Hemispherical Directional Reflectance Factor Research Articles

Reflection of Solar Light from Surface Snow Loaded with Light-Absorbing Impurities: A Case Study of Black Carbon, Mineral Dust, and Ash.

Using a hemispherical directional reflectance factor instrument, spectral data of dirty snow containing black carbon (BC), mineral dust (MD), and ash was collected from multiple locations to investigate the impact of these light-absorbing impurities (LAIs) on snow reflectance characteristics. The findings revealed that the perturbation of snow reflectance caused by LAIs is characterized by nonlinear deceleration, indicating that the reduction in snow reflectance per unit ppm of LAIs declines as snow contamination increases. The reduction in snow reflectance caused by BC may reach saturation at elevated particle concentrations (thousands of ppm) on snow. Snowpacks loaded with MD or ash initially exhibit a significant reduction in spectral slope around 600 and 700 nm. The deposition of numerous MD or ash particles can increase snow reflectance beyond the wavelength of 1400 nm, with an increase of 0.1 for MD and 0.2 for ash. BC can darken the entire measurement range (350-2500 nm), while MD and ash can only affect up to 1200 nm (350-1200 nm). This study enhances our understanding of the multi-angle reflection characteristics of various dirty snow, which can guide future snow albedo simulations and improve the accuracy of LAIs' remote sensing retrieval algorithms.

Airborne measurements of directional reflectivity over the Arctic marginal sea ice zone

Abstract. The directional reflection of solar radiation by the Arctic Ocean is mainly shaped by two dominating surface types: sea ice (often snow-covered) and open ocean (ice-free). In the transitional zone between them, the marginal sea ice zone (MIZ), the surface reflection properties are determined by a mixture of the reflectance of both surface types. Retrieval methods applied over the MIZ need to take into account the mixed directional reflectivity; otherwise uncertainties in the retrieved atmospheric parameters over the MIZ may occur. To quantify these uncertainties, respective measurements of reflection properties of the MIZ are needed. Therefore, in this case study, an averaged hemispherical–directional reflectance factor (HDRF) of the inhomogeneous surface (mixture of sea ice and open ocean) in the MIZ is derived using airborne measurements collected with a digital fish-eye camera during a 20 min low-level flight leg in cloud-free conditions. For this purpose, a sea ice mask was developed to separate the reflectivity measurements from sea ice and open ocean and to derive separate HDRFs of the individual surface types. The respective results were compared with simulations and independent measurements available from the literature. It is shown that the open-ocean HDRF in the MIZ differs from homogeneous ocean surfaces due to wave attenuation. Using individual HDRFs of both surface types and the sea ice fraction, the mixed HDRF describing the directional reflectivity of the inhomogeneous surface of the MIZ was retrieved by a linear weighting procedure. Accounting for the wave attenuation, good agreement between the average measured HDRF and the constructed HDRF of the MIZ was found for the presented case study.

Determination of Spectral and Broadband Albedos in Visible-near Infrared Bands for Different Phenophases of Wheat Using Hemispherical Directional Reflectance Measurements

Albedo is an important parameter in radiation balance, energy balance, atmospheric correction of remote sensing data and weather forecasting models. The values of albedo of agricultural area vary with changes in biophysical parameters at different phenophases of the crop. Spectral and broadband albedo of visible-infrared bands for wheat canopy was estimated with numerical and spectral integration of hemispherical directional reflectance factors (HDRFs). The HDRF measurements on wheat were acquired at 54 view angles (6 azimuthal planes × 9 view zenith angles) to cover the hemispheric span up to 60° view zenith at 7-8 days’ interval during early growth stages to physiological maturity. Canopy and atmospheric parameters were measured parallel to HDRFs of the crop. The spectral and broadband albedo of wheat varies in decreasing pattern with advancement of growth stages. Visible-infrared albedo of crop was maximum at early growth stages (tillering and booting; 0.23) and minimum at late growth stages (late milking and dough; 0.15). The albedo values retrieved from HDRF in this investigation can be useful for phenophase specific applications in cropland fluxes algorithms, crop phenotyping, regional climate modeling and other remote sensing studies.

PROSDM: Applicability of PROSPECT model coupled with spectral derivatives and similarity metrics to retrieve leaf biochemical traits from bidirectional reflectance

The PROSPECT model, one of the most popular leaf radiative transfer models, has long been used for retrieving leaf biochemical traits from leaf directional-hemispherical reflectance factor (DHRF) spectra, while remains underexplored for applications to the leaf bidirectional reflectance factor (BRF) spectra to retrieve leaf biochemical traits. Existence of leaf surface reflectance and anisotropic property could be the main issues that constrain the applicability of the PROSPECT inversion to assess leaf biochemical traits from leaf BRF spectra. This study presents an inversion method by integrating the PROSPECT model with spectral derivatives and similarity metrics (SDM), called PROSDM, to remove the difference between leaf BRF and DHRF spectra and retrieve leaf biochemical traits from leaf BRF spectra. Leaf BRF spectra and the corresponding contents of chlorophyll (Cab), carotenoid (Cxc), water (Cw), and dry matter (Cm) were obtained from ten datasets across a wide variety of plant species with varied growth stages, nutrition status, and planting regions. The datasets showed that the significant difference existed between leaf BRF and DHRF spectra, which varied with spectral wavelengths and plant species, and affected the accuracies of retrieving Cab, Cxc, Cw, and Cm. To eliminate the difference between leaf BRF and DHRF spectra independent on wavelengths, spectral derivatives were applied. When the difference between BRF and DHRF spectra varied with wavelengths, spectral derivatives only removed part of the difference, and implementation of the Manhattan distance compensated the limitation of the spectral derivatives to further reduce the difference. As a result, the PROSDM outperformed the PROSPECT and PROCOSINE inversions as well as PROCWT to retrieve Cab, Cxc, Cw, and Cm from leaf BRF spectra with the root mean square errors (RMSEs) of 7.64 μg/cm2, 2.77 μg/cm2, 0.0041 g/cm2, and 0.0024 g/cm2, respectively. Significant improvements in the retrievals of Cab, Cxc, Cw, and Cm were obtained with the RMSEs reduced by 20.33%, 29.34%, 25.45%, and 44.19% compared to the PROSPECT inversion, respectively. It was further found that the model inversions were affected by the spectral saturation, PROSPECT versions, spectral subdomains, and the range of model parameters. The retrieval results by different inversion methods may be improved with the suitable spectral subdomains and range of model parameters. Importantly, the proposed PROSDM showed the great potential to alleviate these negative effects on the retrievals of Cab, Cxc, Cw, and Cm. The performance assessment of PROSDM demonstrates a promising potential for its applications in remote sensing aiming at retrievals of leaf biochemical traits from leaf BRF spectra.

Optical Properties of Snow Surfaces: Multiangular Photometric and Polarimetric Hyperspectral Measurements

Understanding the optical properties of light reflected from snow surfaces is fundamental for remote sensing-based characterizations of snow properties and quantification of radiative transfer in the atmosphere-earth system. In theory, both intensity and polarization are required for describing the optical properties of light reflected from snow. However, thus far, a few studies have focused on the polarimetric properties of snow. In this study, we measured both multiangular photometric and polarimetric (based on the Stokes parameters) hyperspectral field results of snow with different properties (grain size, pollution levels, and microscopic surface roughness). By considering the absorption ratio of the polarizer, the intensity defined by photometric results [bidirectional reflectance factor (BRF) and hemispherical directional reflectance factor (HDRF)] was first confirmed to be similar to those derived from polarimetric measurements [I parameter reflectance factor (IpRF)] of snow surfaces. Then, the bidirectional polarized reflectance factor (BPRF) of snow, which is used to define the polarimetric properties of snow, was found to be useful for characterizing snow properties. Moreover, comparing ground measurements of snow BPRF with modeled results, we found that some existing BPRF models did not match well with the BPRF measured in the 2π space. These results suggest that more attention should be paid to the combination of IpRF (BRF or HDRF) and BPRF because polarimetric measurements can be used both for describing the optical properties of light reflected from snow and for quantifying snow properties.

Parameterizing anisotropic reflectance of snow surfaces from airborne digital camera observations in Antarctica

Abstract. The surface reflection of solar radiation comprises an important boundary condition for solar radiative transfer simulations. In polar regions above snow surfaces, the surface reflection is particularly anisotropic due to low Sun elevations and the highly anisotropic scattering phase function of the snow crystals. The characterization of this surface reflection anisotropy is essential for satellite remote sensing over both the Arctic and Antarctica. To quantify the angular snow reflection properties, the hemispherical-directional reflectance factor (HDRF) of snow surfaces was derived from airborne measurements in Antarctica during austral summer in 2013/14. For this purpose, a digital 180∘ fish-eye camera (green channel, 490–585 nm wavelength band) was used. The HDRF was measured for different surface roughness conditions, optical-equivalent snow grain sizes, and solar zenith angles. The airborne observations covered an area of around 1000 km × 1000 km in the vicinity of Kohnen Station (75∘0′ S, 0∘4′ E) at the outer part of the East Antarctic Plateau. The observations include regions with higher (coastal areas) and lower (inner Antarctica) precipitation amounts and frequencies. The digital camera provided upward, angular-dependent radiance measurements from the lower hemisphere. The comparison of the measured HDRF derived for smooth and rough snow surfaces (sastrugi) showed significant differences, which are superimposed on the diurnal cycle. By inverting a semi-empirical kernel-driven bidirectional reflectance distribution function (BRDF) model, the measured HDRF of snow surfaces was parameterized as a function of solar zenith angle, surface roughness, and optical-equivalent snow grain size. This allows a direct comparison of the HDRF measurements with the BRDF derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite product MCD43. For the analyzed cases, MODIS observations (545–565 nm wavelength band) generally underestimated the anisotropy of the surface reflection. The largest deviations were found for the volumetric model weight fvol (average underestimation by a factor of 10). These deviations are likely linked to short-term changes in snow properties.

In-Situ and Aircraft Reflectance Measurement Effectiveness for CAL/VAL Activities: A Study over Railroad Valley

This paper aims to assess the relationship between the surface reflectance derived from ground based and aircraft measurements. The parameters of the Rahman–Pinty–Verstraete (RPV) and Ross Thick-LiSparse (RTLS) kernel based bi-directional reflectance distribution functions (BRDF), have been derived using actual measurements of the hemispherical-directional reflectance factor (HDRF), collected during different campaigns over the Railroad Valley Playa. The effect of the atmosphere, including that of the diffuse radiation on bi-directional reflectance factor (BRF) parameter retrievals, assessed using 6S model simulations, was negligible for the low turbidity conditions of the site under investigation (τ550≤0.05). It was also shown that the effects of the diffuse radiation on RPV spectral parameters retrieval is linear for the isotropic parameter ρ0 and the scattering parameter Θ, and can be described with a second order polynomial for the k-Minnaert parameter. In order to overcome the lack of temporal collocations between aircraft and in-situ measurements, Monte Carlo 3-D radiative transfer simulations mimicking in-situ and remote sensing techniques were performed on a synthetic parametric meshed scene defined by merging Landsat and Multianglhe Imaging Spectroradiometer (MISR) remote sensing reflectance data. We simulated directional reflectance measurements made at different heights for PARABOLA and CAR, and analyzed them according to practices adopted for real measurements, consisting of the inversion of BRF functions and the calculation of the bi-hemispherical reflectance (BHR). The difference of retrievals against the known benchmarks of kernel parameters and BHR is presented. We associated an uncertainty of up to 2% with the retrieval of area averaged BHR, independently of flight altitudes and the BRF model used for the inversion. As expected, the local nature of PARABOLA data is revealed by the difference of the anisotropic kernel parameters with the corresponding parameters retrieved from aircraft loops. The uncertainty of the resultant BHR fell within ±3%.

Parameter estimation and evaluation of Ross-Li and RPV models for wheat phenophases using hemispherical directional reflectance measurements

ABSTRACT Hemispherical directional reflectance factor (HDRF) measurements of wheat crop acquired with field goniometer system are used to estimate parameters and evaluate anisotropic reflectance models. The HDRFs were sampled at 54 view angles (6 azimuthal planes × 9 view zenith angles) to cover the hemispheric span up to 60° zenith. The observations were made at 7–8 days’ interval during different phenophases of the crop. Biophysical parameters were also measured parallel to HDRF. Kernel driven Ross-Li variants and RPV (Rehman Pinty Verstrate) models parameters are generated by fitting HDRF data. RossThin-H/LiSparse-R model was fitted best for all visible-near infrared bands in early phenophases while the RossThick-H/LiSparse-R model was best fitted for heading and flowering phases in most cases. In late grain development phases (Late milking and Dough) of the wheat, HDRFs of visible bands were best fitted with RossThin-H/LiDense-R model in most instances. The HDRF simulation of wheat by RPV models is identical to Ross-Li models. Both models are adequate to account reflectance anisotropy of wheat canopy. Phenophase specific model parameters can be used to reconstruct reflectance anisotropy of wheat for different applications.

Assessment of unified models for estimating leaf chlorophyll content across directional-hemispherical reflectance and bidirectional reflectance spectra

As an important indicator of plant photosynthetic activity, leaf chlorophyll content (LCC) has often been estimated non-destructively in the past decades from reflectance spectra measured with various spectrometers and leaf-holding accessories. Most studies established LCC predictive models with either integrating sphere measured directional-hemispherical reflectance factor (DHRF) spectra or leaf clip measured bidirectional reflectance factor (BRF) spectra. Given the effect of specular reflection on leaf reflectance, it remains unclear how DHRF spectra differ from the corresponding BRF spectra and whether the derived predictive models could be transferred between these two types of spectral data. To fill the gap in spectral examination and model comparison, this study aimed to examine the effect of specular reflection on leaf reflectance properties, the commonly used spectral indices or indicators, and the derived regression models across a broad variety of leaf DHRF and BRF spectra. Specifically, we quantified the difference between leaf BRF and DHRF spectra measurements and evaluated the effect of specular reflection on the estimation of LCC with 20 spectral features in four categories (simple ratio, SR; modified SR, mSR; double difference index, DD and red edge position, REP). Seven measured datasets collected from a combination of species, growing conditions, sites, and years were used to evaluate the model difference and calibrate the unified models across DHRF and BRF spectra. The robustness of those predictive models was validated with independent measured and simulated datasets comprised of both BRF and DHRF spectra.Our results demonstrated that the BRF spectra exhibited systematically higher amplitude than DHRF spectra. The widely used vegetation indices (VIs) in the SR category exhibited the most noticeable sensitivity to specular reflection as a significant proportion in BRF spectra. The adverse effect of specular reflection can be alleviated by the other three categories to different extents. With further assessment of model comparisons, we determined four unified models from the pooled data with two DD indices and two REP metrics. Application of the unified models to the validation spectra yielded low RMSE values up to 4.5 μg/cm2 and would not result in a significant loss in accuracy as compared to the BRF-specific or DHRF-specific LCC predictive models derived from the four spectral features. The assessment of unified models with comprehensive measured and simulated data could help us better understand the mechanism underlying the specular reflection effect on the relationship of LCC with sensitive spectral features. It will also facilitate the direct estimation of LCC with the common types of leaf reflectance spectra, which is beneficial to rapid and non-destructive determination of LCC for the plant science and agronomy communities.

The definition of remotely sensed reflectance quantities suitable for rugged terrain

The anisotropic scattering behavior of land surface is characterized by its bidirectional reflectance-distribution function (BRDF). However, a physically consistent BRDF definition is still lacking for heterogeneous and rugged terrain that accounts for approximately 24% of Earth's land surface. In this study, we revisited current BRDF definitions and updated them for rugged terrain with few dependent parameters: illumination and viewing geometries, terrain shadows, effective areas of illumination and observation, and anisotropic reflectance properties of subpixel-scale slopes. Furthermore, the bidirectional reflectance factor (BRF), hemispherical-directional reflectance factor (HDRF), directional-hemispheric reflectance (DHR), and bi-hemispherical reflectance (BHR) were proposed within the current physical framework of reflectance quantities. These reflectance quantities have been adopted by the 3-D Discrete Anisotropic Radiative Transfer (DART) model to provide the simulations of remote sensing images. To highlight the importance of a proper usage of such reflectance terms, we used DART simulations to present the topographic effects on these reflectance quantities. Finally, the other issues with respect to surface BRDF/BRF, such as spatial scale of rugged terrain, characterization of anisotropic reflectance of micro-scale surfaces, derivative reflectance quantities, topographic parameters, wavelength dependence and reciprocity, and future perspective were discussed.

Radiometric block adjustment of hyperspectral image blocks in the Brazilian environment

ABSTRACTThe objective of this investigation was to study and optimize a hyperspectral unmanned aerial vehicle (UAV)-based remote-sensing system for the Brazilian environment. Comprised mainly of forest and sugarcane, the study area was located in the western region of the State of São Paulo. A novel hyperspectral camera based on a tunable Fabry–Pérot interferometer was mounted aboard a UAV due to its flexibility and capability to acquire data with a high temporal and spatial resolution. Five approaches designed to produce mosaics of hyperspectral images, which represent the hemispherical directional reflectance factor of targets in the Brazilian environment, are presented and evaluated. The method considers the irradiance variation during image acquisition and the effects of the bidirectional reflectance distribution function. The main goal was achieved by comparing the spectral responses of radiometric reference targets acquired with a spectroradiometer in the field with those produced by the five different approaches. The best results were achieved by correcting the bidirectional reflectance distribution function effects and by applying a least squares method to a radiometric block adjustment using only the image data, thereby achieving a root mean square error of 11.35%.

PROCWT: Coupling PROSPECT with continuous wavelet transform to improve the retrieval of foliar chemistry from leaf bidirectional reflectance spectra

The leaf optical properties model PROSPECT has been widely used to retrieve foliar chemistry in reverse mode from directional-hemispherical reflectance factor (DHRF) spectra measured with integrating sphere equipped spectrometers. With bidirectional reflectance factor (BRF) spectra, some researchers attempted to invert PROSPECT after a modification to the latest version of the model. However, the retrieval accuracy varies greatly with chemical constituents and can be low for some of them, such as dry matter content. This paper proposes a new approach called PROCWT by coupling PROSPECT with continuous wavelet transform (CWT) to suppress the surface reflectance effect and enhance the absorption features of chemical constituents. Instead of the reflectance spectra, the wavelet coefficient spectra generated after CWT were used to construct the merit function for model inversion. Given that the multi-scale decomposition of CWT enables enhancement of chemical-specific absorption features, the use of PROCWT at different scales of wavelet decomposition could lead to improved retrievals of biochemical parameters. The performance of PROCWT was evaluated for estimating foliar chemicals of wheat and rice crops from BRF spectra measured with a leaf clip equipped spectrometer over a two-year field experiment. PROCWT was also compared with the standard PROSPECT inversion (STANDARD), the PROSPECT inversion with the subtraction of surface reflectance (PROREF), and the simplified PROCOSINE (sPROCOSINE).Our results demonstrated that the contribution of surface reflectance component was significant for BRF spectra and the effect of surface reflectance could be suppressed by PROCWT as well as PROREF and sPROCOSINE. Compared with STANDARD, PROCWT and the two traditional methods significantly improved the retrieval accuracies for pigments and leaf water content, but only PROCWT produced significant improvement for dry matter content with a decrease of 14.79g/m2 in the root mean squared error (RMSE) (30% of the mean) over the entire experimental dataset by enhancing dry matter absorption features. High scales of wavelet decomposition were favorable for the estimation of carotenoid and water contents and low scales for the estimation of chlorophyll and dry matter contents. The difference in optimal scale revealed the separation of overlapping absorption features attributed to various chemical constituents. In addition, the newest PROSPECT-D outperformed PROSPECT-5B in the retrieval of chlorophyll content but not for carotenoid. This new physically-based approach could be beneficial to analysts attempting to retrieve leaf chemicals from BRF spectra alone and close-range reflectance imagery of crops and even other vegetation types.

Reference Data Set of Human Skin Reflectance.

This data set contains 100 reference reflectance spectra of human skin, spanning the wavelength region from 250 nm to 2500 nm. The spectra were acquired with a commercial spectrophotometer and are directly traceable to the national scale for directional-hemispherical reflectance factor.

Assessing the consistency of optical properties measured in four integrating spheres

ABSTRACTLeaf optical properties (LOPs) determine the radiation regime of vegetation, thus being key input parameters in leaf and canopy radiative transfer models. It is of great importance to know the uncertainties originating from the LOP measurements. The most common approach to measure LOP uses integrating spheres. They allow measurements of both directional-hemispherical reflectance factor (R) and transmittance factor (T). However, sphere’s design, inner surface coating and measurement protocol differ among the spheres’ models and manufacturers. Our main goal was to evaluate the consistency of optical properties measured in four integrating spheres (Dualsphere, Labspehre, ASD, and Li-cor). Our test samples were three Spectralon® panels, four artificial materials and leaves from six common broadleaf tree species. Results showed that spectra measured in the four integrating spheres were generally similar in the spectral region between 400 and 1600 nm. The average standard deviation computed among the spectra of all samples measured in all spheres was around 0.023 (and varied between 0.005 and 0.044). Statistically significant differences were detected mainly between Dualsphere and Li-cor spheres.

Impacts of coal dust from an active mine on the spectral reflectance of Arctic surface snow in Svalbard, Norway

AbstractLight‐absorbing particles (LAPs) in snow such as dust and black carbon influence the radiative forcing at the Earth's surface, which has major implications for global climate models. LAPs also significantly influence the melting of glaciers, sea ice, and seasonal snow. Here we present an in situ study of surface snow near an active coal mine in the Norwegian Arctic. We couple measurements of spectral hemispherical directional reflectance factor (HDRF) with measurements of LAPs characterized in two ways, as refractory black carbon using a Single Particle Soot Photometer and the total light absorption of LAPs measured with the Light Absorption Heating Method. The Snow Ice and Aerosol Radiation model was constrained by LAP measurements. Results were compared to observed spectral albedo measurements. Modeled and observed albedos were similar at the cleaner and more remote sites. However, the modeled spectral albedos do not fully account for the low spectral albedo measured next to the mine. LAP measurements also showed a large variation in particle sizes (tenths to tens of microns) related to transport distance of the particles from the mine. Here we find that LAPs from coal dust reduce the spectral HDRF by up to 84% next to the mine and 55% 0.5 km downwind of the mine. The coupling of extreme LAP observations (1 ng g−1 to 4863 ng g−1) with HDRF measurements from 350 to 2500 nm has facilitated the development of spectral band pairs, which could be used in the future to remotely assess LAPs in Arctic snow.

Data Service Platform for Sentinel-2 Surface Reflectance and Value-Added Products: System Use and Examples

This technical note presents the first Sentinel-2 data service platform for obtaining atmospherically-corrected images and generating the corresponding value-added products for any land surface on Earth. Using the European Space Agency’s (ESA) Sen2Cor algorithm, the platform processes ESA’s Level-1C top-of-atmosphere reflectance to atmospherically-corrected bottom-of-atmosphere (BoA) reflectance (Level-2A). The processing runs on-demand, with a global coverage, on the Earth Observation Data Centre (EODC), which is a public-private collaborative IT infrastructure in Vienna (Austria) for archiving, processing, and distributing Earth observation (EO) data. Using the data service platform, users can submit processing requests and access the results via a user-friendly web page or using a dedicated application programming interface (API). Building on the processed Level-2A data, the platform also creates value-added products with a particular focus on agricultural vegetation monitoring, such as leaf area index (LAI) and broadband hemispherical-directional reflectance factor (HDRF). An analysis of the performance of the data service platform, along with processing capacity, is presented. Some preliminary consistency checks of the algorithm implementation are included to demonstrate the expected product quality. In particular, Sentinel-2 data were compared to atmospherically-corrected Landsat-8 data for six test sites achieving a R2 = 0.90 and Root Mean Square Error (RMSE) = 0.031. LAI was validated for one test site using ground estimations. Results show a very good agreement (R2 = 0.83) and a RMSE of 0.32 m2/m2 (12% of mean value).

A Radiative Transfer Model for Heterogeneous Agro-Forestry Scenarios

Landscape heterogeneity is a common natural phenomenon but is seldom considered in current radiative transfer (RT) models for predicting the surface reflectance. This paper developed an analytical RT model for heterogeneous Agro-Forestry scenarios (RTAF) by dividing the scenario into nonboundary regions (NRs) and boundary regions (BRs). The scattering contribution of the NRs can be estimated from the scattering-by-arbitrarily-inclined-leaves-with-the-hot-spot-effect model as homogeneous canopies, whereas that of the BRs is calculated based on the bidirectional gap probability by considering the interactions and mutual shadowing effects among different patches. The multiangular airborne observations and discrete-anisotropic-RT model simulations were used to validate and evaluate the RTAF model over an agro-forestry scenario in the Heihe River Basin, China. The results suggest that the RTAF model can accurately simulate the hemispherical–directional reflectance factors (HDRFs) of the heterogeneous scenarios in the red and near-infrared (NIR) bands. The boundary effect can significantly influence the angular distribution of the HDRFs and consequently enlarge the HDRF variations between the backward and forward directions. Compared with the widely used dominant cover type (DCT) and spectral linear mixture (SLM) models, the RTAF model reduced the maximum relative error from 25.7% (SLM) and 23.0% (DCT) to 9.8% in the red band and from 19.6% (DCT) and 13.7% (SLM) to 8.7% in the NIR band. The RTAF model provides a promising way to improve the retrieval of biophysical parameters (e.g., leaf area index) from remote sensing data over heterogeneous agro-forestry scenarios.

A New Method for the Estimation of Broadband Apparent Albedo Using Hyperspectral Airborne Hemispherical Directional Reflectance Factor Values

The broadband albedo values retrieved from satellite sensors are usually compared directly to ground measurements. Some authors have noted the necessity of high spatial resolution albedo estimates to fill the gap between ground measurements and satellite retrievals. In this respect, hyperspectral airborne data with high spatial resolution is a powerful tool. Here, a new operational method for the calculation of airborne broadband apparent albedo over the spectral range of 350–2500 nm is presented. This new method uses the Hemispherical Directional Reflectance Factor (HDRF) as a proxy for the narrowband albedo, assuming a Lambertian approximation. The broadband apparent albedo obtained is compared to that estimated using theapparent albedo equation devised for the Moderate Resolution Imaging Spectroradiometer (MODIS). Airborne data were collected using the Airborne Hyperspectral Scanner (AHS). Field data were acquired at three sites: a camelina field, a green grass field, and a vineyard. The HDRF can be used to approximate the narrowband albedo for all View Zenith Angle (VZA) values for flights parallel to the solar principal plane (SPP); for flights orthogonal to the SPP, discrepancies are observed when the VZA approaches −45°. Root Mean Square Error (RMSE) values in the range 0.009–0.018 were obtained using the new method, improving upon previous results over the same area (RMSEs of 0.01–0.03). The relative error in the albedo estimation using the new method is 12% for −36.2° < VZA < 40.8° in the case of flights parallel to the SPP and less than 15% for −13° < VZA < 45° and 45% for VZA = −45° for flights orthogonal to the SPP. The good performance of the new method lies in the use of the at-surface solar irradiance and the proposed integration method.

Hemispherical-Directional Reflectance (HDRF) of Windblown Snow-Covered Arctic Tundra at Large Solar Zenith Angles

Ground-based measurements of the hemispherical-directional reflectance factor (HDRF) of windblown snow-covered Arctic tundra were measured at large solar zenith angles ( $79^{\circ}$ – $85^{\circ} $ ) for six sites near the international research base in Ny-Alesund, Svalbard. Measurements were made with the Gonio RAdiometric Spectrometer System over the viewing angles $0^{\circ}$ – $50^{\circ}$ and the azimuth angles $0^{\circ}$ – $360^{\circ} $ , for the wavelength range 400–1700 nm. The HDRF measurements showed good consistency between sites for near-nadir and backward viewing angles, with a relative standard deviation of less than 10% between sites where the snowpack was smooth and the snow depth was greater than 40 cm. The averaged HDRF showed good symmetry with respect to the solar principal plane and exhibited a forward scattering peak that was strongly wavelength dependent, with greater than a factor of 2 increase in the ratio of maximum to minimum HDRF values for all viewing angles over the wavelength range 400–1300 nm. The angular effects on the HDRF had minimal influence for viewing angles less than $15^{\circ} $ in the backward viewing direction for the averaged sites and agreed well with another study of snow HDRF for infrared wavelengths, but showed differences of up to 0.24 in the HDRF for visible wavelengths owing to light-absorbing impurities measured in the snowpack. The site that had the largest roughness elements showed the strongest anisotropy in the HDRF, a large reduction in forward scattering, and a strong asymmetry with respect to the solar principal plane.

Characterisation of the HDRF (as a proxy for BRDF) of snow surfaces at Dome C, Antarctica, for the inter-calibration and inter-comparison of satellite optical data

Measurements of the Hemispherical Directional Reflectance Factor (HDRF) of snow surfaces were performed at Dome C, Antarctica, during the Australis Summer 2011–2012 to support the inter-comparison and inter-calibration of satellite optical sensors. HDRF data were collected with the Gonio Radiometric Spectrometer System (GRASS) which performs hyper-spectral measurements of radiance from the same target surface with independent collectors at a number of viewing and azimuth angles in the 0–60° and 0–360° angular ranges, respectively. The radiance collectors, installed on a hemispheric frame and connected to a spectrometer through fibre optics, have an 8° full cone of acceptance and a viewing footprint varying from 0.049m2 at nadir to 0.142m2 at viewing angles of 60°. These relatively small footprints allow for the characterisation of small-scale heterogeneities in the HDRF of observed surfaces. HDRF measurements representative of the Dome C snow surfaces were made at eight different sites along a transect approximately 100m long. All the sites exhibit similar HDRF distributions with inter-site differences explained by small-scale inhomogeneities of the surface. The measured HDRF display marked forward scattering with anisotropy increasing with wavelength in the 400–1600nm spectral region. These data complement those from previous measurements performed in the same area with a different technique. Agreement between the two data sets is shown by differences generally lower than 4% between HDRF distributions derived from a previous study and the spatially averaged HDRF from the various sites along a transect presented in this work.