Interpretation of hyperspectral remote-sensing imagery by spectrum matching and look-up tables

TLDR

The LUT methodology works as follows. A database of HydroLight‑generated reflectance spectra for various water depths, bottom types, and optical properties is built, and each pixel’s measured spectrum is matched to the closest database entry via least‑squares, assuming the matched conditions represent the pixel’s environment; the method was applied to an Ocean Portable Hyperspectral Imaging Low‑Light Spectrometer image near Lee Stocking Island, Bahamas. The LUT‑retrieved bottom depths were within 5 % and 0.5 m of acoustic depths, bottom classification matched diver and video spot classification, and retrieved IOPs agreed with measured values.

Abstract

A spectrum-matching and look-up-table (LUT) methodology has been developed and evaluated to extract environmental information from remotely sensed hyperspectral imagery. The LUT methodology works as follows. First, a database of remote-sensing reflectance (Rrs) spectra corresponding to various water depths, bottom reflectance spectra, and water-column inherent optical properties (IOPs) is constructed using a special version of the HydroLight radiative transfer numerical model. Second, the measured Rrs spectrum for a particular image pixel is compared with each spectrum in the database, and the closest match to the image spectrum is found using a least-squares minimization. The environmental conditions in nature are then assumed to be the same as the input conditions that generated the closest matching HydroLight-generated database spectrum. The LUT methodology has been evaluated by application to an Ocean Portable Hyperspectral Imaging Low-Light Spectrometer image acquired near Lee Stocking Island, Bahamas, on 17 May 2000. The LUT-retrieved bottom depths were on average within 5% and 0.5 m of independently obtained acoustic depths. The LUT-retrieved bottom classification was in qualitative agreement with diver and video spot classification of bottom types, and the LUT-retrieved IOPs were consistent with IOPs measured at nearby times and locations.