MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes

Chlorophyll-a (Chla) concentrations and ‘water-leaving’ reflectance were assessed along transects in Keweenaw Bay (Lake Superior) and in Green Bay (Lake Michigan) (two of the Laurentian Great Lakes, USA), featuring oligotrophic (0.4–0.8 mg Chla m^? 3) and eutrophic to hyper-eutrophic waters (11–131 mg Chla m^? 3), respectively. A red-to-NIR band Chla retrieval algorithm proved to be applicable to Green Bay, but gave mostly negative values for Keweenaw Bay. An alternative algorithm could be based on Chla fluorescence, which in Keweenaw Bay was indicated by enhanced reflectance near 680 nm. Bands 7, 8 and 9 of the Medium Resolution Imaging Spectrometer (MERIS) have been specifically designed to detect phytoplankton fluorescence in coastal waters. A quite strong linear relationship was found between Chla concentration and fluorescence line height (FLH) computed with these MERIS bands. The same relationship held for observations on oligotrophic waters elsewhere, but not for Green Bay, where the FLH diminished to become negative as Chla increased. The remote sensing application of the algorithms could be tested because a MERIS scene was acquired coinciding with the day of the field observations in Keweenaw Bay and one day after those in Green Bay. For Green Bay the pixel values from the red-to-NIR band algorithm compared well to the steep Chla gradient in situ. This result is very positive from the perspective of satellite use in monitoring eutrophic inland and coastal waters in many parts of the world. Implementation of the FLH relationship in the scene of Keweenaw Bay produced highly variable pixel values. The FLH in oligotrophic inland waters like Lake Superior appears to be very close to or below the MERIS detection limit. An empirical algorithm incorporating three MERIS bands in the blue-to-green spectral region might be used as an alternative, but its applicability to other regions and seasons remains to be verified. Moreover, none of the algorithms will be suitable for mesotrophic water bodies. The results indicate that Chla mapping in oligotrophic and mesotrophic areas of the Great Lakes remains problematic for the current generation of satellite sensors.     

Assessing the potential of SeaWiFS and MODIS for estimating chlorophyll concentration in turbid productive waters using red and near-infrared bands

Bio-optical algorithms for remote estimation of chlorophyll-a concentration (Chl) in case-1 waters exploit the upwelling radiation in the blue and green spectral regions. In turbid productive waters other constituents, that vary independently of Chl, absorb and scatter light in these spectral regions. As a consequence, the accurate estimation of Chl in turbid productive waters has so far not been feasible from satellite sensors. The main purpose of this study was to evaluate the extent to which near-infrared (NIR) to red reflectance ratios could be applied to the Sea Wide Field-of-View Sensor (SeaWiFS) and the Moderate Imaging Spectrometer (MODIS) to estimate Chl in productive turbid waters. To achieve this objective, remote-sensing reflectance spectra and relevant water constituents were collected in 251 stations over lakes and reservoirs with a wide variability in optical parameters (i.e. 4 ≤ Chl ≤ 240 mg m^− 3; 18 ≤ Secchi disk depth ≤ 308 cm). SeaWiFS and MODIS NIR and red reflectances were simulated by using the in-situ hyperspectral data. The proposed algorithms predicted Chl with a relative random uncertainty of approximately 28% (average bias between − 1% and − 4%). The effects of reflectance uncertainties on the predicted Chl were also analyzed. It was found that, for realistic ranges of R_rs uncertainties, Chl could be estimated with a precision better than 40% and an accuracy better than ± 35%. These findings imply that, provided that an atmospheric correction scheme specific for the red-NIR spectral region is available, the extensive database of SeaWiFS and MODIS images could be used to quantitatively monitor Chl in turbid productive waters.     

Use of satellite images of chlorophyll fluorescence to monitor the spring bloom in coastal waters

This article demonstrates a successful application of fluorescence line height (FLH) images from the Medium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagers and provides a strong argument for making more widespread use of FLH in monitoring surface phytoplankton in coastal waters. In the present example, MERIS and MODIS FLH images show the start of the spring bloom in coastal waters of the Strait of Georgia in British Columbia, Canada. The images clearly show a recurring pattern in five of the eight years from 2003 to 2010 covered by MERIS, which suggests seeding of the early spring bloom from narrow coastal inlets. Such seeding has been suggested before, but never observed. FLH images show the blooms more clearly than images of surface chlorophyll based on the ratios of water-leaving radiances in the blue and green spectral range (440–560 nm). FLH images used here have been derived with no atmospheric correction. Alternative products based on the blue/green ratio require atmospheric correction, which is difficult in coastal areas. Such products also tend to be more significantly confused with other constituents of coastal waters.     

Validation of daily MODIS snow cover maps of the Upper Rio Grande River Basin for the 2000-2001 snow year

Snow cover represents an important water resource for the Upper Rio Grande River Basin of Colorado and New Mexico. Accuracy assessment of MODIS snow products was accomplished using Geographic Information System (GIS) techniques. Daily snow cover maps produced from Moderate Resolution Imaging Spectroradiometer (MODIS) data were compared with operational snow cover maps produced by the National Operational Hydrologic Remote Sensing Center (NOHRSC) and against in situ Snowpack Telemetry (SNOTEL) measurements for the 2000-2001 snow season. Over the snow season, agreement between the MODIS and NOHRSC snow maps was high with an overall agreement of 86%. However, MODIS snow maps typically indicate a higher proportion of the basin as being snow-covered than do the NOHRSC snow maps. In particular, large tracts of evergreen forest on the western slopes of the San de Cristo Range, which comprise a large portion of the eastern margin of the basin, are more consistently mapped as snow-covered in the MODIS snow products than in the NOHRSC snow products. NOHRSC snow maps, however, typically indicate a greater proportion of the central portion of the basin, predominately in cultivated areas, as snow. Comparisons of both snow maps with in situ SNOTEL measurements over the snow season show good overall agreement with overall accuracies of 94% and 76% for MODIS and NOHRSC, respectively. A lengthened comparison of MODIS against SNOTEL sites, which increases the number of comparisons of snow-free conditions, indicates a slightly lower overall classification accuracy of 88%. Errors in mapping extra snow and missing snow by MODIS are comparable, with MODIS missing snow in approximately 12% of the cases and mapping too much snow in 15% of the cases. The majority of the days when MODIS fails to map snow occurs at snow depths of less than 4 cm.     

A simple semi-analytical model for remote estimation of chlorophyll-a in turbid waters: Validation

Accurate assessment of phytoplankton chlorophyll-a (chla) concentrations in turbid waters by means of remote sensing is challenging due to the optical complexity of case 2 waters. We have applied a recently developed model of the form [R_rs^? 1(λ₁) ? R_rs^? 1(λ₂)] × R_rs(λ₃) where R_rs(λ_i) is the remote-sensing reflectance at the wavelength λ_i, for the estimation of chla concentrations in turbid waters. The objectives of this paper are (a) to validate the three-band model as well as its special case, the two-band model R_rs^? 1(λ₁) × R_rs(λ₃), using datasets collected over a considerable range of optical properties, trophic status, and geographical locations in turbid lakes, reservoirs, estuaries, and coastal waters, and (b) to evaluate the extent to which the three-band model could be applied to the Medium Resolution Imaging Spectrometer (MERIS) and two-band model could be applied to the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate chla in turbid waters.The three-band model was calibrated and validated using three MERIS spectral bands (660–670 nm, 703.75–713.75 nm, and 750?757.5 nm), and the 2-band model was tested using two MODIS spectral bands (λ₁ = 662–672, λ₃ = 743–753 nm). We assessed the accuracy of chla prediction in four independent datasets without re-parameterization (adjustment of the coefficients) after initial calibration elsewhere. Although the validation data set contained widely variable chla (1.2 to 236 mg m^? 3), Secchi disk depth (0.18 to 4.1 m), and turbidity (1.3 to 78 NTU), chla predicted by the three-band algorithm was strongly correlated with observed chla (r² > 0.96), with a precision of 32% and average bias across data sets of ? 4.9% to 11%. Chla predicted by the two-band algorithm was also closely correlated with observed chla (r² > 0.92); however, the precision declined to 57%, and average bias across the data sets was 18% to 50.3%. These findings imply that, provided that an atmospheric correction scheme for the red and NIR bands is available, the extensive database of MERIS and MODIS imagery could be used for quantitative monitoring of chla in turbid waters.     

Validation of a synthetic chlorophyll index for remote estimates of chlorophyll-a in a turbid hypereutrophic lake

Remote sensing techniques can offer powerful tools for measuring concentrations of chlorophyll-a (chl-a), which is an important proxy for water quality. However, remote estimates of chl-a can be difficult in water bodies that have high levels of total suspended matter (TSM). In this study, we examined the applicability of the synthetic chlorophyll index (SCI) and a parameter relevant to chlorophyll pigments (H_chl) used in conjunction with remote-sensing data to predict chl-a concentrations (C_chl-a) in Taihu Lake, a highly turbid hypereutrophic lake in eastern China. We sampled water quality and surface spectral properties at 250 field stations throughout the lake over five sampling periods spanning 2 years. Because data acquired at 31 stations could not be used due to equipment failure or blue-green algal blooms, we used data acquired at the remaining 219 stations. We then randomly selected parts of the spectral properties data (N = 164) to calibrate bands used in the SCI algorithm and established cubic polynomial models to estimate C_chl-a with SCI and H_chl as the independent variables. We evaluated the accuracy of these models using data from the remaining 55 stations that were not used for calibration. Our results showed the following trends: (1) the parameter of H_chl performed better than SCI in estimating C_chla in Taihu Lake; (2) H_chl showed optimal performance in winter, average performance in spring, and poor performance in summer and autumn; (3) H_chl was appropriate for the NAP-dominant waters with high C_TSM and low C_chl-a, but was not suitable for organism-dominant waters with low C_TSM; and (4) in short, H_chl had limited usability in turbid and eutrophic waters.     

Parameterization of the chlorophyll a-specific in vivo light absorption coefficient covering estuarine,coastal and oceanic waters

We evaluated models predicting the spectral chlorophyll-a (Chl a)-specific absorption coefficient (a* _ph (λ)) from Chl a concentration [Chl a] on the basis of 465 phytoplankton absorption spectra collected in estuarine, coastal and oceanic waters. A power model on ln-transformed data provided the best model fit compared to a power model on non-transformed data previously applied to parameterize the relationship between a* _ph (λ) and [Chl a]. The variation in a* _ph (λ) was parameterized over four orders of magnitude in [Chl a] (0.01-100 mg Chl a m^?3) producing a 13-fold range in a* _ph (0.19 to 0.015 m² mg^?1 Chl a) at 440 nm, the peak absorption of Chl a in the blue part of the spectrum. The variations in the modelled a* _ph spectra were within realistic predictions of a* _ph (λ) and the model satisfactorily reproduced the spectral flattening with increasing [Chl a]. The parameterization of a* _ph (λ) confirmed the indirect dependency of a* _ph (λ) on [Chl a] through co-variations between [Chl a] with pigment packaging and pigment composition. Although pigment packaging determined the spectral flattening, analysis of absorption ratios revealed a systematic change in pigment composition with profound influence on the variability of a* _ph in the 440 to 495 nm region. Modelled spectra deviated by approximately 20% from the measured spectra on average and model accuracy was independent of [Chl a]. Although the model cannot fully replace spectral measurements of phytoplankton absorption, it does permit realistic reconstructions of a* _ph (λ) from simple measurements of [Chl a] sampled in estuarine, coastal and oceanic waters.     

Remote estimation of chlorophyll a in optically complex waters based on optical classification

Accurate assessment of phytoplankton chlorophyll a (Chla) concentration in turbid waters by means of remote sensing is challenging due to optically complexity and significant variability of case 2 waters, especially in inland waters with multiple optical types. In this study, a water optical classification algorithm is developed, and two semi-analytical algorithms (three- and four-band algorithm) for estimating Chla are calibrated and validated using four independent datasets collected from Taihu Lake, Chaohu Lake, and Three Gorges Reservoir. The optical classification algorithm is developed using the dataset collected in Taihu Lake from 2006 to 2009. This dataset is also used to calibrate the three- and four-band Chla estimation algorithms. The optical classification technique uses remote sensing reflectance at three bands: Rrs(G), Rrs(650), and Rrs(NIR), where G indicates the location of reflectance peak in the green region (around 560 nm), and NIR is the location of reflectance peak in the near-infrared region (around 700 nm). Optimal reference wavelengths of the three- and four-band algorithm are located through model tuning and accuracy optimization. The three- and four-band algorithm accuracy is further evaluated using other three independent datasets. The improvement of optical classification in Chla estimation is revealed by comparing the performance of the two algorithms for non-classified and classified waters.Using the slopes of the three reflectance bands, the 138 reflectance spectra samples in the calibration dataset are classified into three classes, each with a specific spectral shape character. The three- and four-band algorithm performs well for both non-classified and classified waters in estimating Chla. For non-classified waters, strong relationships are yielded between measured and predicted Chla, but the performance of the two algorithms is not satisfactory in low Chla conditions, especially for samples with Chla below 30 mg m^− 3. For classified waters, the class-specific algorithms perform better than for non-classified waters. Class-specific algorithms reduce considerable mean relative error from algorithms for non-classified waters in Chla predicting. Optical classification makes that there is no need to adjust the optimal position to estimate Chla for other waters using the class-specific algorithms. The findings in this study demonstrate that optical classification can greatly improve the accuracy of Chla estimation in optically complex waters.     

Validation of MERIS ocean-color products in the Bohai Sea: A case study for turbid coastal waters

An extensive in situ data set in the Bohai Sea of China was collected to assess radiometric properties and concentrations of ocean constituents derived from Medium Resolution Imaging Spectrometer (MERIS). The data collected include spectral normalized water-leaving radiance L_wn(λ) and concentrations of suspended particulate matter (SPM) and chlorophyll a (Chl-a). A strict spatio-temporal match-up method was adopted in view of the complexity and variability of the turbid coastal area, resulting in 13, 48 and 18 match-ups for MERIS L_wn(λ), SPM and Chl-a estimates, respectively. For MERIS L_wn(λ), the match-ups showed mean absolute percentage differences (APD) of 17%-20% in the 412, 443, 620 and 665 nm bands, whereas L_wn(λ) at bands from 490 and 560 nm had better APD of 15-16%. The band ratio of L_wn(490) to L_wn(560) of the satellite data was in good agreement with in situ observations with an APD of 4%. MERIS SPM and Chl-a products overestimated the in situ values, with the APD of approximately 50% and 60%, respectively. When match-up criteria were relaxed, the assessment results degraded systematically. Hence, in turbid coastal areas where temporal variability and spatial heterogeneity of bio-optical properties may be pronounced as the result of terrestrial influences and local dynamics, the strict spatio-temporal match-up is recommended.     

Validation of SeaWiFS chlorophyll a concentrations in the Southern Ocean: A revisit

Surface chlorophyll a concentrations (C_a, mg m^− 3) in the Southern Ocean estimated from SeaWiFS satellite data have been reported in the literature to be significantly lower than those measured from in situ water samples using fluorometric methods. However, we found that high-resolution (∼ 1 km²/pixel) daily SeaWiFS C_a (C_a^SWF) data (SeaDAS4.8, OC4v4 algorithm) was an accurate measure of in situ C_a during January-February of 1998-2002 if concurrent in situ data measured by HPLC (C_a^HPLC) instead of fluorometric (C_a^Fluor) measurements were used as ground truth. Our analyses indicate that C_a^Fluor is 2.48 ± 2.23 (n = 647) times greater than C_a^HPLC between 0.05 and 1.5 mg m^− 3 and that the percentage overestimation of in situ C_a by fluorometric measurements increases with decreasing concentrations. The ratio of C_a^SWF/C_a^HPLC is 1.12 ± 0.91 (n = 96), whereas the ratio of C_a^SWF/C_a^Fluor is 0.55 ± 0.63 (n = 307). Furthermore, there is no significant bias in C_a^SWF (12% and − 0.07 in linear and log-transformed C_a, respectively) when C_a^HPLC is used as ground truth instead of C_a^Fluor. The high C_a^Fluor/C_a^HPLC ratio may be attributed to the relatively low concentrations of chlorophyll b (C_b/C_a = 0.023 ± 0.034, n = 482) and relatively high concentrations of chlorophyll c (C_c/C_a = 0.25 ± 0.59, n = 482) in the phytoplankton pigment composition when compared to values from other regions. Because more than 90% of the waters in the study area, as well as in the entire Southern Ocean (south of 60° S), have C_a^SWF between 0.05 and 1.5 mg m^− 3, we consider that the SeaWiFS performance of C_a retrieval is satisfactory and for this C_a range there is no need to further develop a “regional” bio-optical algorithm to account for the previous SeaWiFS “underestimation”.     

Atmospheric correction of ENVISAT/MERIS data over inland waters: Validation for European lakes

Traditional methods for aerosol retrieval and atmospheric correction of remote sensing data over water surfaces are based on the assumption of zero water reflectance in the near-infrared. Another type of approach which is becoming very popular in atmospheric correction over water is based on the simultaneous retrieval of atmospheric and water parameters through the inversion of coupled atmospheric and bio-optical water models. Both types of approaches may lead to substantial errors over optically-complex water bodies, such as case II waters, in which a wide range of temporal and spatial variations in the concentration of water constituents is expected. This causes the water reflectance in the near-infrared to be non-negligible, and that the water reflectance response under extreme values of the water constituents cannot be described by the assumed bio-optical models. As an alternative to these methods, the SCAPE-M atmospheric processor is proposed in this paper for the automatic atmospheric correction of ENVISAT/MERIS data over inland waters. A-priori assumptions on the water composition and its spectral response are avoided by SCAPE-M by calculating reflectance of close-to-land water pixels through spatial extension of atmospheric parameters derived over neighboring land pixels. This approach is supported by the results obtained from the validation of SCAPE-M over a number of European inland water validation sites which is presented in this work. MERIS-derived aerosol optical thickness, water reflectance and water pigments are compared to in-situ data acquired concurrently to MERIS images in 20 validation match-ups. SCAPE-M has also been compared to specific processors designed for the retrieval of lake water constituents from MERIS data. The performance of SCAPE-M to reproduce ground-based measurements under a range of water types and the ability of MERIS data to monitor chlorophyll-a and phycocyanin pigments using semiempirical algorithms after SCAPE-M processing are discussed. It has been found that SCAPE-M is able to provide high accurate water reflectance over turbid waters, outperforming models based on site-specific bio-optical models, although problems of SCAPE-M to cope with clear waters in some cases have also been identified.     

Bio-optical properties of east coast Malaysia waters in relation to remote sensing of chlorophyll

Surface water samples collected during the monsoon and inter-monsoon seasons of 2009 off the east coast of Peninsular Malaysia have been analysed for concentrations of total chlorophyll, suspended particulates and coloured dissolved organic matter (CDOM). Spectral absorption coefficients of dissolved and particulate materials have also been measured. Significant seasonal variabilities in concentrations and optical properties were reported with high concentrations of all parameters during the northeast monsoon (NEM) season and low during the southwest monsoon (SWM) and inter-monsoon seasons. Contrary to previous reports on the oligotrophic nature of the waters during the inter-monsoon season, relatively high concentrations of chlorophyll (>3 mg m^?3) were observed at offshore stations in the study area in the spring and fall inter-monsoon months. The chlorophyll-specific absorption spectrum changes with the seasons with the greatest absorption per unit chlorophyll during the SWM and the least during the inter-monsoon seasons, probably in response to seasonal changes in phytoplankton community and cell size structure. The water is classified as optical case 2. At the blue end of the spectrum (440 nm), light absorption by non-phytoplankton materials (CDOM and detritus) accounts for nearly 70% of the total non-water absorption regardless of the season. At the wavelength (676 nm) of the secondary chlorophyll absorption peak in the red part of the spectrum, light absorption by chlorophyll contributes 80–90% to total non-water absorption at most stations and this may provide the basis for remote sensing of phytoplankton chlorophyll in these waters.     

Spectral optimization for constituent retrieval in Case 2 waters II: Validation study in the Chesapeake Bay

Coastal waters (Case 2) are generally more optically complex than oceanic waters and contain much higher quantities of colored detrital matter (CDM, a combination of dissolved organic matter and detrital particulates) as well as suspended sediment. Exclusion of CDM in the retrieval can lead to an overestimation of chlorophyll a concentration (C). We present a validation of a Case 2 version of the coupled spectral optimization algorithm (SOA) for simultaneous atmospheric correction and water parameter retrieval using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite ocean color data. Modeling of water constituents uses the Garver, Siegel and Maritorena (GSM) semi-analytic bio-optical model locally tuned for Chesapeake Bay. This includes a parameterization for CDM through its absorption spectrum.SOA-retrieved C and CDM are compared with in situ measurements in Chesapeake Bay. Results are also compared with output from two alternate models 1) the standard algorithm (Std) and 2) the standard atmospheric correction combined with the locally tuned GSM model (StdGSM). The comparisons indicate that the SOA is a viable alternative to both given models in Chesapeake Bay. In contrast, StdGSM appears to require improvement before it can be considered for operational use in these waters. Perhaps the most important result is the high-quality of CDM retrievals with the SOA. They suggest that there is value added using the SOA method in Chesapeake waters, as the Std method does not retrieve CDM. In a companion paper we describe in detail the model implementation, and its accuracy and limitations when applied to the Chesapeake Bay.     

Detection of algal blooms in European waters based on satellite chlorophyll data from MERIS and MODIS

A technique for algal-bloom detection in European waters is described, based on standard chlorophyll a concentration (Chl) data from two ocean-colour sensors, the Moderate Resolution Imaging Spectroradiometer (MODIS) and Medium Resolution Imaging Spectrometer (MERIS). Comparison of the two data sources shows good agreement in case 1 waters, whereas the difference is significant in coastal waters including turbid areas. A relationship between the water-leaving reflectance at 667 nm and Chl for case 1 waters was used to eliminate pixels where Chl retrieval is contaminated by backscatter from inorganic suspended matter. Daily Chl data are compared to a predefined threshold map to determine whether an algal bloom has occurred. In this study, a threshold map was defined as the 90th percentile of previous years' data to take account of regional differences in typical Chl levels, with separate maps for each sensor to take account of sensor-specific bias. The algal-bloom detection processing chain is described, and example results are presented.     

Multitemporal assessment of the geomorphologic evolution of the Restinga of Marambaia,Rio de Janeiro,Brazil

The Restinga of Marambaia is an emerged sand bar located between the Sepetiba Bay and the South Atlantic Ocean, on the south‐east coast of Brazil. The objective of this study was to observe the geomorphologic evolution of the coastal zone of the Restinga of Marambaia using multitemporal satellite images acquired by multisensors from 1975 to 2004. The images were digitally segmented by a region growth algorithm and submitted to an unsupervised classification procedure (ISOSEG) followed by a raster edit based on visual interpretation. The image time‐series showed a general trend of decrease in the total sand bar area with values varying from 80.61 km² in 1975 to 78.15 km² in 2004. The total area calculation based on the 1975 and 1978 Landsat MSS data was shown to be super‐estimated in relation to the Landsat TM, Landsat ETM+, and CBERS‐2 CCD data. These differences can also be associated to the relatively poorer spatial resolution of the MSS data, nominally 79 m, against the 20 m of the CCD data and 30 m of the TM and ETM+ data. For the estimates of the width in the central portion of the sand bar the variation was from 158 m (1975) to 100 m (2004). The formation of a spit in the northern region of the study area was visually observed. The area of the spit was estimated, with values varying from 0.82 km² (1975) to 0.55 km² (2004).     

Airborne remote sensing of chlorophyll content under cloudy sky as applied to the tropical waters in the Gulf of Guinea

A special radiometer has been constructed to perform aerial measurements of ocean color in order to obtain the chlorophyll content of ocean water. This radiometer measures the spectral albedo at four wavelengths (466, 525, 550 and 600 nm) and was used during fourteen flights over the Gulf of Guinea in June and July of 1975. All measurements were performed from 150 m altitude. The acquisition of measurements independent of cloud cover was made possible by the calculation of differences between albedos at different wavelengths. Differences between albedos were mapped after each flight, and showed the detailed structure of a thermal front due to coastal upwellings. A theoretical interpretation, based on computations of radiative transfer in the ocean, shows that the difference of albedos at 466 and 525 nm is very sensitive to chlorophyll content, whereas the difference of albedos at 550 and 600 nm is sensitive to the presence of light scattering particles.     

Comparison of MERIS,MODIS, SeaWiFS-derived particulate organic carbon,and in situ measurements in the South China Sea

Medium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) particulate organic carbon (POC) concentration products for the South China Sea (SCS) were compared with in situ data collected from October 2007 to December 2013. Spectral remote-sensing reflectance (R_rs,λ) was also measured to help understand POC algorithm performance. A strict comparison of the satellite-derived POC and in situ measurements showed that MERIS, MODIS, and SeaWiFS underestimated in situ values by 29.1, 11.7, and 31.5%, respectively. Similar results were obtained with a relaxed matching criterion. Through analysis of the causes of product uncertainty, the results suggested that satellite retrieval of R_rs,λ and the global POC algorithm both have an impact on inversion accuracy. However, the formulation of the POC algorithm seems to be more critical. When a regional algorithm was developed to obtain satellite-derived POC, both the strict and relaxed comparison results showed significant improvement, but for coastal waters, both algorithms had larger errors. Other factors affecting the comparison are also discussed.     

Applications of a New Property of Conics to Architecture: An Alternative Design Project for Rio de Janeiro Metropolitan Cathedral

This paper describes the mathematical discovery of a new property of conics which allows the development of numerous geometric projects for use in architectural and engineering applications. Illustrated is an architectural application in the form of an alternative project for Río de Janeiro Metropolitan Cathedral featuring the integration of a circular base and a cross in the top plane. Two alternative designs are presented for the cathedral, based on the choice of either the Latin Immisa or Greek cross.