BRDF laboratory measurements

Sandmeier, Stefan; Strahler, Alan H.

doi:10.1080/02757250009532398

Cited by 20 publications

(16 citation statements)

References 42 publications

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“…Subsequently, the parameters were randomly combined to ensure diverse canopies. Then, we calculated the corresponding directional reflectances and albedos by direct simulation using the PROSAIL model in the red band (659 nm) and near-infrared (NIR) band (865 nm), where the angle distribution reflects the general geometry in remote sensing observations [47]. The intervals were 15 • , 10 • and 30 • for the SZA (0-60 • ), VZA (0-80 • ) and ϕ (0-330 • ) with a total angle number of 397, respectively, based on typical angle ranges and experimental design [47,48].…”

Section: Data and Experimental Designmentioning

confidence: 99%

“…Then, we calculated the corresponding directional reflectances and albedos by direct simulation using the PROSAIL model in the red band (659 nm) and near-infrared (NIR) band (865 nm), where the angle distribution reflects the general geometry in remote sensing observations [47]. The intervals were 15 • , 10 • and 30 • for the SZA (0-60 • ), VZA (0-80 • ) and ϕ (0-330 • ) with a total angle number of 397, respectively, based on typical angle ranges and experimental design [47,48]. POLDER can yield directional reflectance when SZA and VZA are close to 70 • [49], and VZA ranges from nadir to 75 • off-nadir for the airborne Cloud Absorption Radiometer (CAR) data set and MODIS satellite [33,41].…”

Section: Data and Experimental Designmentioning

confidence: 99%

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

et al. 2018

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Abstract: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.

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Section: Data and Experimental Designmentioning

confidence: 99%

Section: Data and Experimental Designmentioning

confidence: 99%

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

et al. 2018

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“…Both laboratory and field goniometer measurements have their advantages and disadvantages [22]. A drawback of using laboratory goniometry is that the observed target has to be taken out of its natural environment and that an artificial light source has to be used, which typically results in a non-parallel light beam as opposed to the natural illumination of the sun [23].…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral Reflectance Anisotropy Measurements Using a Pushbroom Spectrometer on an Unmanned Aerial Vehicle—Results for Barley, Winter Wheat, and Potato

et al. 2016

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Abstract:Reflectance anisotropy is a signal that contains information on the optical and structural properties of a surface and can be studied by performing multi-angular reflectance measurements that are often done using cumbersome goniometric measurements. In this paper we describe an innovative and fast method where we use a hyperspectral pushbroom spectrometer mounted on a multirotor unmanned aerial vehicle (UAV) to perform such multi-angular measurements. By hovering the UAV above a surface while rotating it around its vertical axis, we were able to sample the reflectance anisotropy within the field of view of the spectrometer, covering all view azimuth directions up to a 30 • view zenith angle. We used this method to study the reflectance anisotropy of barley, potato, and winter wheat at different growth stages. The reflectance anisotropy patterns of the crops were interpreted by analysis of the parameters obtained by fitting of the Rahman-Pinty-Verstraete (RPV) model at a 5-nm interval in the 450-915 nm range. To demonstrate the results of our method, we firstly present measurements of barley and winter wheat at two different growth stages. On the first measuring day, barley and winter wheat had structurally comparable canopies and displayed similar anisotropic reflectance patterns. On the second measuring day the anisotropy of crops differed significantly due to the crop-specific development of grain heads in the top layer of their canopies. Secondly, we show how the anisotropy is reduced for a potato canopy when it grows from an open row structure to a closed canopy. In this case, especially the backward scattering intensity was strongly diminished due to the decrease in shadowing effects that were caused by the potato rows that were still present on the first measuring day. The results of this study indicate that the presented method is capable of retrieving anisotropic reflectance characteristics of vegetation canopies and that it is a feasible alternative for field goniometer measurements.

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“…They were derived by linear interpolation between the red and NIR MODIS BRDF spectral model parameters. The BRDF shapes at red and NIR wavelengths are often quite different and typically red wavelengths have higher relative reflectance variation with respect to view and solar angle than the NIR [31,32]. The wavelength dependence of BRDF is not well studied, and only a small number of studies have considered red-edge wavelengths [33][34][35].…”

Section: Spectral Brdf Parameters Derived From the Polder Brdf Databasementioning

confidence: 99%

Adjustment of Sentinel-2 Multi-Spectral Instrument (MSI) Red-Edge Band Reflectance to Nadir BRDF Adjusted Reflectance (NBAR) and Quantification of Red-Edge Band BRDF Effects

Roy

Zhang

2017

Remote Sensing

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Optical wavelength satellite data have directional reflectance effects over non-Lambertian surfaces, described by the bidirectional reflectance distribution function (BRDF). The Sentinel-2 multi-spectral instrument (MSI) acquires data over a 20.6 • field of view that have been shown to have non-negligible BRDF effects in the visible, near-infrared, and short wave infrared bands. MSI red-edge BRDF effects have not been investigated. In this study, they are quantified by an examination of 6.6 million (January 2016) and 10.7 million (April 2016) pairs of forward and back scatter reflectance observations extracted over approximately 20 • × 10 • of southern Africa. Non-negligible MSI red-edge BRDF effects up to 0.08 (reflectance units) across the 290 km wide MSI swath are documented. A recently published MODIS BRDF parameter c-factor approach to adjust MSI visible, near-infrared, and short wave infrared reflectance to nadir BRDF-adjusted reflectance (NBAR) is adapted for application to the MSI red-edge bands. The red-edge band BRDF parameters needed to implement the algorithm are provided. The parameters are derived by a linear wavelength interpolation of fixed global MODIS red and NIR BRDF model parameters. The efficacy of the interpolation is investigated using POLDER red, red-edge, and NIR BRDF model parameters, and is shown to be appropriate for the c-factor NBAR generation approach. After adjustment to NBAR, red-edge MSI BRDF effects were reduced for the January data (acquired close to the solar principal where BRDF effects are maximal) and the April data (acquired close to the orthogonal plane) for all the MSI red-edge bands.

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BRDF laboratory measurements

Cited by 20 publications

References 42 publications

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

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

Hyperspectral Reflectance Anisotropy Measurements Using a Pushbroom Spectrometer on an Unmanned Aerial Vehicle—Results for Barley, Winter Wheat, and Potato

Adjustment of Sentinel-2 Multi-Spectral Instrument (MSI) Red-Edge Band Reflectance to Nadir BRDF Adjusted Reflectance (NBAR) and Quantification of Red-Edge Band BRDF Effects

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