I. Ioannou

Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands.

Remote sensing algorithms that use red and NIR bands for the estimation of chlorophyll-a concentration [Chl] can be more effective in inland and coastal waters than algorithms that use blue and green bands. We tested such two-band and three-band red-NIR algorithms using comprehensive synthetic data sets of reflectance spectra and inherent optical properties related to various water parameters and a very consistent in situ data set from several lakes in Nebraska, USA. The two-band algorithms tested with MERIS bands were Rrs(708)/Rrs(665) and Rrs(753)/Rrs(665). The three-band algorithm with MERIS bands was in the form R3=[Rrs(-1)(665)-Rrs(-1)(708)]×Rrs(753). It is shown that the relationships of both Rrs(708)/Rrs(665) and R3 with [Chl] do not depend much on the absorption by CDOM and non-algal particles, or the backscattering properties of water constituents, and can be defined in terms of water absorption coefficients at the respective bands as well as the phytoplankton specific absorption coefficient at 665 nm. The relationship of the latter with [Chl] was established for [Chl]>1 mg/m3 and then further used to develop algorithms which showed a very good match with field data and should not require regional tuning.

Fluorescence component in the reflectance spectra from coastal waters. Dependence on water composition

Based on HYDROLIGHT simulations of more than 2000 reflectance spectra from datasets typical of coastal waters with highly variable optically active constituents as well as on intercomparisons with field measurements, the magnitude of chlorophyll fluorescence was analyzed and parameterized as a function of phytoplankton, CDOM, and suspended inorganic matter concentrations. Using the parameterizations developed, we show that variations in the fluorescence component of water leaving radiance in coastal waters are due more to the variability of attenuation in the water than to the variability of the fluorescence quantum yield, which we estimate to be relatively stable at around 1%. Finally, the ranges of water conditions where fluorescence plays a significant role in the reflectance NIR peak and where it is effectively undetectable are also determined.

Fluorescence component in the reflectance spectra from coastal waters. II. Performance of retrieval algorithms.

Retrieval of chlorophyll fluorescence magnitude using Fluorescence Height algorithms in coastal waters is more complicated than in the open ocean because of the strong deviations of elastic reflectance within the fluorescence band from the derived fluorescence baseline. We use results of our recently established relationship between fluorescence magnitude and concentrations of water constituents together with extensive HYDROLIGHT simulations, field and satellite data to analyze the performance and retrieval limitations of MODIS and MERIS FLH algorithms in the variety of coastal waters and to examine improvements for spectral band selection suitable for future sensors.

Neural network approach to retrieve the inherent optical properties of the ocean from observations of MODIS

Retrieving the inherent optical properties of water from remote sensing multispectral reflectance measurements is difficult due to both the complex nature of the forward modeling and the inherent nonlinearity of the inverse problem. In such cases, neural network (NN) techniques have a long history in inverting complex nonlinear systems. The process we adopt utilizes two NNs in parallel. The first NN is used to relate the remote sensing reflectance at available MODIS-visible wavelengths (except the 678 nm fluorescence channel) to the absorption and backscatter coefficients at 442 nm (peak of chlorophyll absorption). The second NN separates algal and nonalgal absorption components, outputting the ratio of algal-to-nonalgal absorption. The resulting synthetically trained algorithm is tested using both the NASA Bio-Optical Marine Algorithm Data Set (NOMAD), as well as our own field datasets from the Chesapeake Bay and Long Island Sound, New York. Very good agreement is obtained, with R² values of 93.75%, 90.67%, and 86.43% for the total, algal, and nonalgal absorption, respectively, for the NOMAD. For our field data, which cover absorbing waters up to about 6 m⁻¹, R² is 91.87% for the total measured absorption.

Retrieving quantum yield of sun-induced chlorophyll fluorescence near surface from hyperspectral in-situ measurement in productive water.

Magnitude and quantum yield (eta) of sun induced chlorophyll fluorescence are determined in widely varying productive waters with chlorophyll concentrations from 2- 200 mg/m(3). Fluorescence was estimated using linear fitting of in-situ measured surface reflectance with elastic and inelastic reflectance spectra. Elastic reflectance spectra were obtained from Hydrolight simulations with measured absorption and attenuation spectra as inputs. Eta is then computed based on a depth integrated fluorescence model and compared with Hydrolight calculation results. Despite the large variability of coastal environments examined the ? values are found to vary over a relatively narrow range 0.1%-1% with mean values of 0.33%+/-0.17%.

Satellite Retrievals of Karenia brevis Harmful Algal Blooms in the West Florida Shelf Using Neural Networks and Comparisons with Other Techniques

We describe the application of a Neural Network (NN) previously developed by us, to the detection and tracking, of Karenia brevis Harmful Algal Blooms (KB HABs) that plague the coasts of the West Florida Shelf (WFS) using Visible Infrared Imaging Radiometer Suite (VIIRS) satellite observations. Previous approaches for the detection of KB HABs in the WFS primarily used observations from the Moderate Resolution Imaging Spectroradiometer Aqua (MODIS-A) satellite. They depended on the remote sensing reflectance signal at the 678 nm chlorophyll fluorescence band (Rrs678) needed for both the normalized fluorescence height (nFLH) and Red Band Difference algorithms (RBD) currently used. VIIRS which has replaced MODIS-A, unfortunately does not have a 678 nm fluorescence channel so we customized the NN approach to retrieve phytoplankton absorption at 443 nm (aph443) using only Rrs measurements from existing VIIRS channels at 486, 551 and 671 nm. The aph443 values in these retrieved VIIRS images, can in turn be correlated to chlorophyll-a concentrations [Chla] and KB cell counts. To retrieve KB values, the VIIRS NN retrieved aph443 images are filtered by applying limiting constraints, defined by (i) low backscatter at Rrs 551 nm and (ii) a minimum aph443 value known to be associated with KB HABs in the WFS. The resulting filtered residual images, are then used to delineate and quantify the existing KB HABs. Comparisons with KB HABs satellite retrievals obtained using other techniques, including nFLH, as well as with in situ measurements reported over a four year period, confirm the viability of the NN technique, when combined with the filtering constraints devised, for effective detection of KB HABs.

Fluorescence contribution to reflectance spectra for a variety of coastal waters

Improved remote sensing retrievals of the chlorophyll fluorescence component in coastal water reflectance can significantly help environmental impact assessments. While retrieval of chlorophyll fluorescence from satellite observations of open ocean reflectance using Fluorescence Line Height (FLH) algorithms is now routine, it is much more complicated in coastal waters where the fluorescence overlaps with a NIR elastic scattering peak arising from the combination of photosynthetic pigment and particulate scattering and absorption, and rapidly increasing water absorption. To examine retrieval accuracies attainable in coastal waters by MODIS and other FLH algorithms, we compared the results of extensive numerical simulations with those of our field measurements in the Chesapeake Bay. The relationship between the contribution of fluorescence in the reflectance spectra and [Chl] and other water constituents was analyzed by simulations of more than 1000 reflectances using the HYDROLIGHT radiative transfer program. For these, IOP were related to parameterized microphysical models, following the same procedures used to generate the IOCCG dataset, but with higher (1 nm) spectral resolution, and wider range of parameters including chlorophyll specific absorption more typical of coastal waters. Results of simulations and field measurements show that the variability of retrieved fluorescence can be attributed largely to its attenuation in the water by algae, CDOM and mineral particles, and much less to the variation of the fluorescence quantum yield. Our systematic parametric study of fluorescence as a function of the other water components is then used to define the range of water parameters where fluorescence contributes significantly to the NIR peak reflectance, and where it is almost undetectable.

Evaluation of the impact of backscatter spectral characteristics on Chl retrievals in coastal waters

With the increasing recognition of the need for using the NIR bands for chlorophyll retrieval in coastal waters it is necessary to account not only for the spectral modulation of the total elastic backscatter by the chlorophyll absorption spectra, as it is normally done, but to also take into account the spectral signature of the backscatter itself, whether from mineral or organic particulates, including algae, and to assess how these factors effect retrieval algorithms. Based on our recent field measurements in coastal waters, we have undertaken a study to examine the spectral behavior of the backscatter to total scattering ratio as a function of suspended solids and chlorophyll loadings. The total scattering spectra is obtained using the WET Labs AC-S instrument which provides hyperspectral measurements of absorption and attenuation, in conjunction with the bb9 instrument which provides direct measurement of backscatter, as well fluorescence measurement of chlorophyll concentration [Chl]. The relevant WET Labs absorption and attenuation data were then used as input into Hydrolight radiative transfer simulations to obtain the backscattering ratio spectral distributions. Preliminary NIR algorithms, which were evolved for high [Chl] coastal waters and which focus on the contribution of spectral changes due to chlorophyll backscattering in the NIR, are presented. It is expected that these algorithms will ultimately prove to be less dependent on regional tuning.

Impact of scattering and absorption of photosynthetic pigments on fluorescence retrieval algorithms for coastal waters

Fluorescence Line Height (FLH) algorithms are effective for fluorescence retrieval in the open ocean where elastic reflectance in the fluorescence zone does not deviate much from the baseline. In coastal waters, FLH algorithms are significantly complicated by the overlap of the fluorescence and elastic reflectance peaks. To test accuracy of MODIS, MERIS and other FLH algorithms, we compared numerical simulations using an extensive synthetic database suitable for case II waters, with results of extensive field measurements of reflectance, absorption and attenuation spectra by us in the Chesapeake Bay, as well as satellite FLH data from several areas that typically show low correlation between [Chl] and FLH. Our synthetic datasets were created using the HYDROLIGHT radiative transfer code with IOPs connected to parameterized microphysical models in accordance with procedures used to generate the IOCCG dataset, but with some added improvements. These included higher (1 nm) spectral resolution, a wider range of parameters typical for coastal waters, including chlorophyll specific absorptions with significant variations in spectral shapes and magnitude. HYDROLIGHT simulations of elastic reflectance using measured attenuation/extinction spectra followed by subtraction from measured reflectance, permitted retrieval of the fluorescence contribution to the latter, for comparisons with the data set simulations. We find relatively small fluorescence contributions to surface reflectance for mineral concentrations > 5 mg/l because of strong attenuation in the excitation zone and enhanced elastic reflectance making fluorescence detection unrealistic. For lower mineral concentrations, we find that some combinations of NIR observation bands permit reasonably good FLH retrievals in conditions where specific absorption spectral variation is not very high, and that application of multi-spectral algorithms can be more efficient for the retrieval of fluorescence contributions in coastal areas.

Algorithms for the remote estimation of chlorophyll-a in the Chesapeake Bay

Remote estimation of chlorophyll-a concentration [Chl-a] in the Chesapeake Bay from reflectance spectra is challenging because of the optical complexity and variability of the water composition as well as atmospheric corrections for this area. This work is focused on algorithms for near surface measurements. The performance and tuning of several well established global inversion algorithms that use the NIR and Blue-Green parts of the spectrum are analyzed together with recently proposed algorithm that use the Red-Green part of the spectrum. These algorithms are evaluated and tuned on our field data collected during summer 2013 field campaign in the in the Chesapeake Bay region . These data consist of a full range of water optical properties as well as chlorophyll concentrations and specific absorption spectra from in water samples. We then compare these algorithms with a multiband retrieval algorithm that was developed using neural networks (NN) and which was trained on simulated data generated through bio-optical modeling typical for a broad range of coastal water parameters, including those known for the Chesapeake Bay. This NN algorithm was then applied to our field measurements and used to retrieve the phytoplankton absorption at 443nm which was then related to [Chl-a]. In this process, special attention was paid to field data consistency in terms of both measured reflectance and [Chl-a] values, to avoid undesirable biases and trends. All algorithm retrievals were finally evaluated by several statistical indicators to arrive at their relative merits and potential for further improvements and application to satellite data.