Multispectral satellite remote sensing can predict shallow-water depth distribution inexpensively and exhaustively, but it requires many in-situ measurements for calibration. To extend its feasibility, we improved and employed a recently developed technique, for the first time, to obtain a generalized predictor of depth. We used six WorldView-2 images and obtained a predictor that yielded a 0.648 m root-mean-square error against a dataset with a 5.544 m standard deviation of depth. The predictor can be used with as few as two pixels with known depth per image, or with no depth data whatsoever, if only relative depth is needed. (98 words) Subject termsBathymetry, multispectral, satellite remote sensing, coral reef 4 Main Text

Although visible bands of high-resolution multispectral imagery are used for bathymetry, the relative utility of different bands is poorly understood. Therefore, we evaluated the relative utility of the six visible bands of WorldView-2. We statistically selected the visible bands that gave the best accuracy under different situations, tallying how often each band was included in the best combination. The average frequency was greater than 50% for every band and differed between bands by only 17%. We conclude that all visible bands are useful for remote sensing of water depth, although the utility depends on the image and number of training pixels available.