Bathymetry Retrieval from Hyperspectral Imagery in the Very Shallow Water Limit: A Case Study from the 2007 Virginia Coast Reserve (VCR'07) Multi-Sensor Campaign

@article{Bachmann2010BathymetryRF,
  title={Bathymetry Retrieval from Hyperspectral Imagery in the Very Shallow Water Limit: A Case Study from the 2007 Virginia Coast Reserve (VCR'07) Multi-Sensor Campaign},
  author={Charles M. Bachmann and Marcos J. Montes and Robert A. Fusina and Christopher E. Parrish and Jon Sellars and Alan D. Weidemann and Wesley Goode and Charles Reid Nichols and Patrick Woodward and Kevin L. McIlhany and Victoria Hill and Richard C. Zimmerman and Daniel R. Korwan and Barry Truitt and Arthur Schwarzschild},
  journal={Marine Geodesy},
  year={2010},
  volume={33},
  pages={53 - 75}
}
We focus on the validation of a simplified approach to bathymetry retrieval from hyperspectral imagery (HSI) in the very shallow water limit (less than 1–2 m), where many existing bathymetric LIDAR sensors perform poorly. In this depth regime, near infra-red (NIR) reflectance depends primarily on water depth (water absorption) and bottom type, with suspended constituents playing a secondary role. Our processing framework exploits two optimal regions where a simple model depending on bottom type… 

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