@article{0af13139459e4cdfb64404655d2eb6b9,
title = "A Simple Method for Extracting Water Depth From Multispectral Satellite Imagery in Regions of Variable Bottom Type",
abstract = "Satellite imagery offers an efficient and cost-effective means of estimating water depth in shallow environments. However, traditional empirical algorithms for calculating water depth often are unable to account for varying bottom reflectance, and therefore yield biased estimates for certain benthic environments. We present a simple method that is grounded in the physics of radiative transfer in seawater, but made more robust through the calibration of individual color-to-depth relationships for separate spectral classes. Our cluster-based regression (CBR) algorithm, applied to a portion of the Great Bahama Bank, drastically reduces the geographic structure in the residual and has a mean absolute error of 0.19 m with quantified uncertainties. Our CBR bathymetry is 3–5 times more accurate than existing models and outperforms machine learning protocols at extrapolating beyond the calibration data. Finally, we demonstrate how comparison of CBR with traditional models sensitive to bottom type reveals the characteristic length scales of biosedimentary facies belts.",
keywords = "Bahamas, bathymetry, classification, machine learning, remote sensing",
author = "Geyman, {Emily C.} and Maloof, {Adam C.}",
note = "Funding Information: Thank you to Jeff Birch at Small Hope Bay Lodge for making work possible on Andros Island. Also, thank you to Alex Cartwright, Rudolph “Timer{"} Coakley, Niki Hinsey, Anastasia Mackey, Alvin Marshall, Sonny “Abba{"} Martin, Bhruna Neymor, Garnet Thompson, Linda Whyms, and local customs and immigration. Chris Allen at Air Flight Charters and Dawn Reading at Princeton provided logistical support. Thank you to Liam O'Connor and Tano Humes for assistance in the field. Planet provided the RapidEye satellite imagery through the Planet Research Ambassadors Program (Planet Team, 2017). Thank you especially to Joe Mascaro at Planet. Frederik Simons offered helpful suggestions about how to probe the spatial correlation structure of the residual. Comments from S. J. Purkis significantly improved the manuscript. This material is based upon work supported by the Princeton Environmental Institute at Princeton University through the Smith-Newton Scholars Program. This work also was supported by the GSA Northeastern Section Stephen G. Pollock Undergraduate Student Research Grant, the Evolving Earth Foundation, the High Meadows Foundation, and the Sigma Xi Research Society. Georeferenced tiff images of the final bathymetry and uncertainty maps (Figures 2c and 2d), the median and standard deviation of the bathymetric maps obtained from seven different RapidEye acquisitions (supporting information, Figure S4), and a table containing the GPS coordinates and tide-corrected depths from the acoustic survey (Figure 1), are available in the supporting information. Publisher Copyright: {\textcopyright}2019. The Authors.",
year = "2019",
month = mar,
doi = "10.1029/2018EA000539",
language = "English (US)",
volume = "6",
pages = "527--537",
journal = "Earth and Space Science",
issn = "2333-5084",
publisher = "Wiley-Blackwell Publishing Ltd",
number = "3",
}