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The conical–conical reflectance factor (CCRF) has been calculated as an alternative to the bidirectional reflectance distribution function (BRDF) for three types of bare sea ice with varying surface roughness (σ= 0.1–10) and ice thicknesses (50–2000 cm) over an incident solar irradiance wavelength range of 300–1400 nm. The comprehensive study of the CCRF of sea ice presented here is paramount for interpreting sea ice measurements from satellite imagery and inter-calibrating space-borne sensors that derive albedo from multiple multi-angular measurements. The calculations performed by a radiative-transfer code (PlanarRad) show that the CCRF of sea ice is sensitive to realistic values of surface roughness. The results presented here show that surface roughness cannot be considered independently of sea ice thickness, solar zenith angle and wavelength. A typical CCRF of sea ice has a quasi-isotropic reflectance over the hemisphere, associated with a strong forward-scattering peak of photons. Surface roughness is crucial for the location, size and intensity of the forward-scattering peak. As the surface roughness increases, a spreading of the CCRF peak is observed. The hemisphere was split in to 216 quadrangular regions or quads. The peak remains specular for the smaller surface roughnesses (σ=0.001 to σ=0.01), whereas for larger surface roughness features (above σ=0.05), the peak spreads out over multiple quads with a lower intensity than for smaller roughness features, and the highest value is displaced further out on the solar principal plane. Different types of sea ice have a similar pattern with wavelength: the CCRF increases by 30 % from first-year sea ice to multi-year sea ice at 400 nm and up to 631 % at 1100 nm, 32 % from melting sea ice to multi-year sea ice at 400 nm and a maximum of 98 % at 900 nm, and 11 % from melting sea ice to first-year sea ice at 400 nm and up to 86 % at 800 nm. The CCRF calculations presented in this study form the first set of complete CCRF values as an approximation of the BRDF for bare sea ice with a wide range of configurations.

Mesophotic coral reefs, generally defined as deep reefs between 30 and 150 m, are found worldwide and are largely structured by changes in the underwater light field. Additionally, it is increasingly understood that reef-to-reef variability in topography, combined with quantitative and qualitative changes in the underwater light field with increasing depth, significantly influence the observed changes in coral distribution and abundance. Here, we take a modeling approach to examine the effects of the inherent optical properties of the water column on the irradiance that corals are exposed to along a shallow to mesophotic depth gradient. In particular, the roles of reef topography including horizontal, sloping and vertical substrates are quantified, as well as the differences between mounding, plating and branching colony morphologies. Downwelling irradiance and reef topography interact such that for a water mass of similar optical properties, the irradiance reaching the benthos varies significantly with topography (i.e. substrate angle). Coral morphology, however, is also a factor; model results show that isolated hemispherical colonies consistently ‘see’ greater incident irradiances across depths, and throughout the day, compared to plating and branching morphologies. These modeled geometric-based differences in the incident irradiances on different coral morphologies are not, however, consistent with actual depth-dependent distributions of these coral morphotypes, where plating morphologies dominate as you go deeper. Other factors, such as the cost of calcification, arguably contribute to these differences, but irradiance-driven patterns are a strong proximate cause for the observed differences in mesophotic communities on sloping versus vertical reef substrates.

The Bidirectional Reflectance Distribution Function (BRDF) has been calculated for three types of bare sea ice with varying surface roughness (σ = 0.1–10 cm) and ice thicknesses (50–2000 cm) over an incident solar irradiance wavelength range of 300–1400 nm. The comprehensive study of the BRDF of sea ice presented here is paramount for interpreting sea ice measurements from satellite imagery and inter-calibrating spaceborne sensors that derive albedo from multiple multi-angularmeasurements. The calculations performed by a radiative transfer code (PlanarRad) show that the BRDF of sea ice is sensitive to realistic values of surface roughness. The results presented here show that surface roughness cannot be considered indepen- dently of sea ice thickness, solar zenith angle and wavelength. A typical BRDF of sea ice has a quasi-isotropic reflectance over the hemisphere, associated with a strong forward scattering peak of light. Surface roughness is crucial for the location, size and intensity of the forward scattering peak. As the surface roughness increases, a spreading of the BRF peak is observed. The peak remains specular for the smaller surface roughnesses (σ = 0.001 m to σ = 0.01 m), whereas for larger surface roughness features (above σ = 0.05 m), the peak spreads out over multiple quads with a lower intensity than for smaller roughness features, and the highest value is displaced further out on the solar principal plane. Different types of sea ice have a similar pattern with wavelength, the BRF increases by 29.5 % from first-year sea ice to multi-year sea ice at 400 nm and up to 630.7 % at 1100 nm, 31.5 % from melting sea ice to multi-year sea ice at 400 nm and a maximum of 97.7 % at 900 nm, and 11.3 % from melting sea ice to first-year sea ice at 400 nm and up to 86.2 % at 800 nm. As a specific example, for first-year sea ice at λ = 500 nm and θi = 60°, the BRF of an optically thick layer with surface roughness of σ = 0.001 m is 0.543 at nadir. The forward scattering peak is spread over a single quad located at φr = 0°, θr = 60°, that has a BRF of 9.748. For the same configuration with surface roughness of σ = 0.1 m, the nadir has a BRF of 0.549 and the forward scattering peak is spread over 18 quads, located between φr = 345° and φr = 15°, θr = 40° and θr = 87.5° with values between 0.776 and 5.089. The BRDF calculations presented in this study form the first set of complete BRDF values for bare sea ice with a wide range of configurations.

Light scattering characteristics of the cyanobacterium Microcystis are investigated with numerical models for sphere aggregates. During summer bloom seasons, Microcystis is prevalent in many inland waters across the globe. Monitoring concentrations with remote sensing techniques requires knowledge of the inherent optical properties (IOPs), especially the backscattering properties of Microcystis cells and colonies in natural settings. In situ measurements in waters dominated by Microcystis blooms have previously detected extremely high backscattering ratios, i.e., b b /b>0.043 at 443 nm [1], the highest to our knowledge in the natural environment. These highb b /bvalues could hold promise as a diagnostic tool in identifying and monitoring Microcystis using optical approaches. However, it has been unclear how this type of optically ‘soft’ organic particle can generate such highb b /bvalues. In this study, the Multiple Sphere T-matrix (MSTM) model is used to calculate the IOPs of model colonies, including b b /b. Colony sizes in the model ranged from several cells to several hundred and both colony packing density and cell gas vacuole content were varied. Results are compared with model results for equivalent-volume spheres (EVS) and direct in situ measurements. Colony formation was required in the modeling to reproduce the high b b /bconsistent with in situ measurements. The combination of moderate to very dense colony (packing density >30%) and high gas vacuole content in individual cells (volume percentage >20%) was the most favorable condition leading to rapid increases in b b /bwith increasing number of cells N cell of the colony. Significant linear correlations were observed betweenb b /b and N c e l l 1 / 3 for these colonies, whereb b /b increased beyond 0.04 once cell number reached about 1000 cells in the case with the most densely packed cells and highest gas vacuole content. Within commonly observed colony sizes (N cell 6), colonies with high gas vacuole content exhibited b b /bvalues up to 0.055, consistent with direct measurements from Lake Erie. Polarized scattering was also of interest as a diagnostic tool, particularly with future Earth-orbiting polarimeters being deployed for the NASA Plankton, Aerosols, Cloud, ocean Ecosystem (PACE) mission. The Degree of Linear Polarization (DoLP), expressed by the ratio of two Mueller matrix elements−P12/P11, decreased with increasing colony cell number for Microcystis. Another ratio of two Mueller matrix elementsP22/P11, an index for nonsphericity, also decreased with increasing colony size. In addition to higher relative backscattering, greater colony packing density and larger gas vacuole sizes both led to lower DoLP peak magnitude and lowerP22/P11. An optical opposition feature due to constructive phase interference that was observed previously for cosmic dusts is also present for these modeled colonies, manifested by a narrow intensity peak and negative polarization dip near exact backscattering direction, gradually forming as colony size increases.

Remote sensing offers a potential tool for large scale environmental surveying and monitoring. However, remote observations of coral reefs are difficult especially due to the spatial and spectral complexity of the target compared to sensor specifications as well as the environmental implications of the water medium above. The development of sensors is driven by technological advances and the desired products. Currently, spaceborne systems are technologically limited to a choice between high spectral resolution and high spatial resolution, but not both. The current study explores the dilemma of whether future sensor design for marine monitoring should prioritise on improving their spatial or spectral resolution. To address this question, a spatially and spectrally resampled ground-level hyperspectral image was used to test two classification elements: (1) how the tradeoff between spatial and spectral resolutions affects classification; and (2) how a noise reduction by majority filter might improve classification accuracy. The studied reef, in the Gulf of Aqaba (Eilat), Israel, is heterogeneous and complex so the local substrate patches are generally finer than currently available imagery. Therefore, the tested spatial resolution was broadly divided into four scale categories from five millimeters to one meter. Spectral resolution resampling aimed to mimic currently available and forthcoming spaceborne sensors such as (1) Environmental Mapping and Analysis Program (EnMAP) that is characterized by 25 bands of 6.5 nm width; (2) VENμS with 12 narrow bands; and (3) the WorldView series with broadband multispectral resolution. Results suggest that spatial resolution should generally be prioritized for coral reef classification because the finer spatial scale tested (pixel size

Quantifying the number and type of benthic classes that are able to be spectrally identified in shallow water remote sensing is important in understanding its potential for habitat mapping. Factors that impact the effectiveness of shallow water habitat mapping include water column turbidity, depth, sensor and environmental noise, spectral resolution of the sensor and spectral variability of the benthic classes. In this paper, we present a simple hierarchical clustering method coupled with a shallow water forward model to generate water-column specific spectral libraries. This technique requires no prior decision on the number of classes to output: the resultant classes are optically separable above the spectral noise introduced by the sensor, image based radiometric corrections, the benthos’ natural spectral variability and the attenuating properties of a variable water column at depth. The modeling reveals the effect reducing the spectral resolution has on the number and type of classes that are optically distinct. We illustrate the potential of this clustering algorithm in an analysis of the conditions, including clustering accuracy, sensor spectral resolution and water column optical properties and depth that enabled the spectral distinction of the seagrass Amphibolis antartica from benthic algae.

The Sentinel-2A and 2B Multi-Spectral Instrument (MSI) offers a specification of potential value toward a number of objectives in remote sensing of coral reefs. Coral reefs represent a unique challenge for remote sensing, being highly heterogeneous at metre scales and occurring at variable depths and water clarity regimes. However, conservation initiatives, such as the United Nations Sustainable Development Goals, add urgency to the need for the large scale environmental monitoring information that remote sensing can provide. In the quest to meet this challenge a range of satellite instruments have been leveraged, from Landsat to high spatial resolution sensors such as WorldView-2, toward objectives such as: mapping of bottom types, bathymetry, change detection, and detection of coral bleaching events. Sentinel-2A and 2B offer a new paradigm of available instruments, with a 5-day revisit, 10 m multispectral spatial resolution and freely available data. Pre-launch simulation analyses by several of the authors suggested Sentinel-2 would have good performance for reef applications, in this paper we follow up on this study by reviewing the potential based on the substantial archive of actual data now available. First we determine to what extent the World's reefs are covered by Sentinel-2, since the mission requirements do not by default include all reefs. Secondly we review how a 5-day revisit translates to a usable acquisition rate of clear images, given that cloud and surface glint are common confounding factors. The usable acquisition rate is the real determinant of the objectives to which the data can be applied. Finally we apply current processing algorithms to Sentinel-2 data of several sites over the Great Barrier Reef, including physics-based bathymetry inversion and object-orientated benthic mapping. Landsat 8 OLI is most comparable current sensor to Sentinel-2 MSI, so direct comparisons and the possibilities for data synthesis are explored. Our findings confirm that Sentinel-2 has excellent performance for meeting several essential coral reef scientific and monitoring objectives. Taking into account cloud and sun glint, the usable acquisition rate for a large proportion of reefs is likely to be around 20 clear images a year on average, giving a new potential for evaluation of short time-scale disturbances and impacts. The spatial resolution of 10 m is a key threshold for delineating benthic features of interest such as coral structures, and there is evidence from image and field data that bleaching is detectable. Radiometrically Sentinel-2 data can support good results in physics-based methods, such as bathymetric mapping, comparable to Landsat 8 and WorldView-2. In addition the large scale acquisition area, provided by the 290 km wide swath, offers advantages over high spatial resolution imagery for mapping at multi-reef scales. Sentinel-2 data can be immediately leveraged with existing methods, to provide a new level of reef monitoring information compared to that previously available by remote sensing. Combined with Landsat 8 and the historical Landsat archive, the data collected today will be invaluable for decades or even centuries to come. In this context, the main downside of the Sentinel-2 mission is that approximately 12% of the World's reefs currently lie outside the acquisition plan and are not imaged. Surprisingly, for a European initiative, coral reefs in European governed territories are among the worst served globally. These omissions, approximately only 1/200th of the currently imaged area, limit the global scope which otherwise would be one of Sentinel-2's greatest strengths.

Gout is a painful disorder and is common in type 2 diabetes. Fenofibrate lowers uric acid and reduces gout attacks in small, short-term studies. Whether fenofibrate produces sustained reductions in uric acid and gout attacks is unknown.In the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial, participants aged 50-75 years with type 2 diabetes were randomly assigned to receive either co-micronised fenofibrate 200 mg once per day or matching placebo for a median of 5 years follow-up. We did a post-hoc analysis of recorded on-study gout attacks and plasma uric acid concentrations according to treatment allocation. The outcomes of this analysis were change in uric acid concentrations and risk of on-study gout attacks. The FIELD study is registered with ISRCTN, number ISRCTN64783481.Between Feb 23, 1998, and Nov 3, 2000, 9795 patients were randomly assigned to fenofibrate (n=4895) or placebo (n=4900) in the FIELD study. Uric acid concentrations fell by 20·2% (95% CI 19·9-20·5) during the 6-week active fenofibrate run-in period immediately pre-randomisation (a reduction of 0·06 mmol/L or 1 mg/dL) and remained -20·1% (18·5-21·7, p0·0001) lower in patients taking fenofibrate than in those on placebo in a random subset re-measured at 1 year. With placebo allocation, there were 151 (3%) first gout events over 5 years, compared with 81 (2%) among those allocated fenofibrate (HR with treatment 0·54, 95% CI 0·41-0·70; p0·0001). In the placebo group, the cumulative proportion of patients with first gout events was 7·7% in patients with baseline uric acid concentration higher than 0·36 mmol/L and 13·9% in those with baseline uric acid concentration higher than 0·42 mmol/L, compared with 3·4% and 5·7%, respectively, in the fenofibrate group. Risk reductions were similar among men and women and those with dyslipidaemia, on diuretics, and with elevated uric acid concentrations. For participants with elevated baseline uric acid concentrations despite taking allopurinol at study entry, there was no heterogeneity of the treatment effect of fenofibrate on gout risk. Taking account of all gout events, fenofibrate treatment halved the risk (HR 0·48, 95% CI 0·37-0·60; p0·0001) compared with placebo.Fenofibrate lowered uric acid concentrations by 20%, and almost halved first on-study gout events over 5 years of treatment. Fenofibrate could be a useful adjunct for preventing gout in diabetes.None.

In coastal regions, shallow water semi-analytical inversion algorithms may be used to derive geophysical parameters such as inherent optical properties (IOPs), water column depth, and bottom albedo coefficients by inverting sensor-derived sub-surface remote sensing reflectance, rrs. The uncertainties of these derived geophysical parameters due to instrumental and environmental noise can be estimated numerically via the addition of spectral noise to the sensor-derived rrs before inversion. Repeating this process multiple times allows the calculation of the standard error and average for each derived parameter. Apart from spectral non-uniqueness, the optimization algorithm employed in the inversion must converge onto a single minimum to obtain a true representation of the uncertainty for a given set of noise-perturbed rrs. Failure to do so inflates the uncertainty and affects the average retrieved value (accuracy). We show that the standard approach of seeding the optimization with an arbitrary, fixed initial guess, can lead to the convergence to multiple minima, each having substantially different centroids in multi-parameter solution space. We present the Update-Repeat Levenberg-Marquardt (UR-LM) and Latin Hypercube Sampling (LHS) routines that dynamically search the solution space for an optimal initial guess, that when applied to the optimization allows convergence to the best local minimum. We apply the UR-LM and LHS methods on HICO-derived and simulated rrs and demonstrate the improved computational efficiency, precision, and accuracy afforded from these methods compared with the standard approach. Conceptually, these methods are applicable to remote sensing based, shallow water or oceanic semi-analytical inversion algorithms requiring nonlinear least squares optimization.

Satellite, airborne, or platform-based remote sensing reflectance measurements of aquatic targets are frequently compromised by water-surface effects such as specular sun reflection glint or transient objects like buoys or boats. For temporal or spatial data series where sub-surface reflectance is of interest, the elimination of affected data may require time-consuming manual selection of spectra and substantial data loss. Here, we present a method for the automated elimination of data points containing surface objects or strong sun reflection, which is based on the spectral slope in the ultra-violet to blue 350 nm to 450 nm. To minimize data loss, an automated sun glint correction combining two previously published methods is also presented. The method operates by subtracting a glint spectrum by means of a regression curve characterized from low to medium glint data points and is further automated by selecting these low glint data on the basis of the oxygen absorption depth in the near infrared NIR. The elimination and correction algorithms facilitate rapid automated processing of large bio-optical data sets for both spatial and temporally resolved remote-sensing reflectance data sets. Here we demonstrate their efficacy on a three-month data set of hourly light field measurements from a fixed platform in the northwest Mediterranean.

The Sentinel 2 mission offers continuity of service for the moderate resolution multispectral SPOT XS and Landsat Thematic Mapper series sensors, but also offers several design improvements that may lead to enhanced capability in coral reef mapping applications. In this study modeling and simulated image analyses were conducted to evaluate the relative capability of the Sentinel 2 instrument design compared to SPOT-4 and Landsat ETM+, for mapping bathymetry and benthic composition, and for coral bleaching detection. The analyses involved propagating noise and environmental uncertainties through a radiative transfer model inversion to quantify uncertainty in retrievable parameters from each sensor. The experiment structure included factors for sensor-environmental noise, band choice, and complexity of benthic reflectance model. Results indicate that while variables related to reef ‘health’ such as coral mortality and algal cover cannot be mapped accurately by this class of instrument; Sentinel 2 does have improved ability for discrimination of reef benthic composition over SPOT-4 and Landsat ETM+. The key enabling design factors are the narrowness of bands, increased spatial resolution and additional band at 443 nm; instrument noise was a less significant factor. Rapid revisit times, global coverage, and freely available data suggest the potential for time series analyses. Sentinel 2 may also be capable of bleaching detection by change analysis given effective methods for precise cross-image image radiometric and spatial alignment.

Retrieval of operational optical products from the future Global Monitoring for Environment and Security (GMES) Sentinel-3 mission aims to provide continuity of existing missions delivering ocean/land colour, surface temperature and sea surface topography data. This paper describes the current status of the Sentinel-3 Level 2 Optical Prototype Processor (O-L2PP) whose development includes not only a list of products, but also associated uncertainty estimates—a key requirement for the processor. Examples of the approaches adopted within the Ocean and Land Colour Instrument (OLCI) processing module demonstrate how uncertainties can be estimated.

OBJECTIVE Diabetic patients with moderate renal impairment (estimated glomerular filtration rate [eGFR] 30–59 mL/min/1.73 m2) are at particular cardiovascular risk. Fenofibrate’s safety in these patients is an issue because it may elevate plasma creatinine. Furthermore, guidelines regarding fenofibrate dosing in renal impairment vary internationally. We investigated fenofibrate’s effects on cardiovascular and end-stage renal disease (ESRD) events, according to eGFR, in the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) Study. RESEARCH DESIGN AND METHODS Type 2 diabetic patients (aged 50–75 years) with eGFR ≥30 mL/min/1.73 m2 were randomly allocated to a fixed dose of fenofibrate (200 mg daily) (n = 4,895) or placebo (n = 4,900) for 5 years. Baseline renal function (Modification of Diet in Renal Disease equation) was grouped by eGFR (30–59, 60–89, and ≥90 mL/min/1.73 m2). The prespecified outcome was total cardiovascular events (composite of cardiovascular death, myocardial infarction, stroke, and coronary/carotid revascularization). Serious adverse events and instances of ESRD (plasma creatinine >400 μmol/L, dialysis, renal transplant, or renal death) were recorded. Analysis was by intention to treat. RESULTS Overall, fenofibrate reduced total cardiovascular events, compared with placebo (hazard ratio 0.89 [95% CI 0.80–0.99]; P = 0.035). This benefit was not statistically different across eGFR groupings (P = 0.2 for interaction) (eGFR 30–59 mL/min/1.73 m2: 0.68 [0.47–0.97], P = 0.035; eGFR ≥90 mL/min/1.73 m2: 0.85 [0.70–1.02], P = 0.08). ESRD rates were similar between treatment arms, without adverse safety signals of fenofibrate use in renal impairment. CONCLUSIONS Patients with type 2 diabetes and moderate renal impairment benefit from long-term fenofibrate, without excess drug-related safety concerns compared with those with no or mild renal impairment. Fenofibrate treatment should not be contraindicated in moderate renal impairment, suggesting that current guidelines may be too restrictive.

Maps of coral reef habitats are fundamental tools for reef management, and high map accuracy is desirable to support appropriate decisions, such as the stratification of marine reserves by habitat class. While satelite sensors have been used to map different reef communities, the accuracy of these maps tends to be low (overall accuracy

A simple method for efficient inversion of arbitrary radiative transfer models for image analysis is presented. The method operates by representing the shape of the function that maps model parameters to spectral reflectance by an adaptive look-up tree (ALUT) that evenly distributes the discretization error of tabulated reflectances in spectral space. A post-processing step organizes the data into a binary space partitioning tree that facilitates an efficient inversion search algorithm. In an example shallow water remote sensing application, the method performs faster than an implementation of previously published methodology and has the same accuracy in bathymetric retrievals. The method has no user configuration parameters requiring expert knowledge and minimizes the number of forward model runs required, making it highly suitable for routine operational implementation of image analysis methods. For the research community, straightforward and robust inversion allows research to focus on improving the radiative transfer models themselves without the added complication of devising an inversion strategy.

Sun glint, the specular reflection of light from water surfaces, is a serious confounding factor for remote sensing of water column properties and benthos. This paper reviews current techniques to estimate and remove the glint radiance component from imagery. Methods for processing of ocean color images use statistical sea surface models to predict the glint from the sun and sensor positions and wind data. Methods for higher resolution imaging, used in coastal and shallow water mapping, estimate the glint radiance from the near-infrared signal. The effects of some current methods are demonstrated and possibilities for future techniques are briefly addressed.

Numerous studies have been conducted to compare the classification accuracy of coral reef maps produced from satellite and aerial imagery with different sensor characteristics such as spatial or spectral resolution, or under different environmental conditions. However, in additional to these physical environment and sensor design factors, the ecologically determined spatial complexity of the reef itself presents significant challenges for remote sensing objectives. While previous studies have considered the spatial resolution of the sensors, none have directly drawn the link from sensor spatial resolution to the scale and patterns in the heterogeneity of reef benthos. In this paper, we will study how the accuracy of a commonly used maximum likelihood classification (MLC) algorithm is affected by spatial elements typical of a Caribbean atoll system present in high spectral and spatial resolution imagery. The results indicate that the degree to which ecologically determined spatial factors influence accuracy is dependent on both the amount of coral cover on the reef and the spatial resolution of the images being classified, and may be a contributing factor to the differences in the accuracies obtained for mapping reefs in different geographical locations. Differences in accuracy are also obtained due to the methods of pixel selection for training the maximum likelihood classification algorithm. With respect to estimation of live coral cover, a method which randomly selects training samples from all samples in each class provides better estimates for lower resolution images while a method biased to select the pixels with the highest substrate purity gave better estimations for higher resolution images.

Coral reefs are in decline worldwide and monitoring activities are important for assessing the impact of disturbance on reefs and tracking subsequent recovery or decline. Monitoring by field surveys provides accurate data but at highly localised scales and so is not cost-effective for reef scale monitoring at frequent time points. Remote sensing from satellites is an alternative and complementary approach. While remote sensing cannot provide the level of detail and accuracy at a single point than a field survey, the statistical power for inferring large scale patterns benefits in having complete areal coverage. This review considers the state of the art of coral reef remote sensing for the diverse range of objectives relevant for management, ranging from the composition of the reef: physical extent, benthic cover, bathymetry, rugosity; to environmental parameters: sea surface temperature, exposure, light, carbonate chemistry. In addition to updating previous reviews, here we also consider the capability to go beyond basic maps of habitats or environmental variables, to discuss concepts highly relevant to stakeholders, policy makers and public communication: such as biodiversity, environmental threat and ecosystem services. A clear conclusion of the review is that advances in both sensor technology and processing algorithms continue to drive forward remote sensing capability for coral reef mapping, particularly with respect to spatial resolution of maps, and synthesis across multiple data products. Both trends can be expected to continue.

Quantifying the beta diversity (species replacement along spatiotemporal gradients) of ecosystems is important for understanding and conserving patterns of biodiversity. However, virtually all studies of beta diversity focus on one-dimensional transects orientated along a specific environmental gradient that is defined a priori. By ignoring a second spatial dimension and the associated changes in species composition and environmental gradients, this approach may provide limited insight into the full pattern of beta diversity. Here, we use remotely sensed imagery to quantify beta diversity continuously, in two dimensions, and at multiple scales across an entire tropical marine seascape. We then show that beta diversity can be modeled (0.852 > or = r2 > or = 0.590) at spatial scales between 0.5 and 5.0 km2, using the environmental variables of mean and variance of depth and wave exposure. Beta diversity, quantified within a "window" of a given size, is positively correlated to the range of environmental conditions within that window. For example, beta diversity increases with increasing variance of depth. By analyzing such relationships across seascapes, this study provides a framework for a range of disparate coral reef literature including studies of zonation, diversity, and disturbance. Using supporting evidence from soft-bottom communities, we hypothesize that depth will be an important variable for modeling beta diversity in a range of marine systems. We discuss the implications of our results for the design of marine reserves.

In 1983, the dominant urchin of Caribbean coral reefs (Diadema antillarum) experienced massive disease-induced mortality and its functional extinction persists to this day. Concurrently, reports of coral disease, coral bleaching and nutrification began to appear and many Caribbean reefs have deteriorated in the last two decades. Here, we describe a spatial simulation model of physical and ecological processes occurring on a dominant Caribbean for reef habitat, often referred to as Montastraea reef. The model uses a square lattice to simulate the dynamics of two types of hard coral (a brooder and spawner), cropped algal substrata and macroalgae. Grazing occurs independently by Diadema and parrotfishes and influences the competitive interactions between corals and macroalgae. Four important types of disturbance are simulated: loss of the urchin Diadema, hurricanes, fishing of parrotfishes and nutrification. We use the model to revisit the impact of losing the keystone herbivore, Diadema. The urchin imparted great resilience to Caribbean reefs in the face of severe disturbances including: high hurricane frequencies (once per decade), overfishing of scarids and a range of nutrification levels, including a doubling of the vertical growth rate, vegetative growth rate and colonisation rate of macroalgae. Parrotfishes are able to compensate for the loss of this urchin under a limited range of physical and ecological conditions. When not exploited, parrotfishes allow coral to persist at least at equilibrial levels when hurricane frequencies drop to around once every 20 years (e.g. those found in Central America). However, coral cover declined under decadal hurricane frequencies which may partly explain observations in regions of intense hurricane activity such as Florida. Parrotfish grazing is sufficiently intense to mitigate nutrification impacts providing that the cover of corals is not heavily depleted by other processes such as hurricanes and disease. Indeed, the cover of living coral exhibits a strong interaction with both grazing and nutrification in determining the survival of coral recruits. Reefs of higher coral cover have greater

Specular reflection of solar radiation on non-flat water surfaces is a serious confounding factor for benthic remote sensing in shallow-water environments. This problem was recently overcome by Hochberg et al., who provided an effective method for the removal of 'sun glint' from remotely sensed images by utilization of the brightness in a near-infrared (NIR) band. Application of the technique was shown to give an increase in the accuracy of benthic habitat classification. However, as presented, the method is sensitive to outlier pixels, requires a time-consuming masking of land and cloud, and is not formulated in a manner leading to ease of implementation. We present a revised version of the method, which is more robust, does not require masking and can be implemented very simply. The practical approach described here will hopefully expedite the routine adoption of this effective and simple technique throughout the aquatic remote sensing community.

Hyperspectral remote sensing has shown promise for detailed discrimination of coral reef substratum types, but, by necessity, it samples at pixel scales larger than reef substratum patch sizes. Spectral unmixing techniques have been successful in resolving subpixel areal cover in terrestrial environments. However, the application of spectral unmixing on coral reefs is fundamentally challenging, due not only to the water column, but also to the potentially large number of spectrally similar and ecologically significant end-member (substratum) classes involved. A controlled ex-situ experiment was conducted using field-spectrometer data to assess the accuracy of spectral unmixing techniques to estimate the areal cover of small-scale ( 0.64, i.e. r >0.8). The most successful analyses were based on derivatives of down-sampled data, implying that spectral unmixing benefits more from spectral smoothing and judicious choice of band locations than from high spectral resolution per se. Although these results show that changes in coral and algal cover can be determined by unmixing their spectra, the method is not yet an operational remote sensing tool. Primary empirical research is needed before taking the next step, which is to incorporate a water column, of variable depth, above the sea bed.

A three-dimensional computer model of canopies of the seagrass Amphibolis griffithii was used to investigate the consequences of variations in canopy structure and benthic light environment on leaf-level photosynthetic saturation state. The model was constructed using empirical data of plant morphometrics from a previously conducted shading experiment and validated well to in-situ data on light attenuation in canopies of different densities. Using published values of the leaf-level saturating irradiance for photosynthesis, results show that the interaction of canopy density and canopy-scale photosynthetic response is complex and non-linear, due to the combination of self-shading and the non-linearity of photosynthesis versus irradiance (P-I) curves near saturating irradiance. Therefore studies of light limitation in seagrasses should consider variation in canopy structure and density. Based on empirical work, we propose a number of possible measures for canopy scale photosynthetic response that can be plotted to yield isoclines in the space of canopy density and light environment. These plots can be used to interpret the significance of canopy changes induced as a response to decreases in the benthic light environment: in some cases canopy thinning can lead to an equivalent leaf level light environment, in others physiological changes may also be required but these alone may be inadequate for canopy survival. By providing insight to these processes the methods developed here could be a valuable management tool for seagrass conservation during dredging or other coastal developments.

The intensity and location of Sun glint in two Medium Resolution Imaging Spectrometer (MERIS) images was modeled using a radiative transfer model that includes elevation features as well as the slope of the sea surface. The results are compared to estimates made using glint flagging and correction approaches used within standard atmospheric correction processing code. The model estimate gives a glint pattern with a similar width but lower peak level than any current method, or than that estimated by a radiative transfer model with surfaces that include slope but not height. The MERIS third reprocessing recently adopted a new slope statistics model for Sun glint correction; the results show that this model is an outlier with respect to both the elevation model and other slope statistics models and we recommend that its adoption should be reviewed.

The behavior of light at the air-sea interface has been investigated using ray tracing methods with numerically realized surfaces that incorporate features on scales from 3 millimeters to 200 meters. The directional reflection of light at the surface realizations was tested using Monte Carlo code. Estimated directionally reflected radiances were generally in good agreement with those from existing methods that model the slope statistics but not the shape of the sea surface. However, significant differences were found for some incident and exitant directions. The model was used to quantitatively estimate the pixel-to-pixel variation in ocean color images caused by spatial variation in the sea surface shape.

The shape of a spectroradiometer’s field of view (FOV) affects the way spectral measurements are acquired. Knowing this property is a prerequisite for the correct use of the spectrometer. If the substrate is heterogeneous, the ability to accurately know what is being measured depends on knowing the FOV location, shape, spectral and spatial sensitivity. The GER1500 is a hand-held spectrometer with a fixed lens light entry slit and has a laser guide that allows control over the target by positioning the entire unit. In the current study, the FOV of the GER1500 was mapped and analysed. The spectral and spatial non-uniformities of the FOV were examined and were found to be spectrally independent. The relationship between the FOV and the built-in laser guide was tested and found to have a linear displacement dependent on the distance to the target. This allows an accurate prediction of the actual FOV position. A correction method to improve the agreement between the expected and measured reflectance over heterogeneous targets was developed and validated. The methods described are applicable and may be of use with other hand-held spectroradiometers.

A geometric optical model for three-dimensional radiative transfer capable of handling arbitrary arrangements of surfaces within anisotropic scattering media is described. The model operates by discretizing surfaces and volumes into patches and voxels and establishing the radiative transfer relationship between every pair of elements. In a plane-parallel configuration results for directional radiance agree closely with the numerical integration invariant imbedded method. Model accuracy for two examples incorporating surface water waves and complex benthic structures were assessed by conservation of energy, errors were less than 1%. Potential applications in remote sensing or photobiological studies of structurally complex benthos in shallow water environments are illustrated.

Trends in coral cover are widely used to indi- cate the health of coral reefs but are costly to obtain from field survey over large areas. In situ studies of reflected spectra at the coral surface show that living and recently dead colonies can be distinguished. Here, we investigate whether such spectral differences can be detected using an airborne remote sensing instrument. The Compact Airborne Spectrographic Imager (Itres Research Ltd, Canada) was flown in two configurations: 10 spectral bands with 1-m 2 pixels and 6 spectral bands with 0.25-m 2 pixels. First, we show that an instrument with 10 spectral bands possesses adequate spectral res- olution to distinguish living Porites, living Pocillopora spp., partially dead Porites, recently dead Porites (total colony mortality within 6 months), old dead (>6 months) Porites, Halimeda spp., and coralline red algae when there is no water column to confuse spectra. All substrata were distinguished using fourth-order spectral derivatives around 538 nm and 562 nm. Then, at a shallow site (Tivaru) at Rangiroa Atoll, Tuamotu Archipelago (French Polynesia), we show that live and dead coral can be distinguished from the air to a depth of at least 4 m using first- and fourth-order spectral derivatives between 562-580 nm. However, partially dead and recently dead Poritescolonies could not be distinguished from an airborne platform. Spectral dif- ferences among substrata are then exploited to predict the cover of reef substrata in ten 25-m 2 plots at nearby Motu Nuhi (max depth 8 m). The actual cover in these plots was determined in situ using quadrats with a 0.01- m 2 grid. Considerable disparity occurred between field and image-based measures of substrate cover within individual 25-m 2 quadrats. At this small scale, disparity, measured as the absolute difference in cover between field and remote-sensing methods, reached 25% in some substrata but was always less than 10% for living coral (99% of which consisted of Porites spp.). At the scale of the reef (all ten 25-m 2 quadrats), however, disparities in percent cover between imagery and field data were less than 10% for all substrata and extremely low for some classes (e.g.

Coral reef communities face unprecedented pressures on local, regional and global scales as a consequence of climate change and anthropogenic disturbance. Optical remote sensing, from satellites or aircraft, is possibly the only means of measuring the effects of such stresses at appropriately large spatial scales (many thousands of square kilometres). To map key variables such as coral community structure, percentages of living coral or percentages of dead coral, a remote sensing instrument must be able to distinguish the reflectance spectra (i.e. "spectral signature", reflected light as a function of wavelength) of each category. For biotic classes, reflectance is a complex function of pigmentation, structure and morphology. Studies of coral "colour" fall into two disparate but potentially complementary types. Firstly, biological studies tend to investigate the structure and significance of pigmentation in reef organisms. These studies often lack details that would be useful from a remote sensing perspective such as intraspecific variation in pigment concentration or the contribution of fluorescence to reflectance. Secondly, remote sensing studies take empirical measurements of spectra and seek wavelengths that discriminate benthic categories. Benthic categories used in remote sensing sometimes consist of species groupings that are biologically or spectrally inappropriate (e.g. merging of algal phyla with distinct pigments). Here, we attempt to bridge the gap between biological and remote sensing perspectives of pigmentation in reef taxa. The aim is to assess the extent to which spectral discrimination can be given a biological foundation, to reduce the ad hoc nature of discriminatory criteria, and to understand the fundamental (biological) limitations in the spectral separability of biotic classes. Sources of pigmentation in reef biota are reviewed together with remote sensing studies where spectral discrimination has been effectively demonstrated between benthic categories. The basis of reflectance is considered as the sum of pigmented components, such as zooxanthellae, host tissues and skeletons of corals. Problems in the empirical in situ measurement of reflectance are identified, such as the differing types of reflectance which can be measured, the interaction of the light field with morphology, and depth-dependent variability of measured reflectance due to fluorescence. The latter is estimated in some cases to introduce an error of up to 20% when depth differs by 8 m. Spectral features useful in discriminating reef benthos are identified and related to pigmentation. The slope in the reflectance spectra between 650 and 690 nm is dependent on chlorophyll-a concentration and can be used to discriminate bare sand with no algal component from chlorophyll-a containing benthos (algae, corals). The slope in reflectance at various locations between 500 and 560 nm can be useful in discriminating bleached and unbleached corals, possibly due to reduced peridinin concentration. Rhodophyta may be discernible by the presence of a dip in reflectance at 570 nm, due to a phycoerythrin absorption peak. However, the utility of some discriminatory criteria in deeper waters is mitigated by the relatively poor transmission of light through water at longer wavelengths (especially600 nm). Contrary to suggested categorizations of fluorescent pigments in coral host tissues, it is shown that these pigments form an almost continuous distribution with respect to their excitation and emission peaks. Remote sensing by induced fluorescence is a promising approach, but further details about the variation and distribution of these pigments are required. It is hoped that this review will promote cross-disciplinary collaboration between pigment biologists and the reef remote sensing community. Where possible, the discriminative criteria adopted in remote sensing should be related to biological phenomena, thus lending an intuitive, process-orientated basis for interpreting spectral data. Similarly, remote sensing may provide a novel scaling perspective to biological studies of pigmentation in reef organisms.

Coral reef communities face unprecedented pressures on local, regional and global scales as a consequence of climate change and anthropogenic disturbance. Optical remote sensing, from satellites or aircraft, is possibly the only means of measuring the effects of such stresses at appropriately large spatial scales (many thousands of square kilometres). To map key variables such as coral community structure, percentages of living coral or percentages of dead coral, a remote sensing instrument must be able to distinguish the reflectance spectra (i.e. "spectral signature", reflected light as a function of wavelength) of each category. For biotic classes, reflectance is a complex function of pigmentation, structure and morphology. Studies of coral "colour" fall into two disparate but potentially complementary types. Firstly, biological studies tend to investigate the structure and significance of pigmentation in reef organisms. These studies often lack details that would be useful from a remote sensing perspective such as intraspecific variation in pigment concentration or the contribution of fluorescence to reflectance. Secondly, remote sensing studies take empirical measurements of spectra and seek wavelengths that discriminate benthic categories. Benthic categories used in remote sensing sometimes consist of species groupings that are biologically or spectrally inappropriate (e.g. merging of algal phyla with distinct pigments). Here, we attempt to bridge the gap between biological and remote sensing perspectives of pigmentation in reef taxa. The aim is to assess the extent to which spectral discrimination can be given a biological foundation, to reduce the ad hoc nature of discriminatory criteria, and to understand the fundamental (biological) limitations in the spectral separability of biotic classes. Sources of pigmentation in reef biota are reviewed together with remote sensing studies where spectral discrimination has been effectively demonstrated between benthic categories. The basis of reflectance is considered as the sum of pigmented components, such as zooxanthellae, host tissues and skeletons of corals. Problems in the empirical in situ measurement of reflectance are identified, such as the differing types of reflectance which can be measured, the interaction of the light field with morphology, and depth-dependent variability of measured reflectance due to fluorescence. The latter is estimated in some cases to introduce an error of up to 20% when depth differs by 8 m. Spectral features useful in discriminating reef benthos are identified and related to pigmentation. The slope in the reflectance spectra between 650 and 690 nm is dependent on chlorophyll-a concentration and can be used to discriminate bare sand with no algal component from chlorophyll-a containing benthos (algae, corals). The slope in reflectance at various locations between 500 and 560 nm can be useful in discriminating bleached and unbleached corals, possibly due to reduced peridinin concentration. Rhodophyta may be discernible by the presence of a dip in reflectance at 570 nm, due to a phycoerythrin absorption peak. However, the utility of some discriminatory criteria in deeper waters is mitigated by the relatively poor transmission of light through water at longer wavelengths (especially > 600 nm). Contrary to suggested categorizations of fluorescent pigments in coral host tissues, it is shown that these pigments form an almost continuous distribution with respect to their excitation and emission peaks. Remote sensing by induced fluorescence is a promising approach, but further details about the variation and distribution of these pigments are required. It is hoped that this review will promote cross-disciplinary collaboration between pigment biologists and the reef remote sensing community. Where possible, the discriminative criteria adopted in remote sensing should be related to biological phenomena, thus lending an intuitive, process-orientated basis for interpreting spectral data. Similarly, remote sensing may provide a novel scaling perspective to biological studies of pigmentation in reef organisms.

A fast graphics processing unit implementation of the finite-difference time-domain model was used to determine the computational effort required to accurately characterize the mean scattering functions of randomly orientated aspherical particles. The influence of the number of randomized rotational positions on the accuracy of the mean scattering phase function curve was appraised. In general, multiplying the number of orientations by 100 gives increased accuracy of factor 10. Dependent on particle shape, certain regions of the phase function were insensitive to particle orientation. In addition, an error in a key previous publication on scattering by aspherical particles was identified.

Almost three-quarters of the world's coral reefs are thought to be deteriorating as a consequence of environmental stress. Until now, it has been possible to evaluate reef health only by field survey, which is labour-intensive and time-consuming. Here we map live coral cover from the air by remote imaging, a technique that will enable the state of shallow reefs to be monitored swiftly and over large areas.

The National Oceanic and Atmospheric Administration’s Coral Reef Watch program developed and operates several global satellite products to monitor bleaching-level heat stress. While these products have a proven ability to predict the onset of most mass coral bleaching events, they occasionally miss events; inaccurately predict the severity of some mass coral bleaching events; or report false alarms. These products are based solely on temperature and yet coral bleaching is known to result from both temperature and light stress. This study presents a novel methodology (still under development), which combines temperature and light into a single measure of stress to predict the onset and severity of mass coral bleaching. We describe here the biological basis of the Light Stress Damage (LSD) algorithm under development. Then by using empirical relationships derived in separate experiments conducted in mesocosm facilities in the Mexican Caribbean we parameterize the LSD algorithm and demonstrate that it is able to describe three past bleaching events from the Great Barrier Reef (GBR). For this limited example, the LSD algorithm was able to better predict differences in the severity of the three past GBR bleaching events, quantifying the contribution of light to reduce or exacerbate the impact of heat stress. The new Light Stress Damage algorithm we present here is potentially a significant step forward in the evolution of satellite-based bleaching products.