A water-depth correction algorithm for submerged vegetation spectra

Abstract

The substantial difference between the reflectance values at the red and the nearinfrared (NIR) regions has been used to develop vegetation indices for remote sensing of green plants. These spectral indices, however, may not effectively be used for underwater plants because the overlying water interferes with the upwelling vegetation signals. We empirically separated the energy absorbed by water and scattered from the water column using an indoor water tank with hypothetical surfaces that either reflect or absorb all the incoming light. Using the experimental data, a function was developed to correct reflectance measured from a shallow water body for the water effects. When applied to independently measured reflectance of underwater vegetation, the algorithm significantly enhanced vegetation signals, especially in the NIR region. This experimentally driven algorithm can improve mapping capabilities of seagrass beds and invasive aquatics in shallow water bodies.

An improved water-depth correction algorithm for seagrass mapping using hyperspectral data

“…The experimental setup and procedures were similar to those described by Cho and Lu (2010). A black-bottomed tank was again used as the 100% hypothetical absorbing bottom and the reflectance from the black-bottomed tank was used to calculate reflectance from the water surface and the water column (R w ).…”

“…Email: hyun_jung.cho@jsums.edu were derived from empirical measurements made over controlled experimental tanks with hypothetical surfaces that either reflect or absorb all the incoming energy. The algorithm was found to provide a good estimate of the reflectance, especially in the near-infrared (NIR), of laboratory-measured submerged vegetation (Cho and Lu 2010).…”

“…In a previous study, a water-depth correction algorithm was developed to improve the detection of underwater vegetation spectral signals (Cho and Lu 2010). Parameters for the correction of water column-induced scattering and absorption *Corresponding author.…”

Remote Sensing of Submerged Aquatic Vegetation

“…The empirically driven correction algorithm significantly restored the vegetation signals, especially in the NIR region, when applied to independently measured reflectance of underwater plants taken over indoor and outdoor tanks (Cho & Lu, 2010;Washington et al 2011). The algorithm was also successful in restoring the NIR signals originating from seagrass-dominated sea floors when applied to airborne hyperspectral data of Mississippi and Texas coastal waters (Cho et al, 2009;Lu & Cho, 2011;Fig.…”

“…The effects of the overlying water column on upwelling hyperspectral signals were modeled by empirically separating the energy absorbed and scattered by the water using data collected through a series of controlled experiments using hypothetical bottom surfaces that either 100% absorbs or 100% reflects (Cho & Lu, 2010). Later, the white surface (the 100% reflecting surface) was replaced with a gray surface with a known reflectance to reduce problems associated with enhanced multi-path scattering (Lu & Cho, 2011).…”