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Multi-site evaluation of IKONOS data for classification of tropical coral reef environments

TitleMulti-site evaluation of IKONOS data for classification of tropical coral reef environments
Publication TypeJournal Article
Year of Publication2003
AuthorsAndrefouet, S, Kramer, P, Torres-Pulliza, D, Joyce, KE, Hochberg, EJ, Garza-Perez, R, Mumby, PJ, Riegel, B, Yamano, H, White, WH, Zubia, M, Brock, JC, Phinn, SR, Naseer, A, Hatcher, BG, Muller-Karger, FE
JournalRemote Sensing of Env.Remote Sensing of Env.Rem. Sens. Environ.
KeywordsAccuracy, Bathymetric correction, Glint, Habitat mapping, Samoa, corals, seafloor mapping, multibeam bathymetry, benthic habitat mapping, Landsat, Seagrass

Ten IKONOS images of different coral reef sites distributed around the world were processed to assess the potential of 4-m resolution
multispectral data for coral reef habitat mapping. Complexity of reef environments, established by field observation, ranged from 3 to 15
classes of benthic habitats containing various combinations of sediments, carbonate pavement, seagrass, algae, and corals in different
geomorphologic zones (forereef, lagoon, patch reef, reef flats). Processing included corrections for sea surface roughness and bathymetry,
unsupervised or supervised classification, and accuracy assessment based on ground-truth data. IKONOS classification results were
compared with classified Landsat 7 imagery for simple to moderate complexity of reef habitats (5–11 classes). For both sensors, overall
accuracies of the classifications show a general linear trend of decreasing accuracy with increasing habitat complexity. The IKONOS sensor
performed better, with a 15–20% improvement in accuracy compared to Landsat. For IKONOS, overall accuracy was 77% for 4–5 classes,
71% for 7–8 classes, 65% in 9–11 classes, and 53% for more than 13 classes. The Landsat classification accuracy was systematically lower,
with an average of 56% for 5–10 classes. Within this general trend, inter-site comparisons and specificities demonstrate the benefits of
different approaches. Pre-segmentation of the different geomorphologic zones and depth correction provided different advantages in different
environments. Our results help guide scientists and managers in applying IKONOS-class data for coral reef mapping applications.

Short TitleRemote Sensing of EnvironmentRemote Sensing of Environment
Alternate JournalRemote Sensing of Environment