Spectral reflectance of coral reef bottom-types worldwide and implications for coral reef remote sensing

Coral reef benthic communities are mosaics of individual bottom-types that are distinguished by their taxonomic composition and functional roles in the ecosystem. Knowledge of community structure is essential to understanding many reef processes. To develop techniques for identification and mapping of reef bottom-types using remote sensing, we measured 13,100 in situ optical reflectance spectra (400-700 nm, 1-nm intervals) of 12 basic reef bottom-types in the Atlantic, Pacific, and Indian Oceans: fleshy (1) brown, (2) green, and (3) red algae; non-fleshy (4) encrusting calcareous and (5) turf algae; (6) bleached, (7) blue, and (8) brown hermatypic coral; (9) soft/gorgonian coral; (10) seagrass; (11) terrigenous mud; and (12) carbonate sand. Each bottom-type exhibits characteristic spectral reflectance features that are conservative across biogeographic regions. Most notable are the brightness of carbonate sand and local extrema near 570 nm in blue (minimum) and brown (maximum) corals. Classification function analyses for the 12 bottom-types achieve mean accuracies of 83%, 76%, and 71% for full-spectrum data (301-wavelength), 52-wavelength, and 14-wavelength subsets, respectively. The distinguishing spectral features for the 12 bottom-types exist in well-defined, narrow (10-20 nm) wavelength ranges and are ubiquitous throughout the world. We reason that spectral reflectance features arise primarily as a result of spectral absorption processes. Radiative transfer modeling shows that in typically clear coral reef waters, dark substrates such as corals have a depth-of-detection limit on the order of 10-20 m. Our results provide the foundation for design of a sensor with the purpose of assessing the global status of coral reefs.     

An evaluation of Landsat Thematic Mapper (TM) digital data for discriminating coral reef zonation: Heron Reef (GBR)

Coral reefs exhibit patterns of zonation. In this study we have evaluated the usefulness of Landsat-TM digital data as a tool for discrimination and mapping of reef zones. Classification, on bands 1, 2 and 3, and grouping of classes into reef zones was carried out with the aid of canonical variate analysis and minimum spanning trees. Thirteen reef zones can be identified and mapped, at a spatial scale relevant to their dimensions, with confidence. These zones can be further subdivided and mapped as spatially coherent subzones, in order to provide detailed information regarding the density of coral cover on the reef flat. In addition, the canonical variate analysis provides the basis for the aggregation of classes into sub-zones on interpreted primary productivity gradients, which is of relevance to coral reef management, monitoring and research.     

Spectral,spatial and temporal characteristics of Arctic tundra reflectance

Abstract

The objective was to quantify and analyse the spectral, spatial and temporal variability of solar radiation reflected from arctic tundra vegetation at a study site in the Brooks Range foothills of northern Alaska. Spectral radiance data from hand-held radiometers and the SPOT HRV sensor were sampled along hillslope transects (toposequences) and within four vegetation community types. The spatial trend of normalised difference vegetation index (NDVI) along the toposequences corresponded to variations in the abundance of green vegetation matter and in vegetation composition. A marked temporal increase in the NDVI occurred along the toposequences from the beginning of the growing season (mid-June) to peak green up (end of July). The spectral signatures of three tundra dominant vegetation communities, dry heath, moist tussock and wet sedge, were moderately separable, with dry heath being most separable. The overall separability of the major community types was similar at all times during the growing season, with the most divergent signatures occurring in late July during maximum greenness. Some of the important ecological features of the arctic tundra landscape are not resolved by the SPOT HRV sensor in multi-spectral mode, in spite of its high (20 m) spatial resolution.     

Remote-sensing reflectance and true colour produced by a coupled hydrodynamic,optical, sediment,biogeochemical model of the Great Barrier Reef,Australia: Comparison with satellite data

Aquatic biogeochemical models are vital tools in understanding and predicting human impacts on water clarity. In this paper, we develop a spectrally-resolved optical model that produces remote-sensing reflectance as a function of depth-resolved biogeochemical model properties such as phytoplankton biomass, suspended sediment concentrations and benthic reflectance. We compare simulated remote-sensing reflectance from a 4 km resolution coupled hydrodynamic, optical, sediment and biogeochemical model configured for the Great Barrier Reef with observed remote-sensing reflectance from the MODIS sensor at the 8 ocean colour bands. The optical model is sufficiently accurate to capture the remote-sensing reflectance that would arise from a specific biogeochemical state. Thus the mismatch between simulated and observed remote-sensing reflectance provides an excellent metric for model assessment of the coupled biogeochemical model. Finally, we combine simulated remote-sensing reflectance in a red/green/blue colour model to produce simulated true colour images during the passage of Tropical Cyclone Yasi in February 2011.     

Spectral reflectance of dehydrating leaves: Measurements and modelling

Remotely sensed measurements at optical wavelengths may provide information on crop water status and increase the accuracy of crop production forecasts. Previous research has shown that canopy spectral response to water stress is attributable to change in leaf water content, canopy structure and soil moisture. This experiment was designed to study leaf spectral response resulting from changes in leaf water content and to evaluate the use of a radiative transfer model for predicting the spectral behaviour of the leaf. The difference between measured and modelled reflectance increased as leaf water content decreased and it was hypothesized that this may be due to a change in leaf internal structure that was unaccounted for by the model.     

Satellite observations of circulation in the southern Great Barrier Reef,Australia

Twenty-one NOAA-9 AVHRR satellite images of the southern Great Barrier Reef, spanning the period from June 1986 to September 1988, were examined for sea surface temperature patterns in order to trace circulation within this bathymetrically complex area. Our findings are in general agreement with the few field studies of this region. The East Australian Current tended to flow outside the reefs along the shelf break until it entered the Capricorn Channel, where it either meandered westward along the narrowing shelf, adhering closely to the slope contours, or flowed directly southward. It then impinged upon the shelf break, near Fraser Island, where it bifurcated to produce a southward continuation of the current, and a cyclonic eddy within the Capricorn Channel. Cool water, which commonly occurred over the shelf between Fraser Island and Cape Clinton, has probable significance for biological production within the adjacent Capricorn/Bunker Reefs of the Great Barrier Reef Marine Park. Interpreted as a response to upwelling, this cool water may be the result of: I. the combined effect of tidal pumping and coastal trapped waves; 2. effects of the longshore wind component; or 3. topographically-induced upwelling of slope waters due to flow of the East Australian Current along the continental shelf break. The evidence for each of these possible factors is discussed.     

Spectral unmixing of multiple lichen species and underlying substrate

Cryptogamic covers are a wide range of photoautotrophic plants which synthesize their own food while using sunlight as an energy source. Globally, cryptogrammic covers (such as cyanobacteria, algae, fungi, lichens, and bryophytes) annually uptake about 7% of the net primary production of terrestrial vegetation and account for about half of annual biological terrestrial nitrogen fixation. On the basis of these contributions to global carbon and nitrogen cycling, it is crucial to be able to accurately monitor seasonal and regional patterns of cryptogamic cover distribution and abundance. However, lichen-encrusted rock seldom comprises 100% of the ground cover within a pixel of remote-sensed imagery, and thereby arise challenges in lichen mapping and monitoring. Here we explore spectroscopic methods and spectral mixture analysis (SMA) to overcome the challenges of reflectance spectroscopy-based optical remote sensing detection and characterization of crustose lichen species. One suite of discrete wavelengths (λ₁ = {400, 470, 520, 570, 680, 800, 1080, 1120, 1200, 1300, 1470, 1670, 1750, 2132, 2198, 2232 nm}) and two wavelength regions (λ₂ = {λ: 800 nm ≤ λ ≤ 1300 nm} and λ₃ = {λ: 2000 nm ≤ λ ≤ 2400 nm}) were investigated for their ability to discriminate between substrate and different lichen species. We found that the spectral region 800–1300 nm performed best at lichen-substrate differentiation and interspecial lichen differentiation. Furthermore, measures of central tendency from multiple wavelength regions are superior to most individual wavelength regions, particularly for lichen-rock unmixing.     

Spectral reflectance of partly transmitting leaves: Laboratory measurements and mathematical modeling

Previous work related to remote sensing of natural sceneries has shown that the near infrared signature of a plant canopy is a combined function of leaf optical properties, canopy geometry, and soil reflectance. This paper deals with the problems involved in spectrophotometric measurements of leaves that are partly transmitting and partly reflecting, and thus influenced by the sample background provided by the measuring instrument. A mathematical model requiring only single-leaf spectral reflectance data as input is developed for prediction of multiple-leaf reflectance. The validity of the model appears to be adequate for any number of stacked leaves, when leaf-to-leaf variations caused by differences in water content and pigmentation are considered.     

The effects of ecologically determined spatial complexity on the classification accuracy of simulated coral reef images

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.     

Spectral reflectance response of Fraxinus mandshurica leaves to above- and belowground competition

The responses of leaf spectral reflectance of Fraxinus mandshurica saplings to above- and belowground competition were studied under field conditions in a temperate forest near the Changbai Mountain Nature Reserve in northeast China. Two sets of four treatments, each inducing different levels of competition, were applied under the shade of the forest canopy and in a clear felling area under full light exposure. The heights of the saplings were measured once a month and leaf reflectance was measured at the same time. At the end of the experiment, all target saplings were excavated, and their biomass and root morphological traits were analysed. All these traits were then compared with the leaf spectral reflectance values and different spectral indices. We found that changes in height and biomass were significantly affected by the treatment and site, and that the differences between the four treatments coincided well with the differences in the spectral indices. The final biomass and all root morphological attributes were significantly affected by the treatment and site. Again, these differences corresponded well with the differences in the spectral indices and the spectral reflectance curves. In conclusion, we found that leaf spectral reflectance was sensitive to competition and showed a close relation with other responses, which makes it a reliable indicator of the response of F. mandshurica to varying competition intensities, especially when competition is very severe.     

Detection limits of coral reef bleaching by satellite remote sensing: Simulation and data analysis

Monitoring of coral reef bleaching has hitherto been based on regional-scale, in situ data. Larger-scale trends, however, must be determined using satellite-based observations. Using both a radiative transfer simulation and an analysis of multitemporal Landsat TM images, the ability of satellite remote sensing to detect and monitor coral reef bleaching is examined. The radiative transfer simulation indicates that the blue and green bands of Landsat TM can detect bleaching if at least 23% of the coral surface in a pixel has been bleached, assuming a Landsat TM pixel with a resolution of 30×30 m on shallow (less than 3 m deep) reef flats at Ishigaki Island, Japan. Assuming an area with an initial coral coverage of 100% and in which all corals became completely bleached, the bleaching could be detected at a depth of up to 17 m. The difference in reflectance of shallow sand and corals is compared by examining multitemporal Landsat TM images at Ishigaki Island, after normalizing for variations in atmospheric conditions, incident light, water depth, and the sensor's reaction to the radiance received. After the normalization, a severe bleaching event when 25-55% of coral coverage was bleached was detected, but a slight bleaching event when 15% of coral coverage was bleached was not detected. The simulation and data analysis agreed well with each other, and identified reliable limits for satellite remote sensing for detecting coral reef bleaching. Sensitivity analysis on solar zenith angle, aerosol (visibility) and water quality (Chl a concentration) quantified the effect of these factors on bleaching detection, and thus served as general guidelines for detecting coral reef bleaching. Spatial misregistration resulted in a high degree of uncertainty in the detection of changes at the edges of coral patches mainly because of the low (∼30 m) spatial resolution of Landsat TM, indicating that detection of coral reef bleaching by Landsat TM is limited to extremely severe cases on a large homogeneous coral patch and shallow water depths. Satellite remote sensing of coral reef bleaching should be encouraged, however, because the development and deployment of advanced satellite sensors with high spatial resolution continue to progress.     

Spectral discrimination of dolerite in crushed rock road aggregate,Perth, Western Australia

Reflectance spectroscopic analysis, covering the visible to short‐wave infrared wavelength range (400 to 2500 nm), was tested on 56 light granite, dark granite and dolerite chips that typically comprise crushed rock aggregate quarried for use as road‐surfacing within the Perth, Western Australia (WA) metropolitan area. The technique was evaluated as a means of identifying and quantifying the proportion of dolerite within a bulk sample of granitic road aggregate. The ratio of the absorption depth at 2350 nm to the absorption depth at 2200 nm, for log‐space difference spectra (R2350 : 2200), successfully identified and discriminated with 100% accuracy all dolerite versus granitic rock chips tested. It is recommended that reflectance spectroscopy replace the current testing methodology (Colour of Aggregate Test) as the standard method of quantifying dolerite content in road surface aggregate.     

Airborne lidar sensing of massive stony coral colonies on patch reefs in the northern Florida reef tract

In this study we examined the ability of the NASA Experimental Advanced Airborne Research Lidar (EAARL) to discriminate cluster zones of massive stony coral colonies on northern Florida reef tract (NFRT) patch reefs based on their topographic complexity (rugosity). Spatially dense EAARL laser submarine topographic soundings acquired in August 2002 were used to create a 1-m resolution digital rugosity map for adjacent NFRT study areas characterized by patch reefs (Region A) and diverse substratums (Region B). In both regions, sites with lidar-sensed rugosities above 1.2 were imaged by an along-track underwater videography system that incorporated the acquisition of instantaneous GPS positions. Subsequent manual interpretation of videotape segments was performed to identify substratum types that caused elevated lidar-sensed rugosity. Our study determined that massive coral colony formation, modified by subsequent physical and biological processes that breakdown patch reef framework, was the primary source of topographic complexity sensed by the EAARL in the NFRT. Sites recognized by lidar scanning to be topographically complex preferentially occurred around the margins of patch reefs, constituted a minor fraction of the reef system, and usually reflected the presence of massive coral colonies in cluster zones, or their derivatives created by mortality, bioerosion, and physical breakdown.     

High-resolution ground verification,cluster analysis and optical model of reef substrate coverage on Landsat TM imagery (Red Sea,Egypt)

A combination of high-resolution ground verification, cluster analysis using Landsat Thematic Mapper (TM) data, and optical modelling, was applied to Red Sea reef substrate. Ground verification, in an area of 3 by 20 pixels (90 by 600 m) with one metre scale resolution, identified the presence of 30 different bottom types that were later reduced to twelve dominant bottom types. A combination of bispectral plots and principal component analysis using spectral bands 1, 2 and 3 confirmed the presence of nine bottom types. The identified clusters were separated and used as a training set to classify substrate. Optical modelling, using literature radiance values and coverage of the original twelve dominant bottom types and a simple model for atmospheric and water column absorption, revealed a difference of up to 60 W m -2 between predicted substrate radiance and the satellite sensor values in the reef top area. Considering the simple atmospheric correction model, the lack of in situ radiance measurements and the uncertainties with respect to possible changes in bottom type distribution since the acquisition of the 14 year old image, the results show the potential use of satellite imagery for reef research in both biological and geological analysis through very precise and semi-quantitative ground verification, including in situ reflectance measurements.     

Comparative evaluation of airborne LiDAR and ship-based multibeam SoNAR bathymetry and intensity for mapping coral reef ecosystems

Large areas of the world's coastal marine environments remain poorly characterized because they have not been mapped with sufficient accuracy and at spatial resolutions high enough to support a wide range of societal needs. Expediting the rate of seafloor mapping requires the collection of multi-use datasets that concurrently address hydrographic charting needs and support decision-making in ecosystem-based management. While active optical and acoustic sensors have previously been compared for the purpose of hydrographic charting, few studies have evaluated the performance and cost effectiveness of these systems for providing benthic habitat maps. Bathymetric and intensity data were collected in shallow water (< 50 m depth) coral reef ecosystems using two conventional remote sensing technologies: (1) airborne Light Detection and Ranging (LiDAR), and (2) ship-based multibeam (MBES) Sound Navigation and Ranging (SoNAR). A comparative assessment using a suite of twelve metrics demonstrated that LiDAR and MBES were equally capable of discriminating seafloor topography (r = > 0.9), although LiDAR depths were found to be consistently shallower than MBES depths. The intensity datasets were not significantly correlated at a broad 4 × 5 km spatial scale (r = − 0.11), but were moderately correlated in flat areas at a fine 4 × 500 m spatial scale (r = 0.51), indicating that the LiDAR intensity algorithm needs to be improved before LiDAR intensity surfaces can be used for habitat mapping. LiDAR cost 6.6% less than MBES and required 40 fewer hours to map the same study area. MBES provided more detail about the seafloor by fully ensonifying high-relief features, by differentiating between fine and coarse sediments and by collecting data with higher spatial resolutions. Surface fractal dimensions and fast Fourier transformations emerged as useful methods for detecting artifacts in the datasets. Overall, LiDAR provided a more cost effective alternative to MBES for mapping and monitoring shallow water coral reef ecosystems (< 50 m depth), although the unique advantages of MBES may make it a more appropriate choice for answering certain ecological or geological questions requiring very high resolution data.     

Multiple time-scale diffusion models of starfish and coral state changes over the whole great barrier reef

A model is developed to investigate starfish and coral dynamics at the macro-scale of the whole Great Barrier Reef. This stochastic near-equilibrium theory is consistent with all available data for the mean rates of change of reef-state relative to abundances of the starfishAcanthaster planci and the scleractinian corals upon which it preys. This result is in striking contrast to the stably cyclic behaviour which dominates the meso-scale of individual reefs as reported previously by the authors. For the first time, a number of important numerical estimates have been made and are reported here. Generally, the starfish dynamics is dominated by randomness, being indistinguishable from Brownian motion in the state-space. On the other hand, the coral process is embedded in a drift field which is always directed towards the low coral state. In fact, the high coral state is inaccessible on the Great Barrier Reef.     

The importance of coastal altimetry retracking and detiding: a case study around the Great Barrier Reef,Australia

A new approach for improving the accuracy of altimetry-derived sea level anomalies (SLAs) near the coast is presented. Estimation of SLAs is optimized using optimal waveform retracking through a fuzzy multiple retracking system and the most appropriate detiding method. With the retracking system, fuzzy-retracked SLAs become available within 5 km of the coast; meanwhile it becomes more important to use pointwise tide modelling rather than state-of-the-art global tidal models, as the latter leave residual ocean tide signals in retracked SLAs. These improvements are demonstrated for Jason-2 waveforms in the area of the Great Barrier Reef, Australia. Comparing the retrieved SLAs with in situ tide gauge data from Townsville and Bundaberg stations showed that the SLAs from this study generally outperform those from conventional methods, demonstrating that adequate waveform retracking and detiding are equally important in bringing altimetry SLAs closer to the coast.     

Spectral unmixing of normalized reflectance data for the deconvolution of lichen and rock mixtures

In subarctic regions the ubiquitous presence of rock encrusting lichens compromises the ability to map the reflectance signatures of minerals from imaging spectrometer data. The use of lichen as an endmember in spectral mixture analysis (SMA) may overcome these limitations. Because lichens rarely completely occupy the Instantaneous Field of View (IFOV), it is difficult to define a lichen endmember from an image using visual or automated endmember extraction tools. Spectral similarity of various crustose/foliose lichen species in the short wave infrared (SWIR) suggests that spectral unmixing of rock and lichens may be successfully accomplished using a single lichen endmember for this spectral range. We report the use of a spectral normalization method to minimize differences in SWIR reflectance between five lichen species (U. torrefacta, R. bolanderi, R. geminatum, R. geographicum, A. cinerea). When the normalization is applied to reflectance spectra from 2000-2400 nm acquired for a lichen encrusted quartzite rock sample we show that only a single lichen endmember is required to account for the lichen contribution in the observed mixtures. In contrast, two such endmembers are required when the normalization is not applied to the reflectance data. We illustrate this point using examples where endmembers are extracted manually and automatically, and compare the SMA results against abundances estimated from digital photography. For both the reflectance and normalized reflectance data, SMA results correlate well (R²>0.9) with abundances estimated from digital photography. The use of normalized reflectance implies that any field/laboratory lichen spectrum can be selected as the lichen endmember for SMA of airborne/spaceborne imagery.     

A comprehensive evaluation of classification algorithms for coral reef habitat mapping: challenges related to quantity,quality, and impurity of training samples

The preparation of control data is a primary concern in many supervised classification schemes. In coral reef mapping, this issue becomes more severe for three reasons: (1) control samples, located beneath the water, are quite difficult and costly to access; (2) because of the high spatial variability of coral reef habitats, it is very difficult to obtain high-quality samples; and (3) pure training samples are also hardly achievable. These issues, namely quantity, quality, and impurity challenges, are the main focus of this study. Three classification algorithms, including Maximum Likelihood Classifier (MLC), Artificial Neural Networks (ANNs), and Support Vector Machines (SVMs), are comprehensively evaluated, and their requirements for control data are determined. To accomplish this, rich field data, collected from diving off of Lizard Island in eastern Australia, and Landsat-8 images are used as the input data. With respect to accuracy, ANN is best, as it can deal with the complexity of coral reef environments; however, it requires a higher number of training samples (i.e. ANN cannot manage the quantity challenge). On the other hand, SVM shows the best resistance against the quantity and impurity challenges. Being aware of these points, a coral reef map is produced, for the first time, of the northern Persian Gulf, a coral habitat with very special environmental conditions. In this region, SVM achieved 68.42% overall accuracy, even though a very limited field work campaign was conducted to provide the control data.     

Detecting end-member structural and biological elements of a coral reef using a single-beam acoustic ground discrimination system

A thematic map of benthic habitat was produced for a coral reef in the Republic of Palau, utilizing hydroacoustic data acquired with a BioSonics DT-X echosounder and a single-beam 418 kHz digital transducer. This article describes and assesses a supervised classification scheme that used a series of three discriminant analyses (DAs) to refine training samples into end-member structural and biological elements utilizing E1′ (leading edge of first echo), E1 (trailing edge of first echo), E2 (complete second echo), fractal dimension (first echo shape) and depth as predictor variables. Hydroacoustic training samples were assigned to one of six predefined groups based on the plurality of benthic elements (sand, sparse submerged aquatic vegetation (SAV)) rubble, pavement, rugose hardbottom, branching coral) that were visually estimated from spatially co-located ground-truthing videos. Records that classified incorrectly or failed to exceed a minimum probability of group membership were removed from the training data set until only ‘pure’ end-member records remained. This refinement of ‘mixed’ training samples circumvented the dilemma typically imposed by the benthic heterogeneity of coral reefs, that is either train the acoustic ground discrimination system (AGDS) on homogeneous benthos and leave the heterogeneous benthos unclassified, or attempt to capture the many ‘mixed’ classes and overwhelm the discriminatory capability of the AGDS. It was made possible by a conjunction of narrow beam width (6.4°) and shallow depth (1.2 to 17.5 m), which produced a sonar footprint small enough to resolve the microscale features used to define benthic groups. Survey data classified from the third-pass training DA were found to: (i) conform to visually apparent contours of satellite imagery, (ii) agree with the structural and biological delineations of a benthic habitat map (BHM) created from visual interpretation of IKONOS imagery and (iii) yield values of benthic cover that agreed closely with independent, contemporaneous video transects. The methodology was proven on a coral reef environment for which high-quality satellite imagery existed, as an example of the potential for single-beam systems to thematically map coral reefs in deep or turbid settings where optical methods are not applicable.