Variations of ocean colour parameters with nonuniform vertical profiles of chlorophyll concentration

Based on radiative transfer simulations, the effects of nonuniform chlorophyll profiles in case 1 waters on the penetration depth, the above‐surface spectral remote‐sensing reflectance, and the optically weighted chlorophyll concentration are investigated. The simulations for nonuniform chlorophyll profiles are compared with those for homogeneous ocean whose chlorophyll concentrations are identical to the surface chlorophyll concentrations in the inhomogeneous ocean. Due to influence of the nonuniformity of chlorophyll profile, the maximum relative error for the penetration depth at 445 nm is more than 60%, the spectral remote‐sensing reflectance is about 40% and the optically weighted chlorophyll concentration is about 40% within the range of our simulations. However, the simulation shows that there is always a spectral band where the value of above‐surface remote‐sensing reflectance is not influenced by the nonuniformity. Depending on this band, a new model for retrieving sea surface chlorophyll concentration is designed by adding a compensation term into the variable in SeaWiFS OC2V4 algorithm. By using an iterative method with this new model, sea surface chlorophyll concentration can be well retrieved even in an area where the vertical chlorophyll distribution is unknown.     

MERIS potential for ocean colour studies in the open ocean

The interest of space observations of ocean colour for determining variations in phytoplankton distribution and for deriving primary production (via models) has been largely demonstrated by the Coastal Zone Color Scanner (CZCS) which operated from 1978 to 1986. The capabilities of this pioneer sensor, however, were limited both in spectral resolution and radiometric accuracy. The next generation of ocean colour sensors will benefit from major improvements. The Medium Resolution Imaging Spectrometer (MERIS), planned by the European Space Agency (ESA) for the Envisat platform, has been designed to measure radiances in 15 visible and infrared channels. Three infrared channels will allow aerosol characterization, and therefore accurate atmospheric corrections, to be performed for each pixel. For the retrieval of marine parameters, nine channels between 410 and 705nm will be available (as opposed to only four with the CZCS). In coastal waters this should, in principle, allow a separate quantification of different substances (phytoplankton, mineral particles, yellow substance) to be performed. In open ocean waters optically dominated by phytoplankton and their associate detrital matter, the basic information (i.e. the concentration of phytoplanktonic pigments) will be retrieved with improved accuracy due to the increased radiometric performances of MERIS. The adoption of multi-wavelength algorithms could also lead to additional information concerning auxiliary pigments and taxonomic groups. Finally, MERIS will be one of the first sensors to allow measurements of Sun-induced chlorophyll a in vivo fluorescence, which could provide a complementary approach for the assessment of phytoplankton abundance. The development of these next-generation algorithms, however, requires a number of fundamental studies.     

A comparison of Multi-layer Perceptron and multilinear regression algorithms for the inversion of synthetic ocean colour spectra

Artificial radiance sets were used as inputs to Multi-layer Perceptron and multilinear regression algorithms to study their retrieval capabilities for optically active constituents in sea water. The radiative transfer model Hydrolight was used to produce 18,000 artificial reflectance spectra representing various case 1 and case 2 water conditions. The remote sensing reflectances were generated at the Medium Resolution Imaging Spectrometer (MERIS) wavebands 412, 442, 490, 510, 560, 620, 665 and 682 nm from randomly generated triplet combinations of chlorophyll a, non-chlorophyllous particles and CDOM (Coloured Dissolved Organic Matter) concentrations. These reflectances were contaminated with different noise terms, before they were used to assess the performance of multilayer perceptron and multilinear regression algorithms. The potential of both algorithms for retrieving optically active constituents was demonstrated with the neural network showing more accurate results for case 2 scenarios.     

The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates

In this paper, uncertainties in the retrieval of satellite surface chlorophyll concentrations in the Mediterranean Sea have been evaluated using both regional and global ocean colour algorithms. The rationale for this effort was to define the most suitable ocean colour algorithm for the reprocessing of the entire SeaWiFS archive over the Mediterranean region where standard algorithms were demonstrated to be inappropriate. Using a large dataset of coincident in situ chlorophyll and optical measurements, covering most of the trophic regimes of the basin, we validated two existing regional algorithms [Bricaud, A., E. Bosc, and D. Antoine, 2002. Algal biomass and sea surface temperature in the Mediterranean Basin — Intercomparison of data from various satellite sensors, and implications for primary production estimates. Remote Sensing of Environment, 81(2-3), 163-178.; D'Ortenzio, F., S. Marullo, M. Ragni, M. R. d'Alcala and R. Santoleri, 2002. Validation of empirical SeaWiFS algorithms for chlorophyll-alpha retrieval in the Mediterranean Sea — A case study for oligotrophic seas. Remote Sensing of Environment, 82(1), 79-94.] and the global algorithm OC4v4 used for standard NASA SeaWiFS products. The results of our analysis confirmed that the OC4v4 performs worse than the two existing regional algorithms. Nonetheless, these two regional algorithms do show uncertainties dependent on chlorophyll values. Then, we introduced a better tuned algorithm, the MedOC4. Using an independent set of in situ chlorophyll data, we quantified the uncertainties in SeaWiFS chlorophyll estimates using the existing and new regional algorithms. The results confirmed that MedOC4 is the best algorithm matching the requirement of unbiased satellite chlorophyll estimates and improving the percentage of the satellite uncertainty, and that the NASA standard chlorophyll products are affected by an uncertainty of the order of 100%. Moreover, the analysis suggests that the poor quality of the SeaWiFS chlorophyll in the Mediterranean is not due to the atmospheric correction term but to peculiarities in the optical properties of the water column. Finally the observed discrepancy between the global and the regional bio-optical algorithms has been discussed analysing the differences between the two in situ datasets used for tuning the algorithms (SeaBASS versus ours). The main results are that methodological differences in the two datasets cannot play a major role and the inherent bio-optical properties of the basin can explain the observed discrepancy. In particular the oligotrophic water of the Mediterranean Sea is less blue (30%) and greener (15%) than the global ocean.     

Landsat remote sensing of chlorophyll a concentrations in central North Island lakes of New Zealand

We investigated the use of Landsat Enhanced Thematic Mapper (ETM) imagery to synoptically quantify chlorophyll a (chl a) concentrations. Two adjoining pairs of images of the central North Island were acquired on two different days in summer and spring 2002. 6sv atmospheric correction was compared to the cosine of the solar zenith angle correction (COST) dark object subtraction (DOS) atmospheric correction. The highest correlation between 6sv ln(Band 3) water surface reflectance and ln(chl a) was found in the 24 January 2002 image (r ² = 0.954). 6sv atmospheric correction was preferable to COST-DOS as it gave more realistic reflectance values at a clear-water reference site and produced the highest correlation coefficient. The results from this investigation suggest that remote sensing provides a valuable tool to assess temporal and spatial distributions of chl a in unmonitored areas within lakes and that predictions may also be extended to unmonitored lakes within the domain of satellite image capture.     

On the calibration and use of in situ ocean colour measurements for monitoring algal blooms

Simultaneous in situ measurements of chlorophyll concentration and water colour are reported at three diverse sites: a sea loch, the west Scottish shelf and the north Atlantic. A good (R² =0.97) log-log relation exists between the ratio, gamma, of the irradiance reflection coefficients at 490 and 570 nm and the chlorophyll concentration, C, over a range of chlorophyll concentrations from 0.01 to nearly 50 mg m ^-3     

New algorithms for the Perspective-Three-Point Problem

In this paper,two approaches are used to solve the Perspective-Three-Point Problem(P3)):the symbolic computation approach and the geometric approach.In the symbolic computation approach,we use Wu-Ritt‘s zero decomposition algorithm to give a complete triangular decomposition for the P3P equation system.This decomposition provides the firest complete analytical solution to the P3P problem.In the geometric approach,we give some pure geometric criteria for the number of real physical solutions.The complete solution classification for two special cases with three and four paramters is also given.     

Evaluation of SeaWiFS chlorophyll algorithms in the Southwestern Atlantic and Southern Oceans

Bio-optical measurements of spectral upwelling radiance and surface chlorophyll-a concentration have been conducted during 15 cruises between 1995 and 2004. The bio-optical data were divided into two sub-sets: the Southwestern Atlantic Ocean (SwAO), comprising a variety of biogeochemical provinces, from the oligotrophic waters in the South Atlantic gyre to the coastal waters influenced by La Plata River and Patos Lagoon discharge, and the Southern Ocean (SO) data set, comprising sampling stations south of the mean position of the Polar Front, with most stations being located in the vicinity of the Antarctic Peninsula. We derived regional chlorophyll algorithms for both regions and comparisons were made with the NASA's OC4v4 (operational algorithm) and OC2v4. For the Southwestern Atlantic region, the NASA OC4v4 algorithm presented a reasonable performance (r²=0.87, rmse-L=0.475, N=136) as compared to the revised algorithm for SwAO data (r²=0.89, rmse-L=0.426, N=136). A few stations under strong river plume influence were not considered in the analyses. These were detected by a higher reflectance at 670 nm, at low in situ chlorophyll concentration (<2 mg m⁻³). These results show that empirical algorithms applied to in-situ radiance data have a limited ability to extract accurate chlorophyll estimates below a 30% uncertainty level. For Southern Ocean stations, a 2-band linear-type model was generated (r²=0.64, rmse-L=0.347, N=77), which significantly improved the bias (6.4%) as compared to NASA's OC4v4 algorithm (bias=−21.7%). An evaluation of some published high-latitude algorithms on our data set has shown a better performance by taxon-specific models, even from distant regions. A validation experiment of the normalized spectral water-leaving radiances and chlorophyll-a SeaWiFS products was also conducted using the FURG-SwAO/SO data set, through a match-up exercise. Despite the relatively low number of pairs of radiometric measurements, SeaWiFS estimations compare well with in situ data (0.77<r²<0.98, N=21), although the satellite estimate show a marked bias (−35.6%) in the blue band nL_w (412). Regarding the chlorophyll-a concentration, an overall agreement was observed (r²=0.77, rmse-L=0.66, N=28), with a mean absolute percentage difference of 66%, which is above the goal generally accepted of 35% for satellite ocean color chlorophyll estimates. For the studied Southern Ocean area (mainly the Bransfield Strait), NASA's OC4v4 algorithm systematically underestimates chlorophyll above 0.2 mg m⁻³, as previously demonstrated by other researchers.     

Joint analysis of temperature and ocean colour satellite images for mesoscale activities in the Gulf of Biscay

In the framework of the Ocean Colour European Archive Network (OCEAN) programme of the European Commission and the European Space Agency, a joint team composed of ACRI, GM-Images and Ecole des Mines de Paris proposed to analyse jointly Coastal Zone Color Scanner (CZCS) (chlorophyll) and Advanced Very High Resolution Radiometer (AVHRR) (temperature) data in order to study mesoscale dynamics features in the Gulf of Biscay. A large archive of AVHRR data, between 1978-1990, was analysed with the support of EPSHOM (Etablissement Principal du Service Hydrographique et Oceanographique de la Marine), together with about one hundred pairs of AVHRR and CZCS images. The method used to process AVHRR and CZCS data is presented in this paper. Interesting oceanographic results have been obtained. Mesoscale features such as eddies and plumes have been observed and detailed. Thestructures have been identified and classified according to an accurate typology. The appearance and evolution of mushroom-like structures have been noted, which may promote a high efficiency in the mixing of water masses. The benefit of the fusion of images is discussed. Although the locations of structures observed in both image types differ perceptibly, the increased number of observations leads to better mapping and monitoring of the features, both in space and time.     

Climatological,annual, and seasonal variability in chlorophyll concentration in the Gulf of Mexico,western Caribbean,and Bahamas using NASA colour maps

This study investigates climatological, seasonal, and interannual variability in chlorophyll concentration (Chl) throughout the Gulf of Mexico (GM), the western Caribbean Sea (WC), and the Bahamas (BI). For this purpose, Coastal Zone Color Scanner (CZCS) (1979–1986), Ocean Color and Temperature Scanner (OCTS) (1996–1997), and Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) (1997–2008) NASA climatology, yearly, and seasonal Level-3 Standard Mapped Image series were used. Inspection of the original Chl and the obtained fuzzy unsupervised classified maps show the existence of a transition zone between the already known coastal and open waters. The extension (total number of pixels) and form of polygons representing these water masses vary both annually and seasonally, showing their greatest differences during spring and autumn in the northeastern and northwestern GM, Campeche Sound, and the Honduras coast in the Caribbean. In contrast, the BI present polygons having an almost invariant extension and form. The seasonal averaged Chl values up to 0.8 mg m^?3 present a cyclic variation, showing the highest Chl during winter months and the lowest Chl during summer months, independent of the basin or the sensor under consideration. The CZCS and OCTS products must be considered with care; however, they provide results that are compatible with findings from the SeaWiFS time series. Annual and winter/autumn trends – a decrease in Chl – were identified in the GM and BI. The Caribbean reports constant Chl values during the two periods under study. Possible interpretations of these trends will come from detailed interpretation of local data.     

New spectral estimate for SAR imaging of the ocean

On the basis of the theory of microwave scattering from the ocean surface the correlation function of the synthetic aperture radar (SAR) signal intensity was obtained as a sum of two items. The first item is the proper image correlation function, i.e. the correlation function free of speckle noise SAR signal intensity, which has been investigated in many works (mostly by Alpers et al.). The second item describes the speckle structure in the image. It has been shown that at sufficiently large values of the well‐known velocity bunching parameter the speckle energy is significant within the spectral interval, where the spectrum of large ocean waves is concentrated. In this case the speckle noise can not be suppressed efficiently by means of image filtering. Meanwhile, the mentioned second item is nothing other than half of the correlation function of the complex intensity, which is the square of the SAR signal complex amplitude (unlike the usual real intensity, i.e. the square of the modulus). Therefore, the unspeckled image correlation function can be presented as the difference between the real intensity correlation function and half of the complex intensity function. This leads to a new spectral estimate, free of speckle noise, for the SAR image. The corresponding expression for the new estimate is presented.     

An algorithm for the retrieval of suspended sediment concentrations in the Irish Sea from SeaWiFS ocean colour satellite imagery

A study was conducted in the Irish Sea with the aim of deriving an algorithm for the retrieval of suspended sediment concentrations from ocean colour imagery obtained from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). In situ observations of the diffuse attenuation coefficient, K_d , and irradiance reflectance, R, were obtained at wavelengths coincident with the SeaWiFS visible wavebands using a Profiling Reflectance Radiometer (PRR600, Biospherical Instruments Inc., San Diego). Results showed that surface reflectance at 665 nm (R₆₆₅ ), rather than variations in the intrinsic colour of the ocean (using colour ratios), was the most widely applicable method of obtaining suspended sediment concentrations from ocean colour imagery in this region. The derived algorithm enabled the estimation of mineral suspended sediment (MSS) concentrations from ocean colour in the Irish Sea, accurate to within 1 mg l^?1 (see equation below). Furthermore, the application of this algorithm to a SeaWiFS image of the Irish Sea accurately reproduced known regions of high turbidity with realistic MSS concentrations.

MSS=0.0441R ² ₆₆₅ + 1.1392R ₆₆₅ + 1.7459

(R ²=0.9105, n=124, RMS error=0.907)

Specific absorption and scattering coefficients were derived for all optically active in-water constituents, namely yellow substance (YS), mineral suspended sediments (MSS) and phytoplankton pigments (C). An optical model based on the empirically derived absorption and scattering coefficients reproduced the observed relationship between MSS and R ₆₆₅. Model results highlighted the relative insensitivity of reflectance at 665 nm to variations in the concentrations of other in-water constituents, suggesting that the algorithm may be applicable to the Irish Sea throughout the year.     

Impact of sea ice on the retrieval of water-leaving reflectance, chlorophyll a concentration and inherent optical properties from satellite ocean color data

Two physical phenomena by which satellite remotely sensed ocean color data are contaminated by sea ice at high latitudes are described through simulations and observations: (1) the adjacency effect that occurs along sea ice margins and (2) the sub-pixel contamination by a small amount of sea ice within an ocean pixel. The signal at the top of the atmosphere (TOA) was simulated using the 6S radiative transfer code that allows modeling of the adjacency effect for various types of sea ice surrounding an open water area. In situ sea ice reflectance spectra used in the simulations were measured prior to and during the melt period as part of the 2004 Canadian Arctic Shelf Exchange Study (CASES). For sub-pixel contamination, the TOA signal was simulated for various surface reflectances obtained by linear mixture of both sea ice and water-leaving reflectances (ρ_w). The standard atmospheric correction algorithm was then applied to the simulated TOA spectra to retrieve ρ_w spectra from which chlorophyll a concentrations (CHL) and inherent optical properties (IOPs) were derived. The adjacency effect was associated with large errors (> 0.002) in the retrieval of ρ_w as far as 24 km from an ice edge in the blue part of the spectrum (443 nm). Therefore, for moderate to high CHL (> 0.5 mg m^− 3), any pixel located within a distance of ∼ 10-20 km from the ice edge were unreliable. It was also found necessary to consider the adjacency effect when the total absorption coefficient (a_t) was to be retrieved using a semi-analytical algorithm. a_t(443) was underestimated by more than 35% at a distance of 20 km from an ice edge for CHL > 0.5 mg m^− 3. The effect on the retrieval of the particle backscattering coefficient (b_bp) was important only for clear waters (CHL ∼ 0.05 mg m^− 3). In contrast, sub-pixel contamination by a small amount of sea ice produced systematic underestimation of ρ_w in the blue because of incorrect interpretation of enhanced reflectance in the near infrared that is attributed to higher concentrations of atmospheric aerosols. In general, sub-pixel contamination was found to result in overestimations of CHL and a_t, and underestimations of b_bp. A simple method was proposed to flag pixels contaminated by adjacency effect.     

A study of the stationary and the anomalous in the ocean surface chlorophyll distribution by satellite data

Variability of chlorophyll concentration in the ocean is one of the most important components of the primary production process on the planet. To preserve the biosphere and to make appropriate use of it, it is imperative to have a deep insight into the long-term dynamics of the primary production on the planet. To investigate the dynamics of chlorophyll concentration based on satellite data, the Institute of Biophysics (Russian Academy of Sciences, Siberian Branch) has developed a geoinformation system. It was used to detect the areas in the global ocean that are quasistationary in relation to seasonal dynamics of chlorophyll concentration. Areas such as these, found in the Indian Ocean, are described in this work. These areas form the basis for the analysis of long-term dynamics of chlorophyll concentration. In these quasistationary zones systematic monitoring of phytopigment concentration is conducted by space-borne and marine craft. The work presents long-term satellite-based data on the space distribution of anomalous deviations of chlorophyll concentration in the ocean. An anomaly criterion is proposed and maps of Pacific Ocean areas with a high probability of anomalies are presented.     

A class-based approach to characterizing and mapping the uncertainty of the MODIS ocean chlorophyll product

Global chlorophyll products derived from NASA's ocean color satellite programs have a nominal uncertainty of ± 35%. This metric has been hard to assess, in part because the data sets for evaluating performance do not reflect the true distribution of chlorophyll in the global ocean. A new technique is introduced that characterizes the chlorophyll uncertainty associated with distinct optical water types, and shows that for much of the open ocean the relative error is under 35%. This technique is based on a fuzzy classification of remote sensing reflectance into eight optical water types for which error statistics have been calculated. The error statistics are based on a data set of coincident MODIS Aqua satellite radiances and in situ chlorophyll measurements. The chlorophyll uncertainty is then mapped dynamically based on fuzzy memberships to the optical water types. The uncertainty maps are thus a separate, companion product to the standard MODIS chlorophyll product.     

New constructive algorithms for leather nesting in the automotive industry

In this paper, we address one of the hardest two-dimensional cutting stock problems that can be found in industry. The problem is called the Leather Nesting Problem, and it consists in finding the best layouts for a set of irregular shapes within large natural leather hides with highly irregular contours, and which may have holes and quality zones. Here, we focus on a real case from the automotive industry, and in particular on the production of car seats. In this case, the irregular shapes that have to be cut from the hides are pieces of the car seats.The practical relevance of this problem, and the potential value of the savings that good solutions may generate, contrasts with the very small number of contributions that have been reported in the literature. In this paper, we aim to contribute to the efficient resolution of this problem by exploring in depth many new different constructive procedures. Our approaches rely on the computation of no-fit polygons, and try to use the information provided by these polygons as much as possible. Different strategies for sorting, selecting and placing the pieces, and for evaluating the placement of these pieces are proposed and discussed. We also report on an extensive set of computational experiments using real instances. To evaluate our approaches, we applied the real criteria used by companies operating in this sector. These experiments show that our approaches can generate very high quality layouts within the same time limits as those needed by human operators.     

Assessment of SeaWiFS,MODIS, and MERIS ocean colour products in the South China Sea

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Medium Resolution Imaging Spectrometer (MERIS) remote-sensing radiometric and chlorophyll-a (chl-a) concentration products for the South China Sea (SCS) from October 2003 to May 2010 were assessed using in situ data. A strict spatiotemporal match-up method was used to minimize the temporal variability effects of atmosphere and seawater around the measurement site. A comparison of the remote-sensing reflectance (R_rs(λ)) of the three sensors with in situ values from the open waters of the SCS showed that the mean absolute percentage difference varied from 13% to 55% in the 412–560 nm spectral range. Generally, the MERIS radiometric products exhibited higher typical uncertainties and bias than the SeaWiFS and MODIS products. The R_rs(443) to R_rs(555/551/560) band ratios of the satellite data were in good agreement with in situ observations for these sensors. The SeaWiFS, MODIS, and MERIS chl-a products overestimated in situ values by 74%, 42%, and 120%, respectively. MODIS retrieval accuracy was better than those of the other sensors, with MERIS performing the worst. When the match-up criteria were relaxed, the assessment results degraded systematically. Therefore, strict spatiotemporal match-up is recommended to minimize the possible influences of small-scale variation in geophysical properties around the measurement site. Coastal and open-sea areas in the SCS should be assessed separately because their biooptical properties are different and the results suggest different atmospheric correction problems.     

Correction of bottom influence in ocean colour satellite images of shallow water areas of the Baltic Sea

Ocean colour satellite measurements are mainly disturbed by the atmosphere, the sea surface and the sea bottom in shallow water areas. In such areas special features of bottom topography can be recognized in satellite images of the visible spectrum and the derived concentrations of water constituents are often misinterpreted. The influence of the sea bottom depends on the water depth, the transmission of the water column, the reflectance of the water, the reflectivity of the bottom materials and the used spectral channels of satellite sensors. The influence of the sea bottom on the spectral reflectance at the sea surface is discussed here on the basis of model computations. The calculations are realized for examples of shallow water areas of the Baltic Sea. Furthermore, a technique for the identification of sea bottom disturbed pixels in satellite images and for the elimination of bottom effects is presented. A linear regression analysis between the bottom depth and the spectral reflectance in the different satellite sensor channels is used in order to test the correlation between these two variables. If a relationship exists, the reflectances have to be corrected. This procedure and the elimination of the bottom influence will be explained for specific satellite systems.     

New algorithms of the Q-learning type

We propose two algorithms for Q-learning that use the two-timescale stochastic approximation methodology. The first of these updates Q-values of all feasible state-action pairs at each instant while the second updates Q-values of states with actions chosen according to the ‘current’ randomized policy updates. A proof of convergence of the algorithms is shown. Finally, numerical experiments using the proposed algorithms on an application of routing in communication networks are presented on a few different settings.