An assessment of the black ocean pixel assumption for MODIS SWIR bands

Recent studies show that an atmospheric correction algorithm using shortwave infrared (SWIR) bands improves satellite-derived ocean color products in turbid coastal waters. In this paper, the black pixel assumption (i.e., zero water-leaving radiance contribution) over the ocean for the Moderate Resolution Imaging Spectroradiometer (MODIS) SWIR bands at 1240, 1640, and 2130 nm is assessed for various coastal ocean regions. The black pixel assumption is found to be generally valid with the MODIS SWIR bands at 1640 and 2130 nm even for extremely turbid waters. For the MODIS 1240 nm band, however, ocean radiance contribution is generally negligible in mildly turbid waters such as regions along the U.S. east coast, while some slight radiance contributions are observed in extremely turbid waters, e.g., some regions along the China east coast, the estuary of the La Plata River. Particularly, in the Hangzhou Bay, the ocean radiance contribution at the SWIR band 1240 nm results in an overcorrection of atmospheric and surface effects, leading to errors of MODIS-derived normalized water-leaving radiance at the blue reaching ~ 0.5 mW cm^− 2 μm^− 1 sr^− 1. In addition, we found that, for non-extremely turbid waters, i.e., the ocean contribution at the near-infrared (NIR) band < ~ 1.0 mW cm^− 2 μm^− 1 sr^− 1, there exists a good relationship in the regional normalized water-leaving radiances between the red and the NIR bands. Thus, for non-extremely turbid waters, such a red-NIR radiance relationship derived regionally can possibly be used for making corrections for the regional NIR ocean contributions without using the SWIR bands, e.g., for atmospheric correction of ocean color products derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS).     

Atmospheric correction based on inherent optical properties of sea water at NIR wavelengths combined with an automated aerosol spectra determination (ASD) technique

Atmospheric correction is the process whereby atmospheric effects on sensor-recorded radiance are removed and the surface radiance is estimated. Atmospheric effects due to gaseous absorption, molecular scattering – and their seasonal as well as latitudinal variations – can be adequately accounted for by using pre-computed look-up tables. However, scattering by aerosol particles is difficult to correct. At-sensor radiance at near-infrared (NIR) wavelengths, after being corrected for gaseous absorption and molecular scattering, was assumed (in standard atmospheric correction) to have been entirely due to aerosol scattering and was used to calculate the aerosol parameters. This assumption, although valid for open ocean clear waters, is not valid for turbid waters due to scattering by suspended particles in the water, which results in an appreciable amount of water-leaving radiance in the NIR region. A new turbid water atmospheric correction scheme is described here for Oceansat-2 Ocean Colour Monitor (OCM-2) data based on inherent optical properties (IOPs) of sea water at NIR, and obtaining an accurate spectral profile of aerosol radiance.     

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.     

Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters

Mapping of total suspended matter concentration (TSM) can be achieved from space-based optical sensors and has growing applications related to sediment transport. A TSM algorithm is developed here for turbid waters, suitable for any ocean colour sensor including MERIS, MODIS and SeaWiFS. Theory shows that use of a single band provides a robust and TSM-sensitive algorithm provided the band is chosen appropriately. Hyperspectral calibration is made using seaborne TSM and reflectance spectra collected in the southern North Sea. Two versions of the algorithm are considered: one which gives directly TSM from reflectance, the other uses the reflectance model of Park and Ruddick (2005) to take account of bidirectional effects.Applying a non-linear regression analysis to the calibration data set gave relative errors in TSM estimation less than 30% in the spectral range 670-750 nm. Validation of this algorithm for MODIS and MERIS retrieved reflectances with concurrent in situ measurements gave the lowest relative errors in TSM estimates, less than 40%, for MODIS bands 667 nm and 678 nm and for MERIS bands 665 nm and 681 nm. Consistency of the approach in a multisensor context (SeaWiFS, MERIS, and MODIS) is demonstrated both for single point time series and for individual images.     

Remote-sensing reflectance characteristics of highly turbid estuarine waters – a comparative experiment of the Yangtze River and the Yellow River

An outdoor tank experiment is carried out to analyse the interrelationships between remote-sensing reflectance and sediment characteristics in the highly turbid waters of the Yangtze River and the Yellow River estuaries. The results show that the sensitivity of remote-sensing reflectance to water turbidity is inversely related to suspended sediment concentration (SSC). SSC estimation in the highly turbid waters (SSC > 0.15 g l^?1) is best achieved by using ocean colour ratios, especially the ratio at 810 nm: 700 nm. The effect of particle size of suspended sediment matter (SSM) on the observed remote-sensing reflectance is significant and depends on wavelengths and a SSC range. The mineral composition of SSM has a weak effect on observed reflectance in comparison to that of particle size.     

Satellite observations of optical and biological properties in the Korean dump site of the Yellow Sea

With the standard near-infrared (NIR) atmospheric correction algorithm for ocean color data processing, a high chlorophyll-a concentration patch was consistently observed from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua platform in the middle of the Yellow Sea during the spring (end of March to early May). This prominent patch was not observed in the historical ocean color satellite imageries in late 1970s to early 1980s, and a location corresponding to this patch has been used as a Korean dump site since 1988. At the same time, MODIS chlorophyll-a concentrations derived using the shortwave infrared (SWIR) atmospheric correction algorithm developed for the ocean color satellite data in turbid coastal or high-productive ocean waters were significantly reduced.Comparison between in situ and MODIS chlorophyll-a measurements shows that the chlorophyll-a from the MODIS-Aqua products using the standard-NIR atmospheric correction algorithm is significantly overestimated. The images of the MODIS-derived normalized water-leaving radiance spectra and water diffuse attenuation coefficient data using the NIR-SWIR-based atmospheric correction approach show that absorption and scattering by organic and inorganic matter dumped in the Korean dump site have strongly influenced the satellite-derived chlorophyll-a data. Therefore, the biased high chlorophyll-a patch in the region is in fact an overestimation of chlorophyll-a values due to large errors from the standard-NIR atmospheric correction algorithm. Using the NIR-SWIR algorithm for MODIS-Aqua ocean color data processing, ocean color products from 2002 to 2008 for the Korean dump site region have been generated and used for characterizing the ocean optical and biological properties. Results show that there have been some important changes in the seasonal and interannual variations of phytoplankton biomass and other water optical and biological properties induced by colored dissolved organic matters, as well as suspended sediments.     

Detection and correction of adjacency effects in hyperspectral airborne data of coastal and inland waters: the use of the near infrared similarity spectrum

A method for the detection and correction of water pixels affected by adjacency effects is presented. The approach is based on the comparison of spectra with the near infrared (NIR) similarity spectrum. Pixels affected by adjacency effects have a water-leaving reflectance spectrum with a different shape to the reference spectrum. This deviation from the similarity spectrum is used as a measure for the adjacency effect. Secondly, the correspondence with the NIR similarity spectrum is used to quantify and to correct for the contribution of the background radiance during atmospheric correction. The advantage of the approach is that it requires no a priori assumptions on the sediment load or related reflectance values in the NIR and can therefore be applied to turbid waters. The approach is tested on hyperspectral airborne data (Compact Airborne Spectrographic Imager (CASI), Airborne Hyperspectral Scanner (AHS)) acquired above coastal and inland waters at different flight altitudes and under varying atmospheric conditions. As the NIR similarity spectrum forms the basis of the approach, the method will fail for water bodies for which this similarity spectrum is no longer valid.     

Detection of turbid waters and absorbing aerosols for the MODIS ocean color data processing

Atmospheric correction for the ocean color products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) uses two near-infrared (NIR) bands centered at 748 and 869 nm for identifying aerosol type and correcting aerosol contributions at the MODIS visible wavelengths. The ocean is usually assumed to be black for open oceans at these two NIR bands with modifications for the productive waters and aerosols are assumed to be non- or weakly absorbing. For cases with strongly absorbing aerosols and cases with the significant NIR ocean contributions, the derived ocean color products will have significant errors, e.g., the derived MODIS normalized water-leaving radiances are biased low considerably. Both cases lead to a significant drop of the sensor-measured radiance at the short visible wavelengths, and they both have similar and indistinguishable radiance characteristics at the short visible wavelengths. To properly handle such cases, the strongly absorbing aerosols and turbid waters need to be identified. Therefore, an appropriate approach (different from the standard procedure) may be carried out. In this paper, we demonstrate methods to identify the turbid waters and strongly absorbing aerosols using combinations of MODIS-measured radiances at the short visible, NIR, and short wave infrared (SWIR) bands. The algorithms are based on the fact that for the turbid waters the ocean has significantly large contributions at the NIR bands, whereas at the SWIR bands the ocean is still black due to much stronger water absorption. With detection of the turbid waters, the strongly absorbing aerosols can then be identified using the MODIS measurements at the short visible and NIR bands. We provide results and discussions for test and evaluation of the algorithm performance with various examples in the coastal regions for the turbid waters and for various absorbing aerosols (e.g., volcano ash plumes, dust, smoke). The proposed algorithms are efficient in the data processing, and can be carried out prior to the atmospheric correction procedure.     

Assessment of the MCC method to estimate sea surface currents in highly turbid coastal waters from GOCI

Previous studies have demonstrated that the Geostationary Ocean Colour Imager (GOCI) could retrieve sea surface currents accurately in low-moderate turbid coastal waters, based on maximum cross-correlation (MCC) technique. However, its performance in highly turbid waters remains unclear. In this study, the MCC method is used to derive hourly sea surface currents in Hangzhou Bay (HZB) with highly turbid waters from the GOCI data, and its performance is examined by in situ measurements and model simulations. The results show that the GOCI-derived sea surface currents can catch tidal phase variations well, yet the performance of the derived velocity is not as good as the previous studies in low-moderate turbid waters. The reason may be due to the rapid deposition and resuspension processes of suspended particulate matter in high turbidity waters, which contaminate the MCC pattern tracking. The GOCI-derived deposition and resuspension rates can reach up to about 190 and 270 mg l^–1 h^–1 in HZB, respectively, which demonstrates that the potential of geostationary ocean colour imagery in deriving the suspended particle deposition and resuspension rates.     

A reflectance band ratio used to estimate suspended matter concentrations in sediment-dominated coastal waters

This letter presents an empirical relationship that may be used to estimate the suspended particulate matter concentrations in highly turbid waters from remote sensing reflectance measurements. Numerous measurements carried out in the Gironde estuarine waters (France) in 2000 and 2001 are presented and analysed. It was observed that the near-infrared (850 nm) reflectance was weakly correlated with the total suspended matter concentration ( TSMc ) measured in surface waters. A strong correlation ( r =0.91) was obtained between the ratio of the near-infrared and visible (550 nm) reflectance and TSMc, which could provide an accurate calibration curve for data from Systeme Probatoire de l'Observation de la Terre (SPOT), Landsat and Indian Remote Sensing (IRS) satellite sensors. The reflectance ratio reduced the effects of changes in illumination conditions and sediment type (grain-size, refractive index). The calibration function obtained, successfully applied to the Gironde, should be applied in other sedimentdominated coastal waters.     

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.     

Comparison of three SeaWiFS atmospheric correction algorithms for turbid waters using AERONET-OC measurements

The use of satellites to monitor the color of the ocean requires effective removal of the atmospheric signal. This can be performed by extrapolating the aerosol optical properties in the visible from the near-infrared (NIR) spectral region assuming that the seawater is totally absorbant in this latter part of the spectrum. However, the non-negligible water-leaving radiance in the NIR which is characteristic of turbid waters may lead to an overestimate of the atmospheric radiance in the whole visible spectrum with increasing severity at shorter wavelengths. This may result in significant errors, if not complete failure, of various algorithms for the retrieval of chlorophyll-a concentration, inherent optical properties and biogeochemical parameters of surface waters.This paper presents results of an inter-comparison study of three methods that compensate for NIR water-leaving radiances and that are based on very different hypothesis: 1) the standard SeaWiFS algorithm (Stumpf et al., 2003; Bailey et al., 2010) based on a bio-optical model and an iterative process; 2) the algorithm developed by Ruddick et al. (2000) based on the spatial homogeneity of the NIR ratios of the aerosol and water-leaving radiances; and 3) the algorithm of Kuchinke et al. (2009) based on a fully coupled atmosphere-ocean spectral optimization inversion. They are compared using normalized water-leaving radiance nL_w in the visible. The reference source for comparison is ground-based measurements from three AERONET-Ocean Color sites, one in the Adriatic Sea and two in the East Coast of USA.Based on the matchup exercise, the best overall estimates of the nL_w are obtained with the latest SeaWiFS standard algorithm version with relative error varying from 14.97% to 35.27% for λ = 490 nm and λ = 670 nm respectively. The least accurate estimates are given by the algorithm of Ruddick, the relative errors being between 16.36% and 42.92% for λ = 490 nm and λ = 412 nm, respectively. The algorithm of Kuchinke appears to be the most accurate algorithm at 412 nm (30.02%), 510 (15.54%) and 670 nm (32.32%) using its default optimization and bio-optical model coefficient settings.Similar conclusions are obtained for the aerosol optical properties (aerosol optical thickness τ(865) and the Ångström exponent, α(510, 865)). Those parameters are retrieved more accurately with the SeaWiFS standard algorithm (relative error of 33% and 54.15% for τ(865) and α(510, 865)).A detailed analysis of the hypotheses of the methods is given for explaining the differences between the algorithms. The determination of the aerosol parameters is critical for the algorithm of Ruddick et al. (2000) while the bio-optical model is critical for the algorithm of Stumpf et al. (2003) utilized in the standard SeaWiFS atmospheric correction and both aerosol and bio-optical model for the coupled atmospheric-ocean algorithm of Kuchinke. The Kuchinke algorithm presents model aerosol-size distributions that differ from real aerosol-size distribution pertaining to the measurements. In conclusion, the results show that for the given atmospheric and oceanic conditions of this study, the SeaWiFS atmospheric correction algorithm is most appropriate for estimating the marine and aerosol parameters in the given turbid waters regions.     

A sun glint correction method for hyperspectral imagery containing areas with non-negligible water leaving NIR signal

Present sun glint removal methods overcorrect data collected in very shallow (less than 2 m) waters if the sensors used do not have bands in far infrared part of the spectrum. The reason is assuming of zero water leaving signal at near infrared (NIR) wavelengths. This assumption is not valid in very shallow waters, but also in areas where aquatic vegetation reaches water surface and in case of phytoplankton blooms that reach very high biomass or form surface scum. We propose an alternative method that can be used for successful glint removal even if the sensor does not have spectral bands beyond 800 nm. The proposed method utilises the presence and depth of the oxygen absorption feature near 760 nm as an indicator of glint contamination. This method allows removing sun glint from hyperspectral imagery preserving shape and magnitude of reflectance spectra in the cases where the negligible water leaving NIR signal is not valid.     

Measurements and analysis of in situ multi-angle reflectance of turbid inland water: a case study in Meiliang Bay,Taihu Lake,China

The bidirectional reflectance properties of the anisotropic light field above the water surface are important for a range of applications. The bidirectional reflectance distribution function of oceanic waters has been well characterized but there is a lack of information for turbid inland waters. In addition, there is a lack of bidirectional reflectance data measured in turbid inland waters partially due to the difficulty in collecting in situ water-surface multi-angle remote-sensing reflectance data. To facilitate bidirectional reflectance studies of turbid inland waters using in situ multi-angular reflectance data, we have designed and developed a simple hand-held 3D positioning pole to position the spectrometer optical fibre probe and a specific method to collect the multi-angular reflectance data above the water surface with this pole. Using this device, we collected multi-angular reflectance data in Meiliang Bay, Taihu Lake, China, and analysed the uncertainties in this method. We analysed the bidirectional distribution characteristics of the data, and compared the findings to those in the literature. Both uncertainty analysis and bidirectional distribution characteristics analysis showed that our method is effective in collecting multi-angular reflectance above the water surface and can be applied to validate bidirectional correction models in the future.     

Evaluation of the NIR-SWIR atmospheric correction algorithm for MODIS-Aqua over the Eastern China Seas

The performance of the near-infrared (NIR) and short-wave infrared (SWIR) combined atmospheric correction algorithm (NIR-SWIR) for Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua over the Eastern China Seas (ECS) was evaluated. The in situ data set for evaluation in this study was collected during 2005 and 2012 through eight cruises in the ECS, wherein 49 in situ observation points were successfully matched with MODIS-Aqua data. The remote-sensing reflectance derived from MODIS-Aqua data using the NIR-SWIR algorithm and the NIR algorithm were compared to the in situ measurements in the matched-up data set, which included ocean bands (412, 443, 488, 531, 547, 667, and 678 nm) and land bands (469, 555, and 645 nm). The results show that the performance of the NIR-SWIR algorithm has been improved in turbid waters, and the effect at the short-wave bands (blue and green bands) is more significant than that at the long-wave bands (red bands). In addition, MODIS-Aqua data at the land bands (469, 555, and 645 nm) show a similar performance to those of nearby ocean bands. However, the lower estimation accuracy is still a remarkable question at bands 412, 645, 667, 678 nm. The results from both the NIR-SWIR and NIR algorithms were applied to the images of MODIS-Aqua in the ECS and they indicate that the extent to which the quality of the derived remote-sensing reflectance using the NIR-SWIR algorithm can be improved shows major differences for different seasons. The minimum area is in summer, and the maximum area in winter. The NIR-SWIR algorithm should be used for the whole of the Bohai Sea in winter.     

SeaWiFS data interpretation in a coastal area in the Bay of Biscay

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) instrument, launched onboard the Orbimage 2 satellite, is composed of an optical scanner with eight channels that are used to interpret the ocean colour, and has been operational since September 1997. SeaWiFS data were received by the Dundee Satellite Receiving Station and processed by the Plymouth Marine Laboratory with a slight time-lag. In situ measurements of reflectance, salinity, seston and chlorophyll a were analysed during the Biomet surveys to gain a better knowledge of the dynamics of the Gironde turbid plume during this period. The results showed logarithmic relationships between the SeaWiFS normalized water-leaving radiances (n L w ) at 490 and 555 nm (n L w (490) and n L w (555)), and the suspended particle matter concentrations. The relationship between the n L w (555) radiances and these concentrations is used to map the coastal terrigenous turbidities. But the chlorophyll a concentrations calculated from SeaWiFS are overestimated in the turbid waters. The n L w (490)/n L w (555) ratio decreases with increasing turbidity and with increasing chlorophyll a concentration. To distinguish the chlorophyll a in turbid waters, the n L w (490) radiances are calculated from n L w (555) considering only the effect of terrigenous turbidity. Then, the n L w (490) SeaWiFS image is compared to the calculated n L w (490), to reveal the 'negative' areas caused by the chlorophyll a and yellow substance absorption.     

OCEANcode: The complete set of algorithms and models for the level_2 processing of European CZCS historical data

A complete set of algorithms and models for the level_2 processing of the European CZCS historical data was integrated in the OCEANcode software package. The OCEANcode allows the calibration of the sensor-recorded signal taking into account the instrument sensitivity loss; the correction of the calibrated signal for atmospheric contamination and derive sub-surface reflectances; and then the estimation of the concentration of water constituents. The atmospheric correction is performed on the basis of a reflectance-model-based algorithm. The Rayleigh correction is applied consistently for all water pixels, using a multiple scattering approach, and introducing atmospheric pressure and Ozone concentration data in the computation. The marine aerosol correction uses a pixel-by-pixel iterative procedure, allowing successive estimates of both the marine reflectance in the red spectral region (670nm) and the Angstrom exponent, which links simple wavelengths ratios to reflectance ratios. For case 1 waters, the optical properties of which are essentially dominated by planktonic pigments, the interrelations between marine reflectances and reflectance ratios at various wavelengths are derived from modelled calculations. For identified case 2 waters, where water constituents other than planktonic pigments (i.e. dissolved organics and suspended sediments) dominate the water optical properties, the evaluation of marine reflectances is approximated by means of interpolated Angstrom exponent values computed over case 1 water pixels and of empirical relationships derived from in situ measurements. The computation of chlorophyll-like pigments is performed with algorithms based on blue/green (443-550nm) reflectance ratios, for lower pigment concentration, or on green/green (520-550nm) reflectance ratios, for higher pigment concentration. As for the case of atmospheric corrections, the inter-relations between pigment concentration and reflectance ratios are model-derived for case 1 waters, and empirically determined for case 2 waters.     

基于高光谱数据和MODIS影像的鄱阳湖悬浮泥沙浓度估算

本文旨在寻找悬浮泥沙浓度的MODIS遥感影像估算模型,并利用实测的高光谱数据对其敏感波段和反演模型进行测试和验证。以鄱阳湖为研究区域,利用光谱数据进行分析,为利用遥感影像建模提供依据。进一步利用同步进行的鄱阳湖水质采样分析与MODIS影像中等分辨率各个波段反射率及其组合进行相关分析,寻找反演悬浮泥沙浓度的敏感波段。实验表明,MODIS的第一波段反射率对于悬浮泥沙浓度有很好的匹配(R² = 0.91; n = 25),进而建立了鄱阳湖地区的悬浮泥沙浓度遥感定量估算模型。利用估算模型和鄱阳湖地区历史MODIS影像,得到了鄱阳湖悬浮泥沙浓度分布图。基于对汛期鄱阳湖悬浮泥沙浓度的连续监测,可对长江倒灌入鄱阳湖现象的形态进行观测。     

The atmospheric correction of water colour and the quantitative retrieval of suspended particulate matter in Case II waters: Application to MERIS

The remote sensing of turbid waters (Case II) using the Medium Resolution Imaging Spectrometer (MERIS) requires new approaches for atmospheric correction of the data. Unlike the open ocean (Case I waters) there are no wavelengths where the water-leaving radiance is zero. A coupled hydrological atmospheric model is described here. The model solves the water-leaving radiance and atmospheric path radiance in the near-infrared (NIR) over Case II turbid waters. The theoretical basis of this model is described, together with its place in the proposed MERIS processing architecture. Flagging procedures are presented that allow seamless correction of both Case I waters, using conventional models, and Case II waters using the proposed model. Preliminary validation of the model over turbid waters in the Humber estuary, UK is presented using Compact Airborne Spectrographic Imager (CASI) imagery to simulate the MERIS satellite sensor. The results presented show that the atmospheric correction scheme has superior performance over the standard single scattering approach, which assumes that water-leaving radiance in the NIR is zero. Despite problems of validating data in such highly dynamic tidal waters, the results show that retrievals of sediments within 50% are possible from algorithms derived from the theoretical models.     

Optical properties of inorganic suspended solids and their influence on ocean colour remote sensing in highly turbid coastal waters

The influence of the optical properties of inorganic suspended solids (ISS) on in-water algorithms was evaluated using an optical model in highly turbid coastal water, whose ISS concentration reached several hundred grams per cubic metre. The measurements were conducted in the upper Gulf of Thailand. The backscattering coefficient of the ISS was calculated using the Lorenz–Mie scattering theory. On the basis of the measurement, the ISS size distribution was parameterized as a function of ISS concentration, and both the spherical and non-spherical particle shape models were evaluated. For ISS concentrations of 10 g m^?3, an estimate of the chlorophyll-a (chl-a) concentration within a factor of 2 on a logarithmic scale is possible in a [chl-a] range of 4–30 mg m^?3. The differential coefficient of remote sensing reflectance was calculated to evaluate its respective sensitivities for chl-a and ISS concentrations. The use of radiometric data at 670 nm (700–900 nm) is valid for in-water algorithms used to estimate chl-a (ISS) concentration in highly turbid coastal waters.