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Abstract
For Earth observation remote sensing, high quality reflectance spectra are necessary for model input, algorithm development, and validation of derived products. In the aquatic environment, a common approach for making spectral reflectance measurements involves using a calibrated reflectance standard such as a Spectralon plaque underwater. The manufacturer provides a National Institute of Standards and Technology traceable reflectance curve with each standard, measured in air. Here, we demonstrate how the reflectance factor changes when submerged in water based on the standard albedo and viewing geometry. Target reflectances calculated incorrectly with the air calibrated values are 10%–60% lower than those estimated with submerged plaque calibrations. We provide guidelines for proper use and calibration of standards underwater.
© 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. INTRODUCTION
Spectral reflectance is the ratio of photons scattered from a target relative to those incident on it. Reflectance is a property of the target, semi-independent of local light fields, and is therefore an important parameter in a variety of marine studies including remote sensing, water column light field studies, behavioral and visual biology, and benthic ecology [1–9]. For underwater in situ measurements of benthic targets, one of the more common techniques of measuring reflectance involves a spectroradiometer in an underwater housing with a fiber-optic probe or foreoptic [2,10–12], though other techniques have been successfully employed [7,13]. In this methodology, the spectral distribution and relative intensity of the light reflected off of a target, such as a coral fragment or kelp frond, is recorded and compared to that from a well characterized optical reflectance standard (Fig. 1). Implicit to this method is the assumption that both the target and sample are Lambertian reflectors, meaning that they diffuse and reflect light equally in all directions, though both samples and standards diverge to varying degrees from this assumption [14–17].
Fig. 1. Divers making in situ reflectance measurements of coral reef constituents using ambient (top) and augmented (bottom) illumination. The hydrophobic nature of Spectralon results in surface bubbles (inset) that must be removed before the standard can be utilized.
By far the most commonly used standard [18] is Spectralon (Labsphere, Inc.), a compressed form of powdered polytetrafluoroethylene (PTFE) [19]. Spectralon is a virtually Lambertian reflector in air, providing relatively flat reflectance at most wavelengths from the UV to IR. Spectralon is available from the manufacturer in a variety of levels, from 2%–99% reflectance with calibrations traceable to the United States National Institute of Standards and Technology (NIST). The reflectance properties of white, 99% reflective Spectralon standards have been well characterized [16,17,20–26]. Some studies [22,27–30] have focused on “gray” standards, which have reflectance values below 99%. These standards are produced by adding varying amounts of carbon black to PTFE during manufacturing [19]. While useful in making reflectance measurements of dark targets [5,31], darker standards exhibit increasingly non-Lambertian behavior [30,32] relative to 99% standards.
It must be noted that while the concept of “reflectance” as a property of a given object is conceptually simple, the specific geometry and instrumentation utilized in making the instrument must be considered, and precise terminology is necessary. While a full discussion of this topic is beyond the scope of the present study, it is important to note that when utilizing a standard such as Spectralon, what is actually being measured is the radiance from a given target relative to that from the standard under the same illumination conditions and geometry. This is the bidirectional reflectance or bidirectional reflectance factor $\textit{BRF}(\lambda)$ [16], though the more convenient term “reflectance” is encountered interchangeably in the literature. We have therefore taken the approach here of using “reflectance” generally, and the specific terms bidirectional reflectance factor $\textit{BRF}(\lambda)$ or reflectance factor where appropriate. While the measurements necessary to derive $\textit{BRF}(\lambda)$ are theoretically straightforward to make, several important considerations must be taken into account when using Spectralon underwater aside from those inherent to reflectance measurements, such as appropriate illumination, measurement and light source geometry, and distance to target. The hydrophobic nature of Spectralon causes bubbles to form on its surface, increasing the apparent or effective reflectance value of the standard [3,4]. Further, the bidirectional reflectance distribution function (BRDF) of the material differs underwater from that in air to some degree, leading to further divergence from diffuse, Lambertian behavior [14]. As a result of these complications, the effective bidirectional reflectance factor of the standard $\textit{BRF}{(\lambda)_{{\rm std}}}$ may be substantially different underwater from the nominal “reflectance” $RN{(\lambda)_{{\rm std}}}$ provided by the manufacturer [33], leading to potential errors in the magnitude of calculated ${\textit BRF}(\lambda)$ for underwater targets. This divergence is not necessarily equal at all wavelengths, or for all magnitudes of nominal reflectance, i.e. gray or white standards [4,16]
Here, we present submerged measurements of Spectralon standards of varying nominal reflectance. We quantify the shift in the effective $\textit{BRF}{(\lambda)_{{\rm std}}}$ for each standard when submerged, and estimate the degree to which this shift can lead to error in measured $\textit{BRF}(\lambda)$ for a typical benthic target or sample. We provide correction factors for a range of Spectralon standards, and a simple methodology for generating such corrections for a given individual standard and measurement geometry.
2. METHODS
Two radiance measurements are necessary for calculating bidirectional reflectance factor $\textit{BRF}(\lambda)$ using a single spectroradiometer: radiance reflected from the standard, and radiance from the object of interest. We carried out these measurements in air and underwater for comparison. Spectralon standards of five different nominal reflectance values were examined: 10%, 20%, 50%, 75% (gray), and 99% (white). All gray standards (${\rm R} \lt {99}\%$) had been used in field or laboratory studies, and likely diverged from both the manufacturer provided spectral reflectance and near-Lambertian behavior. The 99% standard was pristine, and therefore used as a transfer reference, rather than applying the manufacturer provided, nominal data for the gray standards. To model the potential impact of the error in a standard reflectance factor on typical samples of interest, intertidal macro algae rockweed (Fucus sp.) was harvested locally and included in the initial experiment.
A. Experimental Setup
Spectral radiance was measured using a Field Spec 4 Wide-Res fiber optic spectroradiometer (ASD, Inc.) fitted with a flat fiber-optic probe of 25° field of view (FoV). This instrument has a spectral range of 350–2500 nm with a resolution of 3 nm in the range 350–1400 nm and 30 nm from 1400–2500 nm. For this study, the range considered is that most relevant to underwater optics: 400–800 nm. Multiple series of radiance measurements were made for each standard at two viewing angles from nadir ($\theta$): 5° and 45°. While we found that many studies (both in situ and laboratory) do not report the relative angles of illumination, sample, and sensor, nearly nadir viewing angles are perhaps the most appropriate and widely utilized [5,33–36]. However, an angle of 45° has also been used by some researchers [2,10,11,37,38], and we have therefore chosen to examine both angles. The probe face was fixed at a distance of 1 cm to targets to ensure overfill of the probe FoV and reduce the impact of attenuation due to water. The probe was positioned orthogonally to the principle solar plane to minimize self-shading. To simulate field measurements by divers, data were collected under daylight illumination at the University of Connecticut—Avery Point, Groton, CT USA, on 24 November 2015 (Fig. 2). Measurements were taken between 11:00 and 12:30 local time under clear sky and stable atmospheric and illumination conditions, such that the light field was relatively constant between corresponding radiance measurements. For underwater measurements, a shallow tank was filled with artificial seawater (33 psu) to 10 cm depth. The tank was painted with black Rustoleum Flexidip black rubber coating to minimize stray reflected light. This background was chosen due to its low, spectrally flat reflectance at wavelengths longer than 650 nm compared to other black background materials [33]. Standards were placed in the tank by hand. To remove visible bubbles, standards were shaken and then gently wiped with the edge of a piece of plastic underwater paper. Care was taken not to damage or alter the surface of the standards during this process. The radiance at each viewing angle $\theta$ was recorded for all standards, and for the sample algae. All radiance spectra were collected as a median of five locations on the target, each of which was a mean of five spectra. To assess the repeatability of a measured submerged Spectralon reflectance factor, an independent series of measurements using the same Spectralon standards and a locally harvested kelp frond (Saccharina sp.) was carried out the following year (19 November 2016). Between experimental sessions, the 10% and 20% standards had been used for field measurements (submerged) and cleaned multiple times, though use records were not kept. The 50%, 75%, and 99% standards were only used in a laboratory setting and did not require refinishing.
Fig. 2. Measurements were made under natural illumination at viewing angles of 45° (left) and 5° (right). Inset: Spectralon standards of (from top left) 99%, 75%, 20%, and 10% nominal reflectance used in the experiment. The 50% standard is not pictured.
B. Reflectance Factor Derivation
The effective $\textit{BRF}{(\lambda ,\theta)_{{\rm std}}}$ of each gray standard (10%–75% nominal) was calculated relative to a 99% standard, in air and submerged:
Table 1. Values of ${r_\theta}$ from Voss and Zhang [16] Used in Adjusting Reflectance of 99% Spectralon for Geometry and Submersion
The uncertainty for each standard and geometry at the ${ k} = {1}$ (68.4%) confidence level was estimated using the root sum square (RSS) method [40] based on the standard deviation of each radiance measurement, the manufacturer provided reflectance uncertainty of the 99% Spectralon standard, and the standard deviation of the factor ${r_\theta}$ reported by [16]. The uncertainty proved to be virtually invariant with wavelength, and a representative value at 600 nm is shown in Table 2.
Table 2. Effective Bidirectional Reflectance Factor Uncertainty Budget at 600 nm for a Submerged 75% Standard Viewed at 5°, $k = 1$
C. Reflectance of Biological Samples
For the algae sample (Fucus sp.), the reflectance factor was calculated relative to each standard using the $\textit{BRF}{(\lambda ,\theta)_{{\rm std}}}$ calculated for both air and water. Submerged radiance measurements were made at 5° and 45° viewing geometry as described above, with algae reflectance $\textit{BRF}{(\lambda ,\theta)_{{\rm alg}}}$ calculated as
3. RESULTS
A. Change in Effective Reflectance of Spectralon Standards
In air, $\textit{BRF}{(\lambda ,\theta)_{{\rm std}}}$ differed by less than 0.03 (absolute reflectance value) for all gray standards between 5° and 45° viewing geometries (Fig. 3). Submerged, up to a 0.07 difference was observed between geometries (Fig. 3). Relative to their in-air values (Table 3), the effective $\textit{BRF}{(\lambda ,\theta)_{{\rm std}}}$ increased by up to 16% absolute reflectance, depending on standard and geometry (Fig. 4). The relative increase in reflectance factor for a given standard, however, was much greater and showed a generally inverse correlation with nominal reflectance. The 20% standard was 33% more reflective at 600 nm when submerged in the 5° geometry, and 59% brighter in the 45° geometry (Table 4). The plaques were expected to have a nearly flat spectral shape across the spectrum. However, some spectral shape differences were discernible, with a larger relative increase at the shorter wavelengths for the 20% and 10% gray targets.
Fig. 3. Bidirectional reflectance factors of the five Spectralon standards with a viewing geometry of $\theta = 5^ \circ$ (solid lines) and 45° (dashed lines), as measured dry (top) and submerged (bottom). Data impacted by artifacts due to the 760 nm oxygen A band have been removed (758–768 nm). Error bars have been omitted for clarity. Standards that had been cleaned and resurfaced are noted in the legend with *.
Table 3. Bidirectional Reflectance Factor of Spectralon Standards in Air and Submerged at 600 nm from Different Viewing Anglesa
Fig. 4. Comparison of Spectralon bidirectional reflectance factor as measured dry (solid lines) and submerged (dashed) for viewing geometries of $\theta = 5^ \circ$ (top) and 45° (bottom). Data impacted by artifacts due to the 760 nm oxygen A band have been removed (758–768 nm). Error bars have been omitted for clarity. Standards that had been cleaned and resurfaced are noted in the legend with *.
Table 4. Increase in Relative BRF of Spectralon Standards When Submerged at 600 nm
B. Impact of Standard Submersion on Derived Reflectance of Algae Samples
The reflectance of the rockweed sample (Fucus sp.) measured using a submerged standard (Fig. 5) showed substantial variation in magnitude when calculated using nominal standard reflectance values. When $\textit{BRF}{(\lambda ,\theta)_{{\rm alg}}}$ was calculated using the submerged $\textit{BRF}{(\lambda ,\theta)_{{\rm std}}}$ spectra, reflectance variation calcualted with all standards was reduced to within the uncertainty of the measurement (Table 5). Uncertainty of $\textit{BRF}{(\lambda ,\theta)_{{\rm alg}}}$ was calculated using the RSS method as for Spectralon (Table 2), but with the addition of the standard deviation in measurements of the algae radiance.
A similar trend was observed for $\textit{BRF}{(\lambda ,\theta)_{{\rm alg}}}$ of a submerged kelp sample Saccharina sp. (Fig. 6), collected in a subsequent experiment. The $\textit{BRF}{(\lambda ,\theta)_{{\rm alg}}}$ calculated incorrectly using the dry plaque calibrations was significantly lower than $\textit{BRF}{(\lambda ,\theta)_{{\rm alg}}}$ calculated using the submerged calibration factors. The higher variability in the submerged reflectances in visible wavelengths (450–700 nm) compared to five was likely due to changes in the standards themselves with use over time.
Fig. 5. Reflectance of rockweed Fucus sp. calculated using dry reflectance factors (left columns) and with the calibrated submerged standard data (right columns) for viewing angles $\theta = 5^ \circ$ and 45°. Inset regions have been expanded to show variability in derived $\textit{BRF}{(\lambda ,\theta)_{\rm{alg}}}$. Data impacted by artifacts due to the 760 nm oxygen A band have been removed (758–768 nm). Error bars have been omitted for clarity. Standards that had been cleaned and resurfaced are noted in the legend with *.
Table 5. Fucus sp. BRF Calculated Using the Appropriate Submerged Standard Calibration for the Appropriate Viewing Angles at 600 nma
4. DISCUSSION
When using Spectralon underwater, the manufacturer supplied reflectance spectrum must be corrected for submersion and geometry. Otherwise, the magnitude of reflectance of the target may be overestimated. This is particularly true when utilizing gray standards, which are typically employed for dark targets such as corals [5,31,33]. The bidirectional reflectance factor may be calculated with a dry (measured or manufacturer provided) reflectance spectrum of a Spectralon standard. However, as shown in Table 3, the effective spectral reflectance factor of the submerged plaque is substantially higher than the dry Spectralon, ranging from 6%–10% for the white 99% standard to 30%–50% higher for the dark 10% standard, and we are aware of only limited mentions of this issue in the literature [16,33]. The sample reflectance should therefore be estimated using a calibrated, submerged reflectance factor for the appropriate viewing angle. Our results indicate that the submerged reflectance of a given gray standard may be easily estimated through comparison to a 99% reference. Other authors have noted that for 99% Spectralon, the submerged reflectance of the standard may be sufficiently close to that in air such that the divergence might be ignored relative to other sources of error inherent to field measurements [4,16]. It should be noted that changes in solar zenith angle (SZA) between measurements of a reflectance standard and target can lead to errors in the magnitude of the derived reflectance spectrum [39]. The potential error in absolute reflectance due to a change in SZA between reference and target measurements for this experiment is estimated to be ${\lt}0.5\%$, and is negligible compared to other potential sources of uncertainty. The manufacturer provided spectral reflectance for Spectralon standards is measured in an 8°/hemispherical configuration, using a Perkin Elmer Lambda 950 dual beam spectrometer with integrating sphere attachment [41,42]. Using the standard in any other configuration will result in a slightly different reflectance factor, and a rigorous treatment of any study involving the use of diffuse reflectance standards should include correction for measurement geometry. This is well understood in terrestrial studies [39,43], but for underwater field measurements this correction may be considered negligible due to the difference in directionality of the light field (limited elevation angles due to Snell refraction, higher diffuse component) and other sources of variance for the measurement. An important source of potential uncertainty in determining the reflectance of a gray-scale standard underwater is the choice of 99% submergence reflectance adjustment, ${r_\theta}$. The most comprehensive absolute measurements were made by Voss and Zhang [16], and we have therefore selected this value in the present study. However, these measurements were made using a single artifact (which may not be perfectly transferable to other individual Spectralon standards) and using monochromatic light (He–Ne laser, 633 nm). Future work should investigate whether ${r_\theta}$ is variable across standards or varies with wavelength.
Fig. 6. Spectral reflectance factor of kelp Saccharina sp. for 5° viewing geometry using the (A) dry and (B) submerged Spectralon reflectance factors, and for 45 ° geometry using (C) dry and (D) submerged factors. Measurements were conducted approximately 1 year after dry and submerged standard factors were derived, and standards had been used and reconditioned in the intervening time. Inset regions have been expanded to show variability in derived algal reflectance. Data impacted by artifacts due to the 760 nm oxygen A band have been removed (758–768 nm). Error bars have been omitted for clarity. Standards that had been cleaned and resurfaced are noted in the legend with *.
While effective $\textit{BRF}{(\lambda ,\theta)_{{\rm std}}}$ increased for darker standards when submerged, the 20% standard showed a greater increase than the 10%. The standards in this study have been used in multiple field studies and reconditioned (following manufacturer protocols), which may have caused divergence from the otherwise evident trend in relative increase. Accordingly, it may not be possible to develop a definitive model to relate nominal reflectance and effective underwater $\textit{BRF}{(\lambda ,\theta)_{{\rm std}}}$ for all levels of gray-scale Spectralon, or even for all individual standards of the same nominal reflectance. We therefore recommend that researchers utilizing gray Spectralon for submerged reflectance measurements characterize a particular standard relative to the brightest reflectance standard available, in the relevant viewing and illumination geometries.
Simple precautions can be taken to improve reflectance measurements underwater. For underwater reflectance measurements, a 99% reference standard that has been cleared of bubbles should be utilized if the instrument or experimental procedure permits, and with the reflectance calibration factor adjusted for submergence. When gray standards (e.g., 10%) must be employed (due to instrument linearity or dynamic range considerations or dark targets, for example), a correction factor should be applied that accounts for the increase in effective reflectance underwater. This is of particular concern for hyperspectral imagers [6,33,44], which may not have the dynamic range to capture both a bright reflectance standard and dark underwater targets within the same image without saturating the detector. If present, bubbles on the surface of the standard can be removed by either shaking the standard (personal observation) or gentle wiping with an oil-free surface such as underwater paper [4,33]. However, the reflectance factor of Spectralon standards does shift following extensive field use and reconditioning, and therefore the standard should be remeasured periodically to ensure high accuracy sample reflectance measurements.
While our results demonstrate a potentially substantial impact on the relative magnitude of derived sample reflectance when standard submersion is uncorrected, there has been significant success in benthic retrieval and remote sensing of these targets. Use cases involving spectral shape, such as band ratio techniques, should be minimally impacted by the magnitude of the sample’s reflectance, provided any such bias is spectrally flat over the region considered. Further, for highly heterogeneous samples, local differences in reflectance due to pigmentation, shading, or other factors may equal or exceed the variation due to discrepancy in dry and submerged standard reflectance factors. For example, the apparent variation in calculated algae reflectance observed in this study is lower than the measured variation of a single coral species or even a single colony [33]. Other factors inherent to in situ data collection, such as movement of the diver and equipment or variations in the light field due to wave action and diver self-shading, may in fact dominate uncertainty or error in the final derived reflectance spectra. These factors are difficult to estimate at present, and future work should investigate the uncertainty associated with the difficulties of diver-based spectrometry in the field.
This study presents only a selection of the potential standards and geometries that may be used for underwater reflectance measurements. Measurements were intended to most closely represent in situ methods and inform best practices for collecting high quality reflectance end members in benthic and coastal studies. Thorough characterization of individual standards, in the intended measurement geometries, is important to minimize or correct errors associated with submersion.
Funding
National Aeronautics and Space Administration (NNX16AB05G).
Acknowledgment
The authors thank Shungudzemowyo Garaba for assistance in data collection.
Disclosures
Author BJR is currently employed by Labsphere, Inc., the manufacturer of Spectralon.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
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