Spectral reflectance of coral reef benthos and substrate assemblages on Heron Reef, Australia

Leiper, Ian; Phinn, Stuart R.; Dekker, Arnold G.

doi:10.1080/01431161.2011.637675

Cited by 33 publications

(33 citation statements)

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“…This calibration was done in a dark room to minimize stray light. Our equipment design is documented in (Roelfsema et al 2006) and has been used for fieldwork by many others (Leiper et al 2012, Hedley et al 2012, Lim et al 2009, Cheney et al 2008, Matz et al 2006, Cheney and Marshall 2009). …”

Section: Study Site Animal and Substrate Measurementsmentioning

confidence: 99%

Quantification of cuttlefish (Sepia officinalis) camouflage: a study of color and luminance using in situ spectrometry

et al. 2012

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Cephalopods are renowned for their ability to adaptively camouflage on diverse backgrounds.Sepia officinalis camouflage body patterns have been characterized spectrally in the laboratory but not in the field due to the challenges of dynamic natural light fields and the difficulty of using spectrophotometric instruments underwater. To assess cuttlefish color match in their natural habitats, we studied the spectral properties of S. officinalis and their backgrounds on the Aegean coast of Turkey using point-by-point in situ spectrometry. Fifteen spectrometry datasets were collected from seven cuttlefish; radiance spectra from animal body components and surrounding substrates were measured at depths shallower than 5m. We quantified luminance and color contrast of cuttlefish components and background substrates in the eyes of hypothetical di-and trichromatic fish predators. Additionally, we converted radiance spectra to sRGB color space to simulate their in situ appearance to a human observer. Within the range of natural colors at our study site, cuttlefish closely matched the substrate spectra in a variety of body patterns.Theoretical calculations showed that this effect might be more pronounced at greater depths. We also showed that a non-biological method ("Spectral Angle Mapper"), commonly used for spectral shape similarity assessment in the field of remote sensing, shows moderate correlation to biological measures of color contrast. This performance is comparable to that of a traditional measure of spectral shape similarity, hue and chroma. This study is among the first to quantify color matching of camouflaged cuttlefish in the wild.3

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Section: Study Site Animal and Substrate Measurementsmentioning

confidence: 99%

Quantification of cuttlefish (Sepia officinalis) camouflage: a study of color and luminance using in situ spectrometry

et al. 2012

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“…Finally, an albedo spectrum was constructed for each benthic type (i.e., light and dark). This was done by assigning the most appropriate benthic albedo spectrum from a precompiled spectral reflectance library [Leiper et al, 2011;Roelfsema and Phinn, 2012] to each biodiversity type listed in Table 1. The multiple albedo spectra assigned to each class (Table 1) were then averaged together resulting in two separate (''dark'' and ''light'') albedo spectra as shown in Figure 4.…”

Section: Benthic Albedo Mapmentioning

confidence: 99%

A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

et al. 2015

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A semianalytical ocean color inversion algorithm was developed for improving retrievals of inherent optical properties (IOPs) in optically shallow waters. In clear, geometrically shallow waters, light reflected off the seafloor can contribute to the water-leaving radiance signal. This can have a confounding effect on ocean color algorithms developed for optically deep waters, leading to an overestimation of IOPs. The algorithm described here, the Shallow Water Inversion Model (SWIM), uses pre-existing knowledge of bathymetry and benthic substrate brightness to account for optically shallow effects. SWIM was incorporated into the NASA Ocean Biology Processing Group's L2GEN code and tested in waters of the Great Barrier Reef, Australia, using the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua time series (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013). SWIM-derived values of the total non-water absorption coefficient at 443 nm, a t (443), the particulate backscattering coefficient at 443 nm, b bp (443), and the diffuse attenuation coefficient at 488 nm, K d (488), were compared with values derived using the Generalized Inherent Optical Properties algorithm (GIOP) and the Quasi-Analytical Algorithm (QAA). The results indicated that in clear, optically shallow waters SWIM-derived values of a t (443), b bp (443), and K d (443) were realistically lower than values derived using GIOP and QAA, in agreement with radiative transfer modeling. This signified that the benthic reflectance correction was performing as expected. However, in more optically complex waters, SWIM had difficulty converging to a solution, a likely consequence of internal IOP parameterizations. Whilst a comprehensive study of the SWIM algorithm's behavior was conducted, further work is needed to validate the algorithm using in situ data.

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“…Even the currently available spaceborne systems with spatial resolution of 1-4 m are unlikely to capture "pure", unmixed pixels [5,14,15]. Concordantly, the substrate combination within a single pixel may not linearly contribute to its overall reflectance pattern [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…Spectral separability of reef substrates has drawn the attention of many researchers (e.g., [3,5,27]). Most of them have focused on hyperspectral data that benefit from the ability to detect unique spectral features [27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

“…Among these applications, the most desired output is an image classification (or thematic mapping) by which researchers can quantify or map substrates in their study area (e.g., [5][6][7]). However, the integrity of marine remotely sensed data may often be compromised due to: (1) environmental effects-the optical effect of the water and air columns (e.g., [8][9][10]); (2) sensor-imposed effects-spatial, spectral, and noise limitations (e.g., [11,12]); and (3) spectral similarities between the reflectance of the different desired substrate (e.g., [5,6,13]). …”

Section: Introductionmentioning

confidence: 99%

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Ground-Level Classification of a Coral Reef Using a Hyperspectral Camera

Caras

Karnieli

2015

Remote Sensing

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Especially in the remote sensing context, thematic classification is a desired product for coral reef surveys. This study presents a novel statistical-based image classification approach, namely Partial Least Square Discriminant Analysis (PLS-DA), capable of doing so. Three classification models were built and implemented for the images while the fourth was a combination of spectra from all three images together. The classification was optimised by using pre-processing transformations (PPTs) and post-classification low-pass filtering. Despite the fact that the images were acquired under different conditions and quality, the best classification model was achieved by combining spectral training samples from three images (accuracy 0.63 for all classes). PPTs improved the classification accuracy by 5%-15% and post-classification treatments further increased the final accuracy by 10%-20%. The fourth classification model was the most accurate one, suggesting that combining spectra from differ conditions improves thematic classification. Despite some limitations, available aerial sensors already provide an opportunity to implement the described classification and mark the next investigation step. Nonetheless, the findings of this study are relevant both to the field of remote sensing in general and to the niche of coral reef spectroscopy.

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Spectral reflectance of coral reef benthos and substrate assemblages on Heron Reef, Australia

Cited by 33 publications

References 50 publications

Quantification of cuttlefish (Sepia officinalis) camouflage: a study of color and luminance using in situ spectrometry

Quantification of cuttlefish (Sepia officinalis) camouflage: a study of color and luminance using in situ spectrometry

A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

Ground-Level Classification of a Coral Reef Using a Hyperspectral Camera

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