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
Abstract
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 and water depth can be applied in the very shallow limit. These two optimal spectral regions are at a local maximum in the near infra-red reflectance near 810 nm, corresponding to a local minimum in absorption, and a maximum in the first derivative of the reflectance near 720 nm. These two regions correspond to peaks in spectral correlation with bathymetry at these depths.
Department
Center for Coastal and Ocean Mapping
Publication Date
2-26-2010
Volume
33, Issue 1
Journal Title
Marine Geodesy
Pages
53-75
Publisher
Taylor & Francis
Digital Object Identifier (DOI)
10.1080/01490410903534333
Document Type
Journal Article
Recommended Citation
Charles M. Bachmann , Marcos J. Montes , Robert A. Fusina , Christopher Parrish , Jon Sellars , Alan Weidemann , Wesley Goode , C. Reid Nichols , Patrick Woodward , Kevin McIlhany , Victoria Hill , Richard Zimmerman , Daniel Korwan , Barry Truitt & Arthur Schwarzschild (2010) 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, Marine Geodesy, 33:1, 53-75, DOI: 10.1080/01490410903534333