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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