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The cover of living and dead corals from airborne remote sensing
Authors:Email author" target="_blank">PJ?MumbyEmail author  JD?Hedley  JRM?Chisholm  CD?Clark  H?Ripley  J?Jaubert
Institution:(1) Marine Spatial Ecology Lab, School of Biological & Chemical Sciences, University of Exeter, Prince of Wales Road, Exeter, EX4 4PS, UK;(2) Faculté des Sciences, Université de Nice, Campus Calrose, 06108 Nice, France;(3) Department of Geography and Sheffield Centre for Earth Observation Science, University of Sheffield, Sheffield, S10 2TN, UK;(4) Hyperspectral Data Incorporated, 7071 Bayers Road, Suite 119, Halifax, N.S. B3L 2C2, Canada;(5) The Cousteau Society, 92 Avenue Kleber, 75116 Paris, France
Abstract:Trends in coral cover are widely used to indicate 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-m2 pixels and 6 spectral bands with 0.25-m2 pixels. First, we show that an instrument with 10 spectral bands possesses adequate spectral resolution 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 Porites colonies could not be distinguished from an airborne platform. Spectral differences among substrata are then exploited to predict the cover of reef substrata in ten 25-m2 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-m2 grid. Considerable disparity occurred between field and image-based measures of substrate cover within individual 25-m2 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-m2 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. <3% for living Porites, recently dead Porites and Halimeda). The least accurately estimated substrata were sand and coralline red algae, which were overestimated by absolute values 7.9% and 6.6%, respectively. The precision of sampling was similar for field and remote-sensing methods: field methods required 19 plots to detect a 10% difference in coral cover among three reefs with a statistical power of 95%. Remote-sensing methods required 21 plots. However, it took 1 h to acquire imagery over 92,500 m2 of reef, which represents 3,700 plots of 25 m2 each, compared with 3 days to survey 10 such plots underwater. There were no significant differences in accuracy between 1-m2 and 0.25-m2 image resolutions, suggesting that the advantage of using smaller pixels is offset by reduced spectral information and an increase in noise (noise was observed to be 1.6–1.8 times greater in 0.25-m2 pixels). We show that airborne remote sensing can be used to monitor coral and algal cover over large areas, providing that water is shallow and clear, and that brown fleshy macroalgae are scarce, that depth is known independently (e.g. from sonar survey).
Keywords:French Polynesia  Monitoring  Live and dead coral cover  Statistical power  Remote sensing
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