W. Paul Bissett

Ocean PHILLS hyperspectral imager: design, characterization, and calibration

The Ocean Portable Hyperspectral Imager for Low-Light Spectroscopy (Ocean PHILLS) is a hyperspectral imager specifically designed for imaging the coastal ocean. It uses a thinned, backsideilluminated CCD for high sensitivity and an all-reflective spectrograph with a convex grating in an Offner configuration to produce a nearly distortionfree image. The sensor, which was constructed entirely from commercially available components, has been successfully deployed during several oceanographic experiments in 1999-2001. Here we describe the instrument design and present the results of laboratory characterization and calibration. We also present examples of remote-sensing reflectance data obtained from the LEO-15 site in New Jersey that agrees well with ground-truth measurements.

Simulation of carbon‐nitrogen cycling during spring upwelling in the Cariaco Basin

Coupled biological-physical models of carbon-nitrogen cycling by phytoplankton, zooplankton, and bacteria assess the impacts of nitrogen fixation and upwelled nitrate during new production within the shelf environs of the Cariaco Basin. During spring upwelling in response to a mean wind forcing of 8 m s−1, the physical model matches remote-sensing and hydrographic estimates of surface temperature. Within the three-dimensional flow field, the steady solutions of the biological model of a simple food web of diatoms, adult calanoid copepods, and ammonifying/nitrifying bacteria approximate within ∼9% the mean spring observations of settling fluxes caught by a sediment trap at ∼240 m, moored at our time series site in the basin. The models also estimate within ∼11% the average 14C net primary production and mimic the sparse observations of the spatial fields of nitrate and light penetration during the same time period of February-April. Stocks of colored dissolved organic matter are evidently small and diazotrophy is minimal during spring. In one summer case of the model with weaker wind forcing, however, the simulated net primary production is 14% of that measured in August-September, while the predicted detrital flux is then 30% of the observed. Addition of a cyanophyte state variable, with another source of new nitrogen, would remedy the seasonal deficiencies of the biological model, attributed to use of a single phytoplankton group.

Predictive Ecological Modeling of Harmful Algal Blooms

We have thus far constructed a series of coupled ecological/physical models to predict the origin and fate of harmful algal blooms of the toxic dinoflagellate, Gymnodinium breve, on the West Florida shelf. We find that (1) the maximal population growth rate of G. breve must be ∼0.80 day−1 during initiation of a red tide, but as little as 0.08 day−1 during its decay, (2) diatoms dominate when estuarine and shelf-break supplies of nitrate are made available to a model community of small and large diatoms, coccoid cyanophytes and Trichodesmium, non-toxic and red-tide dinoflagellates, microflagellates, and coccolithophores, (3) a numerical recipe for large red tides of G. breve requires DON supplies, mediated by iron-starved, nitrogen-fixers, while small blooms may persist on sediment sources of DON, (4) selective grazing must be exerted on the non-toxic dinoflagellates, and (5) vertical migration of G. breve in relation to seasonal changes of summer downwelling and fall/winter upwelling flow fields determines the duration and intensity of red tide landfalls along the barrier islands and beaches of the west coast of Florida, once other losses are specified. Given poorly known initial and boundary conditions and the expense of shipboard monitoring programs, however, bio-optical moorings or remote sensors are the most likely sources of model validation and improved HAB forecasts. Accordingly, the bio-optical implications of our ecological models must be included in future simulation analyses of HABs on both the West Florida shelf and within other coastal regions. Of particular importance for initiation of the coupled biophysical models is an improved understanding of the relationship of remotely sensed surface signals to shade-adapted dinoflagellates, aggregating below the first optical depth of the water column.

The effects of temporal variability of mixed layer depth on primary productivity around Bermuda

Temporal variations in primary production and surface chlorophyll concentrations, as measured by ship and satellite around Bermuda, were simulated with a numerical model. In the upper 450 m of the water column, population dynamics of a size-fractionated phytoplankton community were forced by daily changes of wind, light, grazing stress, and nutrient availability. The temporal variations of production and chlorophyll were driven by changes in nutrient introduction to the euphotic zone due to both high- and low-frequency changes of the mixed layer depth within 32°-34°N, 62°-64°W between 1979 and 1984. Results from the model derived from high-frequency (case 1) changes in the mixed layer depth showed variations in primary production and peak chlorophyll concentrations when compared with results from the model derived from low-frequency (case 2) mixed layer depth changes. Incorporation of size-fractionated plankton state variables in the model led to greater seasonal resolution of measured primary production and vertical chlorophyll profiles. The findings of this study highlight the possible inadequacy of estimating primary production in the sea from data of low-frequency temporal resolution and oversimplified biological simulations.

New approach for the radiometric calibration of spectral imaging systems.

The calibration of multispectral and hyperspectral imaging systems is typically done in the laboratory using an integrating sphere, which usually produces a signal that is red rich. Using such a source to calibrate environmental monitoring systems presents some difficulties. Not only is much of the calibration data outside the range and spectral quality of data values that are expected to be captured in the field, using these measurements alone may exaggerate the optical flaws found within the system. Left unaccounted for, these flaws will become embedded in to the calibration, and thus, they will be passed on to the field data when the calibration is applied. To address these issues, we used a series of well-characterized spectral filters within our calibration. It provided us with a set us stable spectral standards to test and account for inadequacies in the spectral and radiometric integrity of the optical imager.

Spatial and Spectral Resolution Considerations for Imaging Coastal Waters

Current ocean color sensors, for example SeaWiFS and MODIS, are well suited for sampling the open ocean. However, coastal environments are spatially and optically more complex and require more frequent sampling and higher spatial resolution sensors with additional spectral channels. We have conducted experiments with data from Hyperion and airborne hyperspectral imagers to evaluate these needs for a variety of coastal environments. Here we present results from an analysis of airborne hyperspectral data for a Harmful Algal Bloom in Monterey Bay. Based on these results and earlier studies we recommend increased frequency of sampling, increased spatial sampling and additional spectral channels for ocean color sensors for coastal environments.

Optical remote sensing techniques in biological oceanography

Publisher Summary This chapter describes the basics of ocean color remote sensing. It includes a description to obtain and use SeaWiFS data within NASAs freely available ocean color remote sensing software. Differences in methodology and some of the more recent developments in the optical remote sensing field are described. By exploring how light penetrates the water column and how the optical constituents affects the light as it travels through the water, the basic understanding of the value and limitations of ocean color data is provided. Remote sensing provides a tool that can provide information over time/space scales not possible using traditional sampling approaches from ships. SeaWiFS data can be acquired from NASAs Distributed Active Archive Center [DAAC], and can be ordered online. SeaWiFS is a commercial instrument flying on Orbimages Orbview-2 spacecraft. Apart from the other image processing packages available, the chapter describes SeaDAS, as it is free and can be used with a currently operational satellite sensor (SeaWiFS). There are many other ocean color satellites being planned (and one that has just been launched), but the data streams are not currently available.

Development, validation, and fusion of high resolution active and passive optical imagery

HyperSpectral Imagery (HSI) of the coastal zone often focuses on the estimation of bathymetry. However, the estimation of bathymetry requires knowledge, or the simultaneous solution, of water column Inherent Optical Properties (IOPs) and bottom reflectance. The numerical solution to the simultaneous set of equations for bathymetry, IOPs, and bottom reflectance places high demands on the spectral quality, calibration, atmospheric correction, and Signal-to-Noise (SNR) of the HSI data stream. In October of 2002, a joint FERI/NRL/NAVO/USACE HSI/LIDAR experiment was conducted off of Looe Key, FL. This experiment yielded high quality HSI data at a 2 m resolution and bathymetric LIDAR data at a 4 m resolution. The joint data set allowed for the advancement and validation of a previously generated Look-Up-Table (LUT) approach to the simultaneous retrieval of bathymetry, IOPs, and bottom type. Bathymetric differences between the two techniques were normally distributed around a 0 mean, with the exception of two peaks. One peak related to a mechanical problem in the LIDAR detector mirrors that causes errors on the edges of the LIDAR flight lines. The other significant difference occurred in a single geographic area (Hawk Channel) suggesting an incomplete IOP or bottom reflectance description in the LUT data base. In addition, benthic habitat data from NOAA’s National Ocean Service (NOS) and the Florida Wildlife Research Institute (FWRI) provided validation data for the estimation of bottom type. Preliminary analyses of the bottom type estimation suggest that the best retrievals are for seagrass bottoms. One source of the potential difficulties may be that the LUT database was generated from a more pristine location (Lee Stocking Island, Bahamas). It is expected that fusing the HSI/LIDAR data streams should reduce the errors in bottom typing and IOP estimation.

Detection of seagrass scars using sparse coding and morphological filter

We present a two-step algorithm for the detection of seafloor propeller seagrass scars in shallow water using panchromatic images. The first step is to classify image pixels into scar and non-scar categories based on a sparse coding algorithm. The first step produces an initial scar map in which false positive scar pixels may be present. In the second step, local orientation of each detected scar pixel is computed using the morphological directional profile, which is defined as outputs of a directional filter with a varying orientation parameter. The profile is then utilized to eliminate false positives and generate the final scar detection map. We applied the algorithm to a panchromatic image captured at the Deckle Beach, Florida using the WorldView2 orbiting satellite. Our results show that the proposed method can achieve <90% accuracy on the detection of seagrass scars.

Hyperspectral Remote Sensing of the Coastal Environment

Paper details the construction of a new hyperspectral sensor focused on the coastal environment. This sensor follows the same basic design strategy as its predecessor, the NRL developed PHILLS sensor.