Bathymetry estimations in shallow areas using satellite multispectral scanners have been used preferentially in areas with clear water and homogeneous bottoms. Reef environments have high water transparency, but also have a rich bottom diversity which introduces several difficulties into water depth accuracy estimations. The aim of the present study was to assess the accuracy in a coral reef system of four bathymetric approaches based on a Landsat Thematic Mapper (TM) image, namely (1) a single linear regression model using the first principal component; (2) a multiple linear regression; (3) a two-step non-supervised classification with multiple linear regression; and (4) a supervised classification. Given the natural patchiness, and cover type and depth variability in the study area (Alacranes Reef), 473 echosounded profiles were selected under radiometric and topographic criteria, in order to delineate homogeneous areas that allow a better relationship between radiometric and depth data. One thousand and eighty-five profiles that did not meet the criteria were used to assess the model's response in areas where the bottom exhibits high variability. Differences provided by residual analysis and rms. error were used to evaluate the water depth accuracy estimations of the models. A two-step non-supervised approach produced the lowest overall rms. error (2 m), and exhibited balanced over/under error residuals. References: 18
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