Substrate Reflectance Research Articles

Satellite-derived sediment distribution mapping using ICESat-2 and SuperDove

Nearshore sediment distribution is a significant component of fundamental geographic data, but the inherent optical properties of the water column make the large-scale observation of sediment particularly difficult. The development of satellite-based imaging sensors has enabled earth observation to capture more types and finer granularities of ground information, making it possible to obtain the target sediment distribution on a large scale. We use the proposed wavelet clustering algorithm to separate noise points and signal photons from ICESat-2 and then combine multispectral images and a quasi-analytical algorithm to calculate substrate reflectance to reduce the influence of the inherent properties of the water body. Furthermore, a new deep learning model, TSDANet, is being built to combine substrate reflectance and multispectral image data from SuperDove for nearshore sediment identification. We use field data to validate the method through a large number of experiments. The experiments demonstrate that the wavelet clustering algorithm has a coefficient of determination (R2) of 0.90 and 0.95 for signal point extraction over a large scale of high and low photon densities compared with a digital elevation model, respectively. Compared to single-source data, the TSDANet sediment classification kappa improves by 6.44% on average and 8.28% at its maximum. The results indicate that the identification and classification of sediment using ICESat-2 and SuperDove data is a new and highly feasible method.

Computational visualization of semi-transparent metallic thin films with roughness.

We model the visual appearance of thin, semi-transparent metallic films coated on arbitrary three-dimensional substrates, incorporating effects including nanoscale film roughness, microscale substrate roughness, and source of light. Film reflectance is modeled by combining electrodynamic simulations with the Schlick approximation, which is adapted and validated to describe the color appearance of thin semi-transparent metallic films with nanoscale, subwavelength roughness. Diffuse scattering originating from microscale roughness of the substrate and partial reflectance is described by a microfacet model. Photorealistic rendered images generated by our approach are qualitatively compared to photographs of fabricated thin-film samples under similar lighting conditions. We render images of semi-transparent metallic films as a function of film thickness, multilayer composition, substrate type, nanoscale film roughness, microscale substrate roughness, and environmental lighting, yielding physically plausible results consistent with previously reported observations.

Body size and substrate use affect ventral, but not dorsal, brightness evolution in lizards.

Substrate properties can affect the thermal balance of organisms, and the colored integument, alongside other factors, may influence heat transfer via differential absorption and reflection. Dark coloration may lead to higher heat absorption and could be advantageous when substrates are cool (and vice versa for bright coloration), but these effects are rarely investigated. Here, we examined the effect of substrate reflectance, specific heat capacity (cp), and body size on the dorso-ventral brightness using 276 samples from 12 species of cordylid lizards distributed across 26 sites in South Africa. We predicted, and found, that bright ventral colors occur more frequently in low cp (i.e., drier, with little energy needed for temperature change) substrates, especially in larger body-sized individuals, possibly to better modulate heat transfer with the surrounding environment. By contrast, dorsal brightness was not associated with body size nor any substrate thermal property, suggesting selection pressures other than thermoregulation. Ancestral estimation and evolutionary rate analyses suggest that ventral brightness rapidly differentiated within the Cordylinae starting 25 Mya, coinciding with an aridification period, further hinting at a thermoregulatory role for ventral colors. Our study indicates that substrate properties can have a direct role in shaping the evolution of ventral brightness in ectotherms.

Bio-optical properties of the Brazilian Abrolhos Bank’s shallow coral-reef waters

The Abrolhos Bank harbors the richest coral reef ecosystem in the South Atlantic Ocean. It exhibits unique geomorphologic structures, is localized in shallow depths, and is divided into two reef regions with an inner arc close to the coast (3–20 m depth) and an outer deeper arc (5–30 m depth). This study aims to describe some bio-optical properties of the Abrolhos Bank waters and to evaluate the performance of the inversion Hyperspectral Optimization Processing Exemplar (HOPE) model, developed to retrieve optical properties in shallow waters, in the region. To this end, measurements at 75 stations during two field campaigns conducted during the 2013 and 2016 wet seasons were analyzed, and the HOPE model was applied to both in situ remote sensing reflectance (Rrs) spectra and PRecursore IperSpettrale della Missione Applicativa (PRISMA) imagery. Significant differences in optical and biological properties were found between the two arcs. The empirical relationships between chlorophyll-a concentration (Chl-a) and absorption coefficient of phytoplankton at 440 nm (aphy(440)) diverged from Bricaud’s models, suggesting differences in phytoplankton diversity and cell size. In both arcs, total non-water absorption coefficient at 440 nm (aT-w(440)) was dominated by colored dissolved organic matter (CDOM) by ∼60%. Absorption coefficient by CDOM (acdom) presented a higher variability within the outer arc, with the lowest contribution from non-algal particles (NAPs), and the spectral slopes of aCDOM resembled those of the inner arc. The spectral slopes of the NAP absorption coefficient suggested a dominance by organic rather than mineral particles that probably originated from biological production. The HOPE model applied to in situ Rrs performed satisfactorily for depth in the Abrolhos Bank waters, although retrievals of aphy(440), CDOM plus NAP (adg(440)) and aT-w(440) were underestimated with a relative bias of −27.9%, −32.1% and −45.8%, respectively. The HOPE model retrievals from the PRISMA image exhibited low aphy(440) values over the whole scene and the highest adg(440) values in the Caravelas river plume. Very shallow depths (≤3 m), bottom substrate reflectance used as input in the HOPE model, model parametrization associated with the water complexity in the study site, and uncertainties associated to Rrs measurements used as input might be responsible for differences found when comparing HOPE retrievals with in situ measurements.

Optical and biogeochemical properties of diverse Belgian inland and coastal waters

Abstract. From 2017 to 2019, an extensive sampling campaign was conducted in Belgian inland and coastal waters, aimed at providing paired data of optical and biogeochemical properties to support research into optical monitoring of aquatic systems. The campaign was focused on inland waters, with sampling of four lakes and a coastal lagoon during the growth season, in addition to samples of opportunity from other four lakes. Campaigns also included the Scheldt estuary over a tidal cycle and two sampling campaigns in the Belgian coastal zone. Measured parameters include inherent optical properties (absorption, scattering and beam attenuation coefficients, near-forward volume scattering function, turbidity), apparent optical properties (Secchi disc depth, substrate and water-leaving Lambert-equivalent bi-hemispherical reflectance), and biogeochemical properties (suspended particulate matter, mineral fraction of particle mass, particle size distribution, pigment concentration, DNA metabarcoding, flow microscopy counts, and bottom type classification). The diversity of water bodies and environmental conditions covered a wide range of system states. The chlorophyll a concentration varied from 0.63 to 382.72 mg m−3, while the suspended particulate matter concentration varied from 1.02 to 791.19 g m−3, with mineral fraction varying from 0 to 0.95. Depending on system and season, phytoplankton assemblages were dominated by cyanobacteria, green algae (Mamiellophyceae, Pyramimonadophyceae), or diatoms. The dataset is available from https://doi.org/10.1594/PANGAEA.940240 (Castagna et al., 2022).

Measurement of in-vivo spectral reflectance of bottom types: Implications for remote sensing of shallow waters

Field spectroscopy data serve as a standard for the inter-comparisons, calibration and validation of remote sensing data. It also greatly assists in the detection, characterization and mapping of the earth features from the satellite imagery. Strategies and methods for field-based spectro-radiometric measurements are well-established for land and deep ocean applications, however, there are certain challenges and limitations with respect to the shallow water coastal ecosystems. This paper focuses on the background theory, concepts, and measurement techniques of in-vivo sensing of benthic reflectance in shallow water environment. We investigated various measurement methods, influences of water column, air–water interface, sources of errors (introduced by experimental and environmental factors), and the correction methods that are involved in the determination of benthic substrate reflectance. Special emphasis is provided using in-vivo measurements made in the estuarine and shelf regions, illustrating the benthic substrate reflectance at various platforms, i.e., within the water column, above the water surface, at the top-of-atmosphere, in the air, and in a controlled (laboratory) environment. As part of the correction procedure, a new water column correction method is theoretically formulated and examined for varying water optical properties and water depth. A new step correction method is also developed (based on the additive approach) to correct the spectral reflectance measured by a full range spectroradiometer (350–2500 nm) that is in-built with two or more detectors. This study will have direct implications for improving the data quality of field-based spectro-radiometric measurements that are essential for shallow water remote sensing applications.

A Preliminary Study on Benthic Mapping of Uljin Coast Based on Airborne Hyperspectral Imagery Towards the Whitening Detection

Kim, W.; Kim, S.H.; Baek, S.-I.; Kim, H., and Oh, J., 2021. A preliminary study on benthic mapping of Uljin coast based on airborne hyperspectral imagery towards the whitening detection. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 464–468. Coconut Creek (Florida), ISSN 0749-0208. This paper performed a preliminary investigation on the benthic identification methodology that is based on a semi-analytical optical model as a mean for detecting the whitening in the subtidal zone near Uljin, South Korea. Airborne hyperspectral images were acquired using a CASI-1500 sensor for the study area, and the preprocessing including radiometric, geometric, and atmospheric correction were applied to obtain subsurface remote sensing reflectance that is the input to the semi-analytical inversion method. Although the measured bottom reflectance was not available for the area, the experiment conducted with the typical substrate reflectance revealed the spatial distribution of bottom substrates in the area, with an implication to the whitening progress. It is concluded that a closure test with field-measured water quality variables and the collection of bottom substrate reflectance are warranted for more accurate substrate fraction estimates and the whitening detection.

Intra-specific variation of thermal performance, skin reflectance and body size partially co-vary with climate in a lizard

Abstract Thermal adaptation theory posits that variation of thermal traits such as those affecting thermal budgets and the performance of ectotherms should be associated with climate gradients. Under a simple scenario, thermal traits should also co-vary to shape optimal thermal phenotypes under a particular climate. However, geographical variation and covariation of thermal traits can result from other sources of selection and a wide range of other mechanisms. Here, we explore variation and covariation of skin reflectance (melanization), body size and thermal performance traits among three populations of the lizard Cordylus cordylus, a species endemic to South Africa. We also examine relationships between skin reflectance and substrate reflectance, body size and crevice size to test alternative hypotheses. We found partial support for predictions of thermal adaptation to climate regimes for body size, melanization and chill-coma recovery time. Darker lizards also performed optimally at higher temperatures than lighter coloured lizards but there was limited individual covariation between morphological and performance traits. Despite partial support for thermal adaptation, the complex interactions between sex and body size and between substrate reflectance and size underlying skin reflectance emphasized the importance of testing multiple hypotheses when exploring drivers of thermal trait variation within species.

Effect of embedded polydisperse glass microspheres on radiative cooling of a coating

Radiative cooling, as a passive cooling method, is an effective way to save energy and reduce emissions by dissipating heat into space through the “sky window,” without consuming any additional energy. The actual particles in the radiative-cooling coating constitute a particle cloud with non-uniform size distribution and the cooling effect is greatly affected by the spectral reflectance of the actual substrate. Herein, the radiative transfer of actual SiO2 particles doped with a radiative-cooling coating was initially studied. Monte Carlo ray-tracing method, combined with Mie theory, was used to analyze the influence of particle size, volume fraction of particles, coating thickness, and different substrate reflectances on the spectral radiative characteristics of the radiative-cooling coating. The particles size distribution and spectral substrate reflectance were considered. The numerical results show that the maximum spectral reflectance difference between a coating with a uniform-size-distribution particle cloud and a coating with a non-uniform-size-distribution particle cloud can reach 27.3%. Furthermore, the influence of particle parameters and reflectance of the substrate on the radiative characteristics of the radiative-cooling coating is mainly concentrated in the 10–12 μm band. At 8–10 μm and 12–13 μm, the radiative-cooling coating emissivity varies little with the change of particle parameters and the reflectance of substrate, which is induced by the strong absorption of SiO2 particles.

The microstructural, surface, optical and electrochemical impedance spectroscopic study of the semitransparent all-solid-state thin film battery

The microstructural, surface, optical and electrochemical impedance spectroscopic study of the all-solid-state thin film battery cell were done. Obtained results show that all deposited layers are in polycrystalline form. The crystallite sizes of the layers were calculated by Scherrer equation and its values were found in the range of approximately 10–30 nm. This shows that deposited layers are homogeneous. The fabricated battery is a semitransparent in visible region. According to reflectance graphs, total reflectance of the semitransparent all-solid-state is lower than the value of the un-coated glass substrate reflectance value. The capacity of the manufactured battery cell is approximately 8.3 μAh/cm2. The highly reversibility of charging and discharging of the battery was obtained even after 100 cycles. Ultrahigh coulombic efficiency was obtained approximately 100%. It is concluded that the fabricated battery is proper for the optic and photovoltaic applications and also this battery is proper for the high power applications.

Visual cues for woodpeckers: light reflectance of decayed wood varies by decay fungus

ABSTRACT The appearance of wood substrates is likely relevant to bird species with life histories that require regular interactions with wood for food and shelter. Woodpeckers detect decayed wood for cavity placement or foraging, and some species may be capable of detecting trees decayed by specific fungi; however, a mechanism allowing for such specificity remains unidentified. We hypothesized that decay fungi associated with woodpecker cavity sites alter the substrate reflectance in a species-specific manner that is visually discriminable by woodpeckers. We grew 10 species of wood decay fungi from pure cultures on sterile wood substrates of 3 tree species. We then measured the relative reflectance spectra of decayed and control wood wafers and compared them using the receptor noise-limited (RNL) color discrimination model. The RNL model has been used in studies of feather coloration, egg shells, flowers, and fruit to model how the colors of objects appear to birds. Our analyses indicated 6 of 10 decayed ...

Multisensor Analysis of Spectral Dimensionality and Soil Diversity in the Great Central Valley of California.

Planned hyperspectral satellite missions and the decreased revisit time of multispectral imaging offer the potential for data fusion to leverage both the spectral resolution of hyperspectral sensors and the temporal resolution of multispectral constellations. Hyperspectral imagery can also be used to better understand fundamental properties of multispectral data. In this analysis, we use five flight lines from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) archive with coincident Landsat 8 acquisitions over a spectrally diverse region of California to address the following questions: (1) How much of the spectral dimensionality of hyperspectral data is captured in multispectral data?; (2) Is the characteristic pyramidal structure of the multispectral feature space also present in the low order dimensions of the hyperspectral feature space at comparable spatial scales?; (3) How much variability in rock and soil substrate endmembers (EMs) present in hyperspectral data is captured by multispectral sensors? We find nearly identical partitions of variance, low-order feature space topologies, and EM spectra for hyperspectral and multispectral image composites. The resulting feature spaces and EMs are also very similar to those from previous global multispectral analyses, implying that the fundamental structure of the global feature space is present in our relatively small spatial subset of California. Finally, we find that the multispectral dataset well represents the substrate EM variability present in the study area – despite its inability to resolve narrow band absorptions. We observe a tentative but consistent physical relationship between the gradation of substrate reflectance in the feature space and the gradation of sand versus clay content in the soil classification system.

The impacts of environmental variables on water reflectance measured using a lightweight unmanned aerial vehicle (UAV)-based spectrometer system

Remote sensing methods to study spatial and temporal changes in water quality using satellite or aerial imagery are limited by the inherently low reflectance signal of water across the visible and near infrared spectrum, as well as environmental variables such as surface scattering effects (sun glint), substrate and aquatic vegetation reflectance, and atmospheric effects. This study exploits the low altitude, high-resolution remote sensing capabilities of unmanned aerial vehicle (UAV) platforms to examine the major environmental variables that affect water reflectance acquisition, without the confounding influence of atmospheric effects typical of higher-altitude platforms. After observation and analysis, we found: (1) multiple water spectra measured at the same location had a standard deviation of 10.4%; (2) water spectra changes associated with increasing altitude from 20m to 100m were negligible; (3) the difference between mean reflectance at three off-shore locations in an urban water body reached 29.9%; (4) water bottom visibility increased water reflectance by 20.1% in near shore areas compared to deep water spectra in a clear water lake; (5) emergent plants caused the water spectra to shift towards a shape that is characteristic of vegetation, whereas submerged vegetation showed limited effect on water spectra in the studied lake; (6) cloud and sun glint had major effects and caused water spectra to change abruptly; while glint and shadow effects on spectra may balance each other under certain conditions, the water reflectance can also be unpredictable at times due to wave effects and their effects on lines-of-site to calm water; (7) water spectra collected under a variety of different conditions (e.g. multiple locations, waves) resulted in weaker regression models compared to spectra collected under ideal conditions (e.g. single location, no wave), although the resulting model coefficients were relatively stable. The methods and results from this study contribute to better understanding of water reflectance acquisition using remote sensing, and can be applied in UAV-based water quality assessment or to aid in validation of higher altitude imagery.

Prediction of the radiative properties of surfaces covered with particulate deposits

The heterogeneous particulate deposit has a significant impact on the radiative properties of surfaces. It is necessary to establish a physical model to describe the apparent spectral absorptance of surfaces covered with heterogeneous particulate deposits. In this paper, a general method combining the effective medium theory with the RTM-DRE (ray-tracing method based on the decomposition of radiation energy) method is presented to predict the apparent spectral absorptance of such surfaces. The effective optical constants of the inhomogeneous particles were determined by means of the effective medium theory, whereas the radiative properties of the surfaces were calculated by modeling the radiative transfer process based on the RTM-DRE method. Additionally, the experimental characterizations of the dust deposits were investigated to reveal the dust effect on the radiative properties of surfaces, and the experimental data and theoretical results were compared to validate the presented theoretical model. The mean relative errors lie within 11.0% of the solar band and 7.0% of the infrared waveband, which indicates the reliability of the theoretical model. Furthermore, the effect of the geometric structure parameters and material intrinsic properties on the radiative properties of the surfaces with heterogeneous particulate deposit was investigated based on the prediction model. Six main factors including the deposit thickness, particle size, bulk fraction, chemical compositions, H2O content, and substrate reflectance were considered.

Rainfall validates MODIS-derived NDVI as an index of spatio-temporal variation in green biomass across non-montane semi-arid and arid Central Asia

As satellite-derived normalized difference vegetation index (NDVI) is related to vegetation biomass, it may provide a proxy for habitat quality across extensive species ranges where ground-truth data are scarce. However, NDVI may have limited accuracy in sparsely-vegetated arid and semi-arid environments due to signal contamination by substrate reflectance. To validate NDVI as a vegetation proxy in the low-altitude deserts of Central Asia, we examine its response to precipitation across the migratory corridor of Asian Houbara Chlamydotis macqueenii, a threatened gamebird occupying deserts from the Middle East to China. Restricting NDVI data by altitude (masking higher elevations unoccupied by n = 61 satellite-tracked houbara) and 2009 Globcover land cover (excluding cropland and built-up area), we relate moderate-resolution imaging spectroradiometer (MODIS) NDVI data to Global Precipitation Climatology Project precipitation data across five World Wildlife Fund semi-arid ecoregions (totaling 4.06 million km2). We examine this both spatially (per 1°cell, mean annual NDVI and mean precipitation over 16 years, 2000–2015); and temporally (annual NDVI and annual precipitation) using separate temporal General Linear Models per cell and an overall Generalized Linear Mixed Model (GLMM) (including cell ID as a random effect). We sought to explain spatial variation in the NDVI-precipitation relation among temporal per degree-cell models, in terms of the slope (strength) and adjusted (adj.) R2 (explanatory power), using inter-annual mean NDVI (2000–2015) and Gridded Livestock of the World livestock density. NDVI increases with precipitation, both spatially (adj. R2 = 0.58, p < 0.001) and temporally (mean adj. R2 across n = 244, 1° cells = 0.44; GLMM across cells p < 0.001). More vegetated regions show a stronger temporal response of vegetation biomass for a given precipitation increment (slope of NDVI to precipitation in per cell temporal models increases with inter-annual mean NDVI; adj. R2 = 0.38, p < 0.001), reinforcing the conclusion that NDVI provides a proxy for vegetation abundance. The slope of this relation did not differ among ecoregions. Although livestock density is generally assumed to degrade vegetation and weaken the NDVI-precipitation relationship, explanatory power (adj. R2 of per cell NDVI-precipitation models) is weakly, but positively, related to livestock density (adj. R2 = 0.02, p = 0.011). This may be because we assess livestock at a coarse grain, at scales where overall stocking density is positively associated with vegetation abundance, but may also indicate that livestock are not degrading vegetation at regional landscape-scales despite potential localized effects. The strong signature of rainfall shows MODIS NDVI offers a potentially powerful proxy for spatial and temporal variation in arid and semi-arid vegetation at a resolution of 1° and 1 year over the houbara's breeding and wintering range, and probably also at finer spatial resolutions. NDVI can therefore be used in analyses relating (a) staging and wintering site selection to variation in habitat among potential wintering locations, and (b) variation within and between localities to demographic carry-over effects.

An Insect with Selective Control of Egg Coloration

The color and patterning of animal eggs has important consequences for offspring survival. There are examples of between-species and polymorphic differences in egg coloration in birds and amphibians [1-3], as well as cases of birds and insects whose nutritional status or age can cause within-individual variation in egg pigmentation [4-6]. However, no studies to date have demonstrated that individual animals can selectively control the color of their eggs. Here, we show that individual females of the predatory stink bug Podisus maculiventris can control the pigmentation of their eggs during oviposition, as a response to environmental conditions. The color of egg masses produced by individual females can range from pale yellow to dark black/brown. Females tend to lay darker eggs, which are more resistant to UV radiation, on the upper surface of leaves where UV exposure is highest in nature. Conversely, they lay lighter eggs on the undersides of leaves. However, egg color is not determined by the intensity of UV radiation falling on the surface where they are laid. Rather, female stink bugs appear to use a visual assessment of oviposition substrate reflectance to determine egg color. Unexpectedly, biochemical analyses revealed that the egg pigment is not melanin, the most ubiquitous light-absorbing pigment in animals. Our study offers the first example of an animal able to selectively control the color of its eggs.

Tunable filter-based multispectral imaging for detection of blood stains on construction material substrates part 2: realization of rapid blood stain detection

Based on the blood stain detection method and criteria established in part 1 of this article, we combine and organize all necessary tasks to realize the multispectral imaging-based rapid blood stain detection system. To rapidly detect blood stains on the test surface, the developed system automatically captures the spectral images, extracts their spectral data, determines the positions of blood stains, and accurately highlights the positions of blood stains on the display. To achieve such a system, several tasks are newly introduced, including adjustment of camera exposure times to prevent image saturation or excessive darkness, the search for the sampled clean positions of the substrate to determine the substrate reflectance spectrum, and suitable detection procedures and proper arrangement of criteria to eliminate unnecessary calculations. Parallel processes between image capturing and blood stain identification help shorten the time for blood stain identifications despite a large amount of spectral data to be processed. The developed system can identify blood against several other reddish brown stains on several substrates. The measured average identification times on different test surfaces range from only 23.3 to 28.7 s, including the image capturing process.

Thickness determination of graphene on metal substrate by reflection spectroscopy

We show that reflectivity measurements enable the determination of the thickness of multilayered graphene on a metal substrate. The developed technique is based on comparison of the substrate reflectance with and without graphene and relies on the strong absorbance of graphene and high refractive index contrast. We demonstrate the technique by measuring the thickness of the CVD graphene film grown on a copper substrate.

Shallow water substrate mapping using hyperspectral remote sensing

During April 2004 the airborne hyperspectral sensor, HyMap, collected data over a shallow coastal region of Western Australia. These data were processed by inversion of a semi-analytical shallow water optical model to classify the substrate. Inputs to the optical model include water column constituent specific inherent optical properties (SIOPs), view and illumination geometry, surface condition (based on wind speed) and normalised reflectance spectra of substrate types. A sub-scene of the HyMap data covering approximately 4 km 2 was processed such that each 3×3 m 2 pixel was classed as sand, seagrass, brown algae or various mixtures of these three components. Coincident video data were collected and used to estimate substrate types. We present comparisons of the habitat classifications determined by these two methods and show that the percentage validation of the remotely sensed habitat map may be optimised by selection of appropriate optical model parameters. The optical model was able to retrieve classes for approximately 80% of all pixels in the scene, with validation percentages of approximately 50% for sand and seagrass classification, and 90% for brown algae classification. The semi-analytical model inversion approach to classification can be expected to be applied to any shallow water region where substrate reflectance spectra and SIOPs are known or can be inferred.

Factorial Design Experiment to Analyze the Response of a Luminescent Photoelastic Coating

A luminescent photoelastic coating is a relatively new technique to measure full-field surface strain and determine principal strain directions that has many potential applications in engineering. Generally, luminescent photoelastic coating technology uses an in situ strain gage measurement to calibrate the detected optical response to maximum shear strain. This calibration requires the determination of two coating parameters: the polarization efficiency and the coating characteristic. A better understanding and modeling of these two parameters, particularly the polarization efficiency, will enable a simpler a priori calibration and greater measurement accuracy. This paper presents a factorial design experiment that assesses the effect of four factors on the optical strain response of an luminescent photoelastic coating. The factors examined were substrate reflectance, luminescent dye concentration, absorption dye concentration and cure time. Results show the polarization efficiency is strongly correlated with the emission anisotropy of the coating. When the polarization efficiency is modeled as the measured emission anisotropy, the two most significant factors are the substrate reflectance and the luminescent dye concentration. Absorption dye concentration and reflectance-luminescence interaction are minor but significant effects. The most significant tested factors in modeling the coating coefficient are absorption dye concentration and substrate reflectance. The resulting uncertainties for the polarization efficiency and coating characteristic are 1.3 and 3.7%, respectively.