. Three AmeriFlux crop sites of maize and soybean were selected for this study. Two of the sites were irrigated and the other one was rainfed. The normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the green band chlorophyll index (CIgreen), and the green band wide dynamic range vegetation index (WDRVIgreen) were computed from the moderate resolution imaging spectroradiometer (MODIS) surface reflectance data. We examined the impacts of the MODIS observation footprint and the vegetation bidirectional reflectance distribution function (BRDF) on crop daily GPP estimation with the four spectral vegetation indices (VIs - NDVI, EVI, WDRVIgreen and CIgreen) where GPP was predicted with two linear models, with and without offset: GPP=a×VI×PAR and GPP=a×VI×PAR+b. Model performance was evaluated with coefficient of determination (R2), root mean square error (RMSE), and coefficient of variation (CV). The MODIS data were filtered into four categories and four experiments were conducted to assess the impacts. The first experiment included all observations. The second experiment only included observations with view zenith angle (VZA)≤35° to constrain growth of the footprint size,which achieved a better grid cell match with the agricultural fields. The third experiment included only forward scatter observations with VZA≤35°. The fourth experiment included only backscatter observations with VZA≤35°. Overall, the EVI yielded the most consistently strong relationships to daily GPP under all examined conditions. The model GPP=a×VI×PAR+b had better performance than the model GPP=a×VI×PAR, and the offset was significant for most cases. Better performance was obtained for the irrigated field than its counterpart rainfed field. Comparison of experiment 2 vs. experiment 1 was used to examine the observation footprint impact whereas comparison of experiment 4 vs. experiment 3 was used to examine the BRDF impact. Changes in R2, RMSE,CV and changes in model coefficients “a” and “b” (experiment 2 vs. experiment 1; and experiment 4 vs. experiment 3) were indicators of the impacts. The second experiment produced better performance than the first experiment, increasing R2 (↑0.13) and reducing RMSE (↓0.68gCm−2d−1) and CV (↓9%). For each VI, the slope of GPP=a×VI×PAR in the second experiment for each crop type changed little while the slope and intercept of GPP=a×VI×PAR+b varied field by field. The CIgreen was least affected by the MODIS observation footprint in estimating crop daily GPP (R2, ↑0.08; RMSE, ↓0.42gCm−2d−1; and CV, ↓7%). Footprint most affected the NDVI (R2, ↑0.15; CV, ↓10%) and the EVI (RMSE, ↓0.84gCm−2d−1). The vegetation BRDF impact also caused variation of model performance and change of model coefficients. Significantly different slopes were obtained for forward vs. backscatter observations, especially for the CIgreen and the NDVI. Both the footprint impact and the BRDF impact varied with crop types, irrigation options, model options and VI options.

A synergic algorithm for retrieval of aerosol optical depth over land

In this paper, a novel algorithm for aerosol optical depth(AOD) retrieval with a 1 km spatial resolution over land is presented using the Advanced Along Track Scanning Radiometer (AATSR) dual-view capability at 0.55, 0.66 and 0.87 µm, in combination with the Bi-directional Reflectance Distribution Function (BRDF) model, a product of the Moderate Resolution Imaging Spectroradiometer (MODIS). The BRDF characteristics of the land surface, i.e. prior input parameters for this algorithm, are computed by extracting the geometrical information from AATSR and reducing the kernels from the MODIS BRDF/Albedo Model Parameters Product. Finally, AOD, with a 1 km resolution at 0.55, 0.66 and 0.87 µm for the forward and nadir views of AATSR, can be simultaneously obtained.

Atmospheric Corrections Using MODTRAN for TOA and Surface BRDF Characteristics from High Resolution Spectroradiometric/Angular Measurements from a Helicopter Platform

High-resolution spectral radiance measurements were taken by a spectral radiometer on board a helicopter over the US Oklahoma Southern Great Plain near the Atmospheric Radiation Measurements (ARM) site during August 1998. The radiometer has a spectral range from 350 nm to 2500 nm at 1 nm resolution. The measurements covered several grass and cropland scene types at multiple solar zenith angles. Detailed atmospheric corrections using the Moderate Resolution Transmittance (MODTRAN) radiation model and in-situ sounding and aerosol measurements have been applied to the helicopter measurements in order to retrieve the surface and top of atmosphere (TOA) Bidirectional Reflectance Distribution Function (BRDF) characteristics. The atmospheric corrections are most significant in the visible wavelengths and in the strong water vapor absorption wavelengths in the near infrared region. Adjusting the BRDF to TOA requires a larger correction in the visible channels since Rayleigh scattering contributes significantly to the TOA reflectance. The opposite corrections to the visible and near infrarred wavelengths can alter the radiance difference and ratio that many remote sensing techniques are based on, such as the normalized difference vegetation index (NOVI). The data show that surface BRDFs and spectral albedos are highly sensitive to the vegetation type and sol:!r zenith angle while BRDF at TOA depends more on atmospheric conditions and the viewing geometry. Comparison with the Clouds and the Earth’s Radiant Energy System (CERES) derived clear sky Angular Distribution Model (ADM) for crop and grass scene type shows a standard deviation of O.08 in broadband anisotropic function at 25° solar zenith angle and O.15 at 50° solar zenith angle, respectively.

Sensitivity Analysis and Quality Assessment of Laboratory BRDF Data

A detailed quality and sensitivity analysis of hyper-spectral BRDF data, acquired under controlled laboratory conditions at the European Goniometric Facility (EGO) of the Joint Research Center, Ispra/Italy, has been performed. In regard to bidirectional reflectance measurements in the field with the FIGOS goniometer, the impact of angular data sampling, the movement of the Sun, and the Lambertian assumption of a Spectralon panel have been analyzed. An erectophile grass lawn canopy and a planophile watercress surface were chosen as main targets. A GER-3700 spectroradiometer providing hyperspectral resolution allowed for analyzing the wavelength dependency of the effects. The results of the sensitivity analysis show that in a first step a moderate resolution of 15° and 30° in zenith and azimuth, respectively, is adequate to capture the bidirectional reflectance distribution function (BRDF) of vegetated targets. Only in the hot spot area a higher resolution is desirable. The movement of the light source during data acquisition is found to be critical, and should be kept within ±1° source zenith angle in order to obtain homologous BRDF data sets. Due to the wavelength dependence of BRDF effects, the impact of the light source may vary significantly between different wavelength ranges. A normalization of the irradiance with the help of frequent reference measurements is recommended, and should be carried out using a panel with known BRDF characteristics. The Spectralon panel examined showed deviations from a Lamber-tian panel of up to 5% and more, but obeyed Helmholtz’s reciprocity law. Corresponding calibration coefficients are given for correcting the non-Lambertian behavior in field applications. Laboratory specific constraints such as the nonparallelism and heterogeneity of the lamp are assessed and corrected where necessary and feasible. The reproducibility of the BRDF data obtained lies within 1–9% rmse, depending on target type, wavelength range, and measurement duration.

Empirical methods to compensate for a view-angle-dependent brightness gradient in AVIRIS imagery

A view-angle-dependent brightness gradient was observed in an AVIRIS image of a forested region in Oregon's Cascade Mountains. A method of removing the view-angle effect was sought that would not alter the radiometric integrity of the image, and which would require minimal ancillary information. Four methods were tested and evaluated in terms of remaining brightness gradient and in terms of retention of spectral characteristics. All methods used a quadratic fitting equation to model the changes in brightness across view angles. Other descriptive coefficients were calculated to aid in interpretation. The observed view-angle effect varied with wavelength in a manner consistent with predictions of bidirectional reflectance distribution function characteristics for vegetation. View-angle effects were determined to contain both additive and multiplicative components, with multiplicative components being strong in the chlorophyll absorption region. The view-angle effect in a given pixel was a function of both an underlying viewangle response determined by surface structure and the inherent brightness of that pixel. The most successful compensation method was the one that best accounted for broad differences between pixels in these two components. Despite the simplifying assumptions necessary for empirical view-atigle correction techniques, they can still be useful for hyperspectral remote-sensing data in situations where the view-angle brightness variations would mask variance useful for extracting scene information.