Evanthia Karpouzli

The empirical line method for the atmospheric correction of IKONOS imagery

The empirical line method is an atmospheric correction technique that provides an alternative to radiative transfer modelling approaches. It offers a relatively simple means of surface reflectance calibration, providing that a series of invariant-in-time calibration target measurements are available. This technique has been applied with variable success to both airborne data and coarser spatial resolution satellite sensor data. However, with the advent of higher spatial resolution space-borne sensors there is a need to re-evaluate its potential. The empirical line method was tested for correcting multispectral IKONOS imagery acquired over the tropical island of San Andres, Colombia. The high spatial resolution (4 m) of the data made it possible to identify a number of homogeneous targets with a range of reflectances that were used for the calibration. Coefficients of determination of the prediction equations observed were large, ranging from 0.96-0.99 for each of the four wavebands. An accuracy assessment was performed using a set of independent targets. It demonstrated that the empirical line method can be applied to correct such imagery with accurate results.

Hyperspectral discrimination of coral reef benthic communities in the western Caribbean

Determining a subset of wavelengths that best discriminates reef benthic habitats and their associated communities is essential for the development of remote sensing techniques to monitor them. This study measured spectral reflectance from 17 species of western Caribbean reef biota including coral, algae, seagrasses, and sediments, as well as healthy and diseased coral. It sought to extend the spectral library of reef-associated species found in the literature and to test the spectral discrimination of a hierarchy of habitats, community groups, and species. We compared results from hyperspectral reflectance and derivative datasets to those simulated for the three visible multispectral wavebands of the IKONOS sensor. The best discriminating subset of wavelengths was identified by multivariate stepwise selection procedure (discriminant function analysis). Best discrimination at all levels was obtained using the derivative dataset based on 6–15 non-contiguous wavebands depending on the level of the classification, followed by the hyperspectral reflectance dataset which was based on as few as 2–4 non-contiguous wavebands. IKONOS wavebands performed worst. The best discriminating subset of wavelengths in the three classification resolutions, and particularly those of the medium resolution, was in agreement with those identified by Hochberg and Atkinson (2003) and Hochberg et al. (2003) for reef communities worldwide. At all levels of classification, reflectance wavebands selected by the analysis were similar to those reported in recent studies carried out elsewhere, confirming their applicability in different biogeographical regions. However the greater accuracies achieved using the derivative datasets suggests that hyperspectral data is required for the most accurate classification of reef biotic systems.

Remote Sensing of Seagrass Ecosystems: Use of Spaceborne and Airborne Sensors

The focus of this chapter lies in describing digi-tal multispectral and hyperspectral remote sensingdevelopments and applications in the mapping andmonitoring of seagrass ecosystems. Multispectralrefers to a sensor that registers light in a limitednumber of relatively broad spectral bands (band-widths of 20–60 nm); hyperspectral (also referred toas imaging spectrometry) is defined for sensors thatmeasure the entire spectrum under consideration incontiguous narrow spectral bands (bandwidths be-tween 2 and 20 nm).Currently, seagrass maps are still predominantlybeingproducedfromtheinterpretationofaerialpho-tographyalthoughitislikelythatairborneandspace-borne remote sensing methods will rapidly take overthisrolegiventheadvantagestheypresentintermsofaccuracy, repeatability, versatility, and informationcontent. Nevertheless, retrospective studies of sea-grass change using the more modern methodologieswillstillneedtomakeuseofresultsgeneratedbythemore traditional methods since aerial photographsare the dominant archival source of historical spatial

On the Benefits of Using Both Dual Frequency Side Scan Sonar and Optical Signatures for the Discrimination of Coral Reef Benthic Communities

The importance of coral reef ecosystems is well established (McManus and Noordeloos, 1998). The threats to these highly diverse and endangered communities are well known and a large number of reports document the dramatic effects of climate change and particularly global seawater warming, coastal development, pollution, and impacts from tourism, overfishing, and coral mining on them (Grigg & Dollar, 1990; Holden & LeDrew, 1998; Lough, 2000; Buddemeier, 2002; Knowlton, 2001; Sheppard, 2003). To protect these ecosystems the extent of their degradation must be documented through large scale mapping programmes, and inventories of existing coral reef areas are particularly important (Riegl & Purkis, 2005; Mora et al., 2006). Such programmes are essential so that the health of these ecosystems can be assessed and local and global changes over time can be detected (Holden & LeDrew, 1998). Seagrass beds are also recognized as playing a pivotal role in coastal ecosystems. They are crucial to the maintenance of estuarine biodiversity, the sustainability of many commercial fisheries, for stabilizing and enriching sediments and providing an important food resource and spawning areas for many marine organisms (Powis & Robinson, 1980; Bell & Pollard, 1989, Dekker et al., 2006). Unprecedented declines in seagrass beds have occurred in temperate and tropical meadows throughout the world; their global decline highlights the need for monitoring programmes to manage their conservation and sustainable use (Short & Wyllie-Echeverria, 1996; Ward et al., 1997). Coral reefs, seagrass, and macroalgal habitats are commonly found in association with, and in close proximity to each other, and are linked by many pathways such as sediment deposition mechanisms, the primary productivity cycle, and the migration of many fish species (Mumby, 1997). Due to their nutritional biology and photosynthetic requirements, coral reefs generally exist in clear tropical waters and this makes them highly suited for optical remote sensing (Mumby, 1997; Green et al., 2000). Although less confined to them, macroalgal and seagrass habitats are also found in such environments. Under stress, both coral and seagrass ecosystems may retreat and become replaced by macroalgal or less productive and biologically diverse sedimentary or bare rocky habitats. Such O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg

Integrating dual frequency side scan sonar and high spatial resolution satellite imagery for monitoring coral reef benthic communities

In this study, the characteristics of both optical and acoustic data types were compared to determine if synergistic use of both methods improved the accuracy of classification of benthic reefs and associated habitats. IKONOS imagery and dual frequency side scan sonar data were acquired in the western Caribbean encompassing coral, seagrass, algal and sediment habitats. Both data types were analysed in isolation and in combination at both habitat and community classification levels. The accuracies achieved with the combined dataset (61% and 52% for the coarse and medium classification levels, respectively) were significantly higher than what was achieved on the basis of the two datasets used in isolation, demonstrating the synergy of the acoustic and optical datasets. The greater accuracy improvements were attributed to the higher spatial resolution of the sonar data, its greater depth penetration, and information contained in the sonograms regarding structural organisation of the habitats. Misclassifications using the combined datasets could be attributed to spectral and textural similarities between different classes, quantity and classification of the ground truth sites, and uncertainties in the co-registration of the two datasets.

Hyperspectral discrimination of coral reef benthic communities

This study sought to extend the spectral library of reef associated species found in the literature as well as to investigate variation in optical reflectance within colonies of the same species from different geographical regions. We tested the spectral discrimination of species and taxonomic groups using a hierarchical classification system, to compare results from hyperspectral reflectance and derivative datasets to those simulated for three visible multispectral wavebands typical of the high spatial resolution optical sensors (e.g. IKONOS and QuickBird).