Hyperspectral Bidirectional Reflectance Distribution Function Research Articles

Development of the Ames Global Hyperspectral Synthetic Data Set: Surface Bidirectional Reflectance Distribution Function

AbstractThis study introduces the Ames Global Hyperspectral Synthetic Data set (AGHSD), in particular the surface bidirectional reflectance distribution function (BRDF) product, to support the NASA Surface Biology and Geology (SBG) mission development. The data set is generated based on the corresponding multispectral BRDF products from NASA's MODIS satellite sensor. Based on theories of radiative transfer in vegetation canopies, we derive a simple but robust relationship that indicates that the hyperspectral surface BRDF can be accurately approximated as a weighted sum of the soil surface reflectance, the leaf single albedo, and the canopy scattering coefficient, where the weights or coefficients are spectrally invariant and thus readily estimated from the multispectral MODIS products. We validate the algorithm with simulations by a Monte Carlo Ray Tracing model and find the results highly consistent with the theoretic derivation. Using reflectance spectra of soil and vegetation derived from existing spectral libraries, we apply the algorithm to generate the AGHSD BRDF product at 1 km and 8‐day resolutions for the year of 2019. The data set is biogeochemically and biogeophysically coherent and consistent, and serves the goal to support the SBG community in developing sciences and applications for the future global imaging spectroscopy mission.

Hyperspectral Empirical Absolute Calibration Model Using Libya 4 Pseudo Invariant Calibration Site

The objective of this paper is to find an empirical hyperspectral absolute calibration model using Libya 4 pseudo invariant calibration site (PICS). The approach involves using the Landsat 8 (L8) Operational Land Imager (OLI) as the reference radiometer and using Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm as a hyperspectral source. This model utilizes data from a region of interest (ROI) in an “optimal region” of 3% temporal, spatial, and spectral stability within the Libya 4 PICS. It uses an improved, simple, empirical, hyperspectral Bidirectional Reflectance Distribution function (BRDF) model accounting for four angles: solar zenith and azimuth, and view zenith and azimuth angles. This model can perform absolute calibration in 1 nm spectral resolution by predicting TOA reflectance in all existing spectral bands of the sensors. The resultant model was validated with image data acquired from satellite sensors such as Landsat 7, Sentinel 2A, and Sentinel 2B, Terra MODIS, Aqua MODIS, from their launch date to 2020. These satellite sensors differ in terms of the width of their spectral bandpass, overpass time, off-nadir viewing capabilities, spatial resolution, and temporal revisit time, etc. The result demonstrates the efficacy of the proposed model has an accuracy of the order of 3% with a precision of about 3% for the nadir viewing sensors (with view zenith angle up to 5°) used in the study. For the off-nadir viewing satellites with view zenith angle up to 20°, it can have an estimated accuracy of 6% and precision of 4%.

Modeling and intercomparison of field and laboratory hyperspectral goniometer measurements with G-LiHT imagery of the Algodones Dunes

We compare field hyperspectral bidirectional reflectance distribution function (BRDF) measurements acquired by a hyperspectral goniometer system known as the goniometer of the Rochester Institute of Technology (GRIT) during an experiment in the Algodones Dunes system in March 2015 with NASA Goddard’s light detection and ranging, hyperspectral, and thermal imagery of the site acquired during the experiment. We augment our field spectral data collection with laboratory hyperspectral BRDF measurements of samples brought back from the Algodones Dunes site using GRIT and our second-generation goniometer GRIT-two (GRIT-T). In these laboratory experiments, we vary geophysical parameters such as sediment density and grain size distribution of the sediments that would typically impact observed BRDF with the goal of extending the range of applicability of our resulting BRDF spectral libraries. Geotechnical measurements on site confirm the variability of geophysical parameters such as density and grain size distributions within the dune system, and measurements with GRIT and GRIT-T demonstrate the impact on observed spectral variation. By augmenting field spectral libraries with laboratory BRDF, we show that a greater proportion of the dune system is more faithfully represented in the expanded spectral library. Beyond developing appropriate calibration data for airborne and satellite imagery of the Algodones Dunes, laboratory and field studies also support goals to develop reliable retrieval methods for geophysical quantities such as sediment density directly from spectral imagery. We consider approaches based on the Hapke model. Our approaches use the invariance of the observed functional forms of the single scattering phase function, which must be invariant to differences in the illumination geometry. Fill factor is retrieved and correlates with expected direct measurements of sediment density in a laboratory setting.

Wavelength dependence of the bidirectional reflectance distribution function (BRDF) of beach sands.

The wavelength dependence of the dominant directional reflective properties of beach sands was demonstrated using principal component analysis and the related correlation matrix. In general, we found that the hyperspectral bidirectional reflectance distribution function (BRDF) of beach sands has weak wavelength dependence. Its BRDF varies slightly in three broad wavelength regions. The variations are more evident in surfaces of greater visual roughness than in smooth surfaces. The weak wavelength dependence of the BRDF of beach sand can be captured using three broad wavelength regions instead of hundreds of individual wavelengths.

Land surface VIS/NIR BRDF atlas for RTTOV‐11: model and validation against SEVIRI land SAF albedo product

This study describes the scientific approach and the validation of the visible and near‐infrared snow‐free land surface Bidirectional Reflectance Distribution Function (BRDF) atlas for Version 11 of the Radiative Transfer for the Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) (RTTOV) Forward Model. The atlas provides a global (at a spatial resolution of 0.1°) and monthly mean land surface BRDF for any instrument containing channels with a central wavelength between 0.4 and 2.5 µm, as well as a quality index of the BRDF. It is based on the reconstructed hyperspectral BRDF from the seven channels of the operational and global Moderate Resolution Imaging Spectroradiometer (MODIS) 16 days BRDF kernel‐driven product MCD43C1: a principal component analysis regression method was applied between the seven channels of the MODIS BRDF products and a set of the US Geological Survey hyperspectral reflectance measurements for soils, rocks, and mixtures of both and vegetation surfaces. The comparison of the RTTOV BRDF atlas against the Spinning Enhanced Visible and Infrared Imager (SEVIRI) surface black‐sky albedo products of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Land Satellite Application Facility on Land Surface Analysis (Land‐SAF) shows good spatial and temporal consistency of the RTTOV BRDF atlas when applied on three SEVIRI visible and near‐infrared channels. The RTTOV narrowband black‐sky albedo is retrieved within ±0.01 in absolute accuracy at 0.6 and 1.6 µm and is overestimated by something between 0.01 and 0.03 at 0.8 µm. The temporal variation of the RTTOV broadband black‐sky albedo is consistent with the EUMETSAT Land‐SAF SEVIRI products but overestimated by somewhere between 0.01 and 0.02 when considering the best quality index of the RTTOV BRDF atlas. Less agreement is found in two cases: (i) for extreme geometrical conditions when the satellite zenith angle is greater than 65° and (ii) for lower quality indices of the RTTOV BRDF atlas.

BRDF laboratory measurements

Laboratory studies of the bidirectional reflectance distribution function (BRDF) have greatly improved our understanding of the bidirectional reflectance characteristics of natural and man‐made surfaces. Explorative research and model validation studies in astronomy, remote sensing, material science, and computer graphics have likewise increased the knowledge of BRDF and its relationship to surface properties. In this review, a concise summary of laboratory BRDF studies relevant to remote sensing is given along with a discussion of major advantages and drawbacks of laboratory BRDF experiments and an overview of laboratory goniometric radiometers. Recommendations made for future research directions include the standardization of BRDF laboratory measurements, the initiation of hyperspectral BRDF databases for multidirectional endmember spectra, and the investigation of the BRDF phenomenon at different levels of scale by jointly analyzing laboratory, field, and remote sensing data.

Structure Analysis and Classification of Boreal Forests Using Airborne Hyperspectral BRDF Data from ASAS

A new approach is presented for deriving vegetation canopy structural characteristics from hyperspectral bidirectional reflectance distribution function (BRDF) data. The methodology is based on the relationship between spectral variability of BRDF effects and canopy geometry. Tests with data acquired with the Advanced Solid-State Array Spectroradiometer (ASAS) over Canadian boreal forests during the BOREAS campaign show that vegetation structural characteristics can be derived from the spectral variability of BRDF effects. In addition, the incorporation of both BRDF effects and hyperspectral resolution data substantially improve the classification accuracy. Best classification results are obtained when hyperspectral resolution and BRDF data are combined, but the improvement is not consistent for all classes. For example, adding BRDF information to hyperspectral data increases the overall classification accuracy for a six-class fen site from 37.8% to 44.7%. The addition, however, reduces the accuracy for the jack pine class from 43.6% to 28.8%. These new findings provide evidence for improved capabilities for applications of MISR and MODIS data. The spectral resolution of MODIS is expected to be sufficient to derive canopy structural information based on the spectral variability of BRDF effects, and for MISR a significant improvement of classification accuracies can be anticipated from the combination of nadir reflectance and off-nadir data.

The potential of hyperspectral bidirectional reflectance distribution function data for grass canopy characterization

Hyperspectral bidirectional reflectance distribution function (BRDF) data of Konza prairie grassland acquired in the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) on the ground with two SE‐590 instruments and remotely with the airborne advanced solid‐state array spectroradiometer (ASAS) are analyzed and compared to BRDF data of dense ryegrass obtained in the laboratory and field with the European goniometric facility (EGO) and the Swiss field‐goniometer system (FIGOS). The soil underlying the relatively sparse Konza prairie grass disturbed the spectral BRDF effects of the vegetation components. After a correction of the soil influence based on the bidirectional canopy gap probability, the Konza data from SE‐590 and ASAS sensors showed a consistently strong dependence of spectral BRDF effects from nadir reflectance as was observed in the EGO and FIGOS data. BRDF effects were inversely related to reflectance intensities, low reflectances being associated with pronounced BRDF effects and high reflectances with low BRDF effects. This relationship is due to multiple scattering effects and is influenced by the canopy optical properties and architecture parameters such as leaf area index (LAI), leaf angle distribution (LAD), and the gap fraction. The BRDF data of the Konza prairie grass from both ground and aircraft measurements showed a strong relationship between LAI and spectral BRDF variability. Reflectance data with high spectral resolution in the red edge range from 675 to about 900 nm wavelength, acquired from the two viewing directions with maximum and minimum reflectance intensities proved to be useful for deriving vegetation canopy architecture characteristics from hyperspectral BRDF data. BRDF data with high spectral resolution from the airborne ASAS sensor and from planned commercial remote sensing satellites are therefore an ideal testbed for a further exploration of this promising approach.

A field goniometer system (FIGOS) for acquisition of hyperspectral BRDF data

A new field goniometer system (FIGOS) is introduced that allows in situ measurements of hyperspectral bidirectional reflectance data under natural illumination conditions. Hyperspectral bidirectional reflectance distribution function (BRDF) data sets taken with FIGOS nominally cover the spectral range between 300 and 2450 nm in 704 bands. Typical targets are small-growing, dense, and homogeneous vegetation canopies, man-made surfaces, and soils. Field BRDF data of a perennial ryegrass surface reveal a strong spectral variability. In the blue and red chlorophyll absorption bands, BRDF effects are strong. Less-pronounced bidirectional reflectance effects are observed in the green and in most of the near-infrared range there surface reflectance is high. An anisotropy index (ANIX), defined as the ratio between the maximum and minimum bidirectional reflectance over the hemisphere, is introduced as a surrogate measurement for the extent of spectral BRDF effects. The ANIX data of the ryegrass surface show a very high correlation with nadir reflectance due to multiple scattering effects. Since canopy geometry, multiple scattering, and BRDF effects are related, these findings may help to derive canopy architecture parameters, such as leaf area index (LAI) or leaf angle distribution (LAD) from remotely sensed hyperspectral BRDF data. Furthermore, they show that normalized difference vegetation index (NDVI) data are strongly biased by the spectral variability of BRDF effects.

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.