Evaluating multiple colour-producing agents in Case II waters from Lake Erie

Lake Erie is part of the Great Lakes systems in North America, which represent the largest continental lake systems in the world. Anthropogenic eutrophication in the Western Basin of Lake Erie, a Case II environment, has an adverse impact on the surrounding ecosystems and the regional economy. The optical complexity found in Lake Erie is a feature of many aquatic environments making it a challenging setting for remote-sensing applications. To assess the controls on these optical properties, we sampled 20 locations, encompassing a variety of optical environments in the Western Basin and Sandusky Bay during four research cruises. Strong correlations between light extinction and phycocyanin (correlation coefficient, r ≥ 0.95), suspended sediment (r = 0.90), and chlorophyll-a (r ≥ 0.86) indicate that surface conditions are representative down to at least the first optical depth. Application of varimax-rotated principal component analysis to lab-based, hyperspectral reflectance data identified three components related to a diatom/green algae community, and two blue-green algae communities, one of which was associated with suspended sediment. Phycocyanin and chlorophyll-a content inferred using a semi-analytic red/near-infrared algorithm correlated well with concentrations measured in situ using a multiparameter sonde. Chlorophyll-a retrievals from a regional, blue : green algorithm developed for the Western Basin of Lake Erie compared well with retrievals from the semi-analytic algorithm for all samples from the Western Basin and 25% of samples from Sandusky Bay. Chlorophyll-a retrieval errors using the blue : green algorithm occurred when high ratios of suspended sediment to phycocyanin biased samples from the extremely turbid waters of Sandusky Bay. The bias likely resulted when suspended sediment altered the blue : green ratio or when phycocyanin interfered with the chlorophyll-a absorption peaks. This approach can be applied to other Case II environments to provide insights during the design of experimental field studies and for spectral band selection with the next generation of visible near-infrared remote-sensing instruments.     

MERIS observations of chlorophyll-a dynamics in Erhai Lake between 2003 and 2009

The Medium Resolution Imaging Spectrometer (MERIS) was used to investigate the spatial and temporal dynamics of chlorophyll-a (chl-a) in Erhai Lake, the second largest freshwater lake in the Yunnan province of China. Six chl-a retrieval models, including four Basic ERS & Envisat (A)ATSR and Meris Toolbox (BEAM) software-incorporated algorithms and MERIS three-band and two-band models, were validated to find the best fit to extract chl-a concentration in Erhai Lake. With a chl-a range of 5–15 mg m^–3, the Lakes/Eutrophic method showed the best performance. The algorithm was then applied to eight-year cloud-free MERIS images between 2003 and 2009, with seasonal and inter-annual variability analysed. Long-term chl-a distributions of Erhai Lake revealed significant seasonal and inter-annual variability. The mean chl-a of the south lake was higher in summer (14.3 mg m^–3) than in spring (10.1 mg m^–3), while generally lower chl-a was found in the north lake with a mean chl-a of 6.4 mg m^–3 in spring and 9.0 mg m^–3 in summer, respectively. An increasing trend was found between 2006 and 2009, and the increasing rate was 12.9% for annual chl-a of the entire lake. While chl-a seasonality was attributed to the seasonal changes of the local temperature, the inter-annual variation was possibly linked to the discharged wastewater from Dali City. This work could provide critical information for decision-makers to manage Erhai Lake’s aquatic ecosystems.     

Using hyperspectral data to quantify water-quality parameters in the Wabash River and its tributaries,Indiana

A hand-held spectrometer was used to collect above-water spectral measurements for measuring optically active water-quality characteristics of the Wabash River and its tributaries in Indiana. Water sampling was undertaken concurrent with spectral measurements to estimate concentrations of chlorophyll (chl) and total suspended solids (TSS). A method for removing sky and Sun glint from field spectra for turbid inland waters was developed and tested. Empirical models were then developed using the corrected field spectra and in situ chl and TSS data. A subset of the field measurements was used for model development and the rest for model validation. Spectral characteristics indicative of waters dominated by different inherent optical properties (IOPs) were identified and used as the basis of selecting bands for empirical model development. It was found that the ratio of the reflectance peak at the red edge (704 nm) with the local minimum caused by chl absorption at 677 nm was a strong predictor of chl concentrations (coefficient of determination (R²) = 0.95). The reflectance peak at 704 nm was also a good predictor for TSS estimation (R² = 0.75). In addition, we also found that reflectance within the near-infrared (NIR) wavelengths (700–890 nm) all showed a strong correlation (0.85–0.91) with TSS concentrations and generated robust models. Results suggest that hyperspectral information provided by field spectrometer can be used to distinguish and quantify water-quality parameters under complex IOP conditions.     

Satellite-based water quality monitoring in Lake Vänern,Sweden

Lake Vänern, Sweden, is one of Europe’s largest lakes and has a historical, cultural, ecological as well as economic importance. Lake water quality monitoring is required by national and international legislations and directives, but present programmes are insufficient to meet the requirements. To complement in situ based monitoring, the possibility to obtain reliable information about spatial and temporal water quality trends in Lake Vänern from the ENVISAT mission’s MERIS instrument was evaluated. The complete archive (2002–2012) of MERIS (Medium Resolution Imaging Spectrometer) full resolution data was processed using the water processor developed by Free University Berlin (FUB) to derive aerosol optical thickness (AOT), remote-sensing reflectance (R_rs) and water quality parameters: chlorophyll-a (chl-a) concentration, coloured dissolved organic matter absorption at 443 nm (CDOM), and total suspended matter (TSM) concentration. The objective was to investigate if, either, FUB reflectance products in combination with potential lake-specific band ratio algorithms for water quality estimation, or directly, FUB water quality products, could complement the existing monitoring programme.

Application of lake-specific band ratio algorithms requires high-quality reflectance products based on correctly estimated AOT. The FUB reflectance and AOT products were evaluated using Aerosol Robotic Network – Ocean Color (AERONET-OC) match-up data measured at station Pålgrunden in Lake Vänern. The mean absolute percentage differences (MAPDs) of the final reflectance retrievals at 413, 443, 490, 555, and 665 nm were 510%, 48%, 33%, 34%, and 33%, respectively, corresponding to a large positive bias in 413 nm, positive bias in 443–555 nm, and a negative bias in 665 nm. AOT was strongly overestimated in all bands.

The FUB water quality products were evaluated using match-up in situ data of chl-a, filtered absorbance (Abs_F(420)) and turbidity as Abs_F(420) is related to CDOM and turbidity is strongly related to TSM. The in situ data was collected within the Swedish national and regional monitoring programmes. In order to widen the range of water constituents and add more data to the analysis, data from four large Swedish lakes (Vänern, Vättern, Mälaren, and Hjälmaren) was included in the analysis. High correlation (r ≥ 0.85) between in situ data and MERIS FUB derived water quality estimates were obtained, but the absolute levels were over- (chl-a) or under- (CDOM) estimated. TSM was retrieved without bias.

Calibration algorithms were established for chl-a and CDOM based on the match-up data from all four lakes. After calibration of the MERIS FUB data, realistic time series could be derived that were well in line with in situ measurements. The MAPDs of the final retrievals of chl-a, Abs_F(420) and Turbidity in Lake Vänern were 37%, 15%, and 35%, respectively, corresponding to mean absolute differences (MADs) of 0.9 µg l^?1, 0.17 m^?1, and 0.32 mg l^?1 in absolute values.

The partly inaccurate reflectance estimations in combination with both positive and negative bias imply that successful application of band ratio algorithms is unlikely. The high correlation between MERIS FUB water quality products and in situ data, on the other hand, shows a potential to complement present water quality monitoring programmes and improve the understanding and representability of the temporally and spatially sparse in situ observations. The monitoring potential shown in this study is applicable to the Sentinel-3 mission’s OLCI (Ocean Land Colour Instrument), which was launched by the European Space Agency (ESA) in February 2016 as a part of the EC Copernicus programme.     

Developing a two-step retrieval method for estimating total suspended solid concentration in Chinese turbid inland lakes using Geostationary Ocean Colour Imager (GOCI) imagery

Total suspended solid (TSS) concentration is an important water quality parameter. Mapping its varying distribution using satellite images with high temporal resolution is valuable for studying suspended sediment transportation and diffusion patterns in inland lakes. A total of 255 sites were used to make remote-sensing reflectance measurements and surface water sampling at four Chinese inland lakes, i.e. Taihu Lake, Chaohu Lake, Dianchi Lake, and the Three Gorges Reservoir, at different seasons. A two-step retrieval method was then developed to estimate TSS concentration for contrasting Chinese inland lakes, which is described in this article. In the first step, a cluster method was applied for water classification using eight Geostationary Ocean Colour Imager (GOCI) channel reflectance spectra simulated by spectral reflectance measured by an Analytical Spectral Devices (ASD) Inc. spectrometer. This led to the classification of the water into three classes (1, 2, and 3), each with distinct optical characteristics. Based on the water quality, spectral absorption, and reflectance, the optical features in Class 1 were dominated by TSS, while Class 3 was dominated by chl-a and the optical characteristics of Class 2 were dominated jointly by TSS and chl-a. In the second step, class-specific TSS concentration retrieval algorithms were built. We found that the band ratio Band 8/Band 4 was suitable for Class 1, while the band ratio of Band 7/Band 4 was suitable for both Class 2 and Class 3. A comprehensive determination value, combining the spectral angle mapper and Euclidean distance, was adopted to identify the classes of image pixels when the method was applied to a GOCI image. Then, based on the pixel’s class, the class-specific retrieval algorithm was selected for each pixel. The accuracy analysis showed that the performance of this two-step method was improved significantly compared to the unclassed method: the mean absolute percentage error decreased from 38.9% to 24.3% and the root mean square error decreased from 22.1 to 16.5 mg l^–1. Finally, the GOCI image acquired on 13 May 2013 was used as a demonstration to map the TSS concentration in Taihu Lake with a reasonably good accuracy and highly resolved spatial structure pattern.     

Evaluation of RapidEye data for mapping algal blooms in inland waters

The high spatial resolution multispectral imaging sensor onboard RapidEye (RE) has a red-edge band centred at 710 nm, which can be used to produce a product equivalent to the Maximum Chlorophyll Index (MCI) that was developed to detect algal blooms with Medium Resolution Imaging Spectrometer (MERIS) data. The RapidEye system, with five satellites, offers a greater repeat frequency than other high-resolution satellites. In this study, we compared RapidEye and MERIS derived MCI products for the Harris Chain of Lakes in central Florida, USA, to determine if RapidEye can produce an equivalent product similar to MERIS. Data from two RapidEye satellites (RapidEye-2 and RapidEye-5) were used. Band-by-band matchups used RapidEye Top of the Atmosphere (TOA) reflectance and MERIS ρ_s (reflectance corrected only for Raleigh scattering and molecular absorption). The RapidEye TOA reflectance data differed from MERIS, but when the bands were calibrated to the MERIS, the MCI products matched between the two RapidEye satellites and the MERIS MCI. Estimated chlorophyll-a concentrations using a relationship established for Lake Erie matched in situ chlorophyll-a concentrations with a median error of 1.09 mg m^?3. The results indicate that RapidEye is useful for this purpose, which also suggests that other high-resolution satellites with similar red-edge bands may also provide MCI-type products that would allow estimation of chlorophyll-a. RapidEye provides a context for applying future constellation of small satellites for monitoring water quality issues. Lake water quality managers and environmental agencies could effectively use such high-resolution products to assess and manage algal bloom events.     

Satellite multi-sensor mapping of suspended particulate matter in turbid estuarine and coastal ocean,China

In this work, five ocean-colour sensors, the Moderate Resolution Imaging Spectroradiometer aboard the Terra satellite (Terra MODIS), Moderate Resolution Imaging Spectroradiometer aboard the Aqua satellite (Aqua MODIS), Medium Range Imaging Spectrometer aboard the Environmental Satellite (Envisat MERIS), Medium Resolution Spectral Imager aboard the FY-3 satellite (FY-3 MERSI), and Geostationary Ocean Colour Imager (GOCI), were selected to examine the compatibility of an algorithm proposed for suspended particulate matter (SPM) retrieval and concordance of satellite products retrieved from different ocean-colour sensors. The results could effectively increase revisit frequency and complement a temporal gap of time series satellites that may exist between on-orbit and off-orbit. Using in situ measurements from 17 cruise campaigns between 2004 and 2012, the SPM retrieval algorithm was recalibrated so as to be universal and adapted for multi-sensor retrievals. An inter-comparison of multi-sensor-derived products showed that GOCI-derived SPM and Envisat MERIS-derived SPM had the best fitting on a 1:1 scatterplot, with a statistic regression slope of 0.9617 and an intercept of 0.0041 (in units of g l^–1), respectively. SPM products derived from three sensors with nearly synchronous transit, Envisat MERIS, Terra MODIS, and FY-3 MERSI, exhibited excellent accordance with mean differences of 0.056, 0.057, and 0.013 g l^–1 in three field fixed stations, respectively, in the Yangtze estuary. Terra MODIS-derived SPM with GOCI-derived SPM, except in the high SPM waters of Hangzhou Bay, and Aqua MODIS-derived SPM with GOCI-derived SPM, except in the moderate SPM waters of the South Branch and south of the Subei Coast, showed a good correspondence. Meanwhile, synchronous multi-sensor-derived SPM with concurrent in situ SPM time series observed in fixed field stations mostly displayed a good correspondence. Results suggest that the algorithm is feasible and compatible for SPM retrieval by multiple sensors.     

Analysis of natural background and dredging-induced changes in TSM concentration from MERIS images near commercial harbours in the Estonian coastal sea

Medium Resolution Imaging Spectrometer (MERIS) products with 300 m resolution from 2006 to 2011 were used to evaluate the local background of total suspended matter (TSM) in the vicinity of commercial harbours located along the Estonian coastline in the Baltic Sea. The difference between background TSM maps (mainly influenced by spring bloom, cyanobacterial bloom, resuspension, and river inflow) and dredging period mean maps was used for the estimation of dredging-induced turbidity at the time of dredging operations. Validation of Case II Regional (C2 R) and Free University of Berlin (FUB) MERIS processors with point measurements showed that both processors represent the changes in TSM concentration adequately. C2 R processors showed better statistics (R² = 0.61, root mean square error = 0.82 mg l^–1, SD = 0.77 mg l^–1, mean bias = –0.28 mg l^–1) compared to the FUB processor. Analysis of monthly mean TSM maps revealed that the variability of TSM concentration, showing the resilience level of the local ecosystem, is very different along the Estonian coastline – varying between 0.75 and 2.60 mg l^–1 near the Port of Tallinn, located in the Gulf of Finland, and between 10.04 and 24.23 mg l^–1 near the Port of Pärnu, located in the Gulf of Riga. The viability of the method for dredging impact detection was tested by evaluating the dredging-induced turbidity on monthly mean TSM maps for the dredging period in autumn 2008 in Pakri Bay, which is an environmentally sensitive area. A threshold TSM concentration value of >2.26 mg l^–1 difference from background TSM was defined as a criterion for dredging impact detection for Pakri Bay. The area of dredging-induced turbidity was between 0.56 and 1.25 km² and did not reach the environmentally sensitive NATURA 2000 region adjoining Paldiski South Harbour.     

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.     

Measurement of water colour using AVIRIS imagery to assess the potential for an operational monitoring capability in the Pamlico Sound Estuary,USA

The monitoring of water colour parameters can provide an important diagnostic tool for the assessment of aquatic ecosystem condition. Remote sensing has long been used to effectively monitor chlorophyll concentrations in open ocean systems; however, operational monitoring in coastal and estuarine areas has been limited because of the inherent complexities of coastal systems, and the coarse spectral and spatial resolutions of available satellite systems. Data were collected using the National Aeronautics and Space Administration (NASA) Advanced Visible–Infrared Imaging Spectrometer (AVIRIS) flown at an altitude of approximately 20 000 m to provide hyperspectral imagery and simulate both MEdium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectrometer (MODIS) data. AVIRIS data were atmospherically corrected using a radiative transfer modelling approach and analysed using band ratio and linear regression models. Regression analysis was performed with simultaneous field measurements data in the Neuse River Estuary (NRE) and Pamlico Sound on 15 May 2002. Chlorophyll a (Chl a) concentrations were optimally estimated using AVIRIS bands (9.5 nm) centred at 673.6 and 692.7 nm, resulting in a coefficient of determination (R ²) of 0.98. Concentrations of Chromophoric Dissolved Organic Matter (CDOM), Total Suspended Solids (TSS) and Fixed Suspended Solids (FSS) were also estimated, resulting in coefficients of determination of R ² = 0.90, 0.59 and 0.64, respectively. Ratios of AVIRIS bands centred at or near those corresponding to the MERIS and MODIS sensors indicated that relatively good satellite‐based estimates could potentially be derived for water colour constituents at a spatial resolution of 300 and 500 m, respectively.     

In situ validation of MERIS marine reflectance off the southwest Iberian Peninsula: assessment of vicarious adjustment and corrections for near-land adjacency

Water-leaving reflectance (ρ_w) data from the European Space Agency ocean colour sensor Medium Resolution Imaging Spectrometer (MERIS) was validated with in situ ρ_w between October 2008 and November 2011, off Sagres on the southwest coast of the Iberian Peninsula. The study area is exceptional, since Stations A, B, and C at 2, 10, and 18 km offshore are in optically deep waters at approximately 40, 100, and 160 m, respectively. These stations showed consistently similar bio-optical properties, characteristic of Case 1 waters, enabling the evaluation of adjacency effects independent of the usual co-varying inputs of coastal waters. Using the third reprocessing of MERIS with the standard MEGS 8.1 processor, four different combinations of procedures were tested to improve the calibration between MERIS products and in situ data. These combinations included no vicarious adjustment (NoVIC), vicarious adjustment (VIC), and, for mitigating the effects of land adjacency on MERIS ρ_w, the improved contrast between ocean and land (ICOL) processor (version 2.7.4) and VIC + ICOL. Out of approximately 130 potential matchups for each station, 38–77%, 74–86%, and 88–90% were achieved at Stations A, B, and C, respectively, depending on which of the four combinations were used. Analyses of ρ_w comparing these various procedures, including statistics, scatter plots, histograms, and MERIS full-resolution images, showed that the VIC procedure compared with NoVIC produced minimal changes to the calibration. For example, at the oceanic Station C, the regression slope was closer to unity at all wavelengths with NoVIC compared to VIC, whereas, with the exception of wavelengths 412 and 443 nm, the intercept, mean ratio (MR), absolute percentage difference (APD), and relative percentage difference (RPD) were better with NoVIC. The differences for MR and APD indicate that there was marginal improvement for these two bands with VIC, and an over-adjustment with RPD. ICOL also showed inconsistent results for improving the retrieval of the near-shore conditions, but under some conditions, such as ρ_w at wavelength 560 nm, the improvement was striking. VIC + ICOL showed results intermediate between those of VIC and ICOL implemented separately. In relation to other validation sites, the offshore Station C at Sagres had much in common with the Mediterranean deep water, BOUSSOLE buoy, although the matchup statistics between MERIS ρ_w and in situ ρ_w were much better for Sagres than for BOUSSOLE. Strikingly, the matchup statistics for ρ_w at Sagres were very similar to those for the Acqua Alta Oceanographic Tower (AAOT), where the AAOT showed more scatter at 412 nm, probably because of the atmospheric correction where the aerosol optical thickness is higher at the AAOT. Conversely, Sagres showed much greater scatter at 665 nm in the red as the values were generally close to the limits of detection owing to the clearer waters at Sagres compared to the more turbid waters at the AAOT.     

Water property monitoring and assessment for China's inland Lake Taihu from MODIS-Aqua measurements

We provide results of quantitative measurements and characterization for inland freshwater Lake Taihu from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua. China's Lake Taihu, which is located in the Yangtze River delta in one of the world's most urbanized and heavily populated areas, contains consistently highly turbid waters in addition to frequent large seasonal algae blooms in various lake regions. Thus, satellite data processing requires use of the shortwave infrared (SWIR) atmospheric correction algorithm. Specifically for Lake Taihu, an iterative SWIR-based atmospheric correction algorithm has been developed and proven to provide reasonably accurate water-leaving radiance spectra data. Using MODIS-Aqua measurements, the blue-green algae bloom in Lake Taihu in 2007 has been studied in detail, demonstrating the importance and usefulness of satellite water color remote sensing for effectively monitoring and managing a bloom event.Seasonal and interannual variability, as well as spatial distributions, of lake water properties were studied and assessed using the MODIS-Aqua measurements from 2002 to 2008. Results show that overall waters in Lake Taihu are consistently highly turbid all year round, with the winter and summer as the most and least turbid seasons in the lake, respectively. Extremely turbid waters in the winter are primarily attributed to strong winter winds that lead to significant amounts of total suspended sediment (TSS) in the water column. In addition, MODIS-Aqua-measured water-leaving radiance at the blue band is consistently low in various bay regions in Lake Taihu, indicating high algae concentration in these regions. Climatological water property maps, including normalized water-leaving radiance spectra nL_w(λ), chlorophyll-a concentration, and water diffuse attenuation coefficient at the wavelength of 490 nm (K_d(490)), are derived from all MODIS-Aqua data from 2002 to 2008 for Lake Taihu, showing overall spatial distribution features for the lake water property.     

Validation of MERIS LAI and FAPAR products for winter wheat-sown test fields in North-East Bulgaria

Progress in deriving land surface biophysical parameters in a spatially explicit manner using remotely sensed data has greatly enhanced our ability to model ecosystem processes and monitor crop development. A multitude of satellite sensors and algorithms have been used to generate ready-to-use maps of various biophysical parameters. Validation of these products for different vegetation types is needed to assess their reliability and consistency. While most of the current satellite biophysical products have spatial resolution of one kilometre, a recent effort utilizing data from the Medium Resolution Imaging Spectrometer (MERIS) provided leaf area index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and other canopy parameters in a resolution as fine as 300 m over the European continent. This resolution would be more appropriate for application at the regional scale, particularly for crop monitoring. This higher-resolution MERIS product has been evaluated in a limited number of studies to date. This article aims to validate LAI and FAPAR from the MERIS 10-day composite BioPar BP-10 product over winter wheat fields in northeast Bulgaria. The ground measurements of LAI and FAPAR were up-scaled and 30 m resolution reference raster layers were created using empirical relationships with Landsat TM (RMSE = 0.06 and RMSE = 0.22 for FAPAR and LAI, respectively). MERIS FAPAR and LAI were found to have significant correlation with FAPAR and LAI from the reference raster layers (R² = 0.84 and R² = 0.78, respectively). When MERIS Green LAI was calculated (incorporating the fraction of vegetation and brown vegetation cover from the BioPar BP-10 product), better correspondence with LAI values from the reference raster layer was achieved, with RMSE and bias reduced by 30–35%. The results from this study confirm the findings of previous validations showing that MERIS Green LAI tends to overestimate LAI values lower than 1. As a conclusion of the study, the BioPar BP-10 product was found to provide reliable estimates of FAPAR and acceptably accurate estimates of LAI for winter wheat crops in North-East Bulgaria.     

Comparison and evaluation of Medium Resolution Imaging Spectrometer leaf area index products across a range of land use

Leaf area index (LAI) is a commonly required parameter when modelling land surface fluxes. Satellite based imagers, such as the 300 m full resolution (FR) Medium Spectral Resolution Imaging Spectrometer (MERIS), offer the potential for timely LAI mapping. The availability of multiple MERIS LAI algorithms prompts the need for an evaluation of their performance, especially over a range of land use conditions. Four current methods for deriving LAI from MERIS FR data were compared to estimates from in-situ measurements over a 3 km × 3 km region near Ottawa, Canada. The LAI of deciduous dominant forest stands and corn, soybean and pasture fields was measured in-situ using digital hemispherical photography and processed using the CANEYE software. MERIS LAI estimates were derived using the MERIS Top of Atmosphere (TOA) algorithm, MERIS Top of Canopy (TOC) algorithm, the Canada Centre for Remote Sensing (CCRS) Empirical algorithm and the University of Toronto (UofT) GLOBCARBON algorithm. Results show that TOA and TOC LAI estimates were nearly identical (R² > 0.98) with underestimation of LAI when it is larger than 4 and overestimation when smaller than 2 over the study region. The UofT and CCRS LAI estimates had root mean square errors over 1.4 units with large (∼ 25%) relative residuals over forests and consistent underestimates over corn fields. Both algorithms were correlated (R² > 0.8) possibly due to their use of the same spectral bands derived vegetation index for retrieving LAI. LAI time series from TOA, TOC and CCRS algorithms showed smooth growth trajectories however similar errors were found when the values were compared with the in-situ LAI. In summary, none of the MERIS LAI algorithms currently meet performance requirements from the Global Climate Observing System.     

Atmospheric correction of ENVISAT/MERIS data over case II waters: the use of black pixel assumption in oxygen and water vapour absorption bands

The Medium Resolution Imaging Spectrometer (MERIS) sensor, with its good physical design, can provide excellent data for water colour monitoring. However, owing to the shortage of shortwave-infrared (SWIR) bands, the traditional near-infrared (NIR)–SWIR algorithm for atmospheric correction in inland turbid case II waters cannot be extended to the MERIS data directly, which limits its applications. In this study, we developed a modified NIR black pixel method for atmospheric correction of MERIS data in inland turbid case II waters. In the new method, two special NIR bands provided by MERIS data, an oxygen absorption band (O₂ A-band, 761 nm) and a water vapour absorption band (vapour A-band, 900 nm), were introduced to keep the assumption of zero water-leaving reflectance valid according to the fact that both atmospheric transmittance and water-leaving reflectance are very small at these two bands. After addressing the aerosol wavelength dependence for the cases of single- and multiple-scattering conditions, we further validated the new method in two case lakes (Lake Dianchi in China and Lake Kasumigaura in Japan) by comparing the results with in situ measurements and other atmospheric correction algorithms, including Self-Contained Atmospheric Parameters Estimation for MERIS data (SCAPE-M) and the Basic ERS (European Remote Sensing Satellite) & ENVISAT (Environmental Satellite) (A)ATSR ((Advanced) Along-Track Scanning Radiometer) and MERIS (BEAM) processor. We found that the proposed method had acceptable accuracy in the bands within 560–754 nm (MERIS bands 5–10) (average absolute deviation (AAD) = 0.0081, average deviation (AD) = 0.0074), which are commonly used in the estimation models of chlorophyll-a (chl-a) concentrations. In addition, the performance of the new method was superior to that of the BEAM processor and only slightly worse than that of SCAPE-M in these bands. Considering its acceptable accuracy and simplicity both in principle and at implementation compared with the SCAPE-M method, the new method provides an option for atmospheric correction of MERIS data in inland turbid case II waters with applications aiming for chl-a estimation.     

A new method to generate a high-resolution global distribution map of lake chlorophyll

A new method was developed, evaluated, and applied to generate a global dataset of growing-season chlorophyll-a (chl) concentrations in 2011 for freshwater lakes. Chl observations from freshwater lakes are valuable for estimating lake productivity as well as assessing the role that these lakes play in carbon budgets. The standard 4 km NASA OceanColor L3 chlorophyll concentration products generated from MODIS and MERIS sensor data are not sufficiently representative of global chl values because these can only resolve larger lakes, which generally have lower chl concentrations than lakes of smaller surface area. Our new methodology utilizes the 300 m-resolution MERIS full-resolution full-swath (FRS) global dataset as input and does not rely on the land mask used to generate standard NASA products, which masks many lakes that are otherwise resolvable in MERIS imagery. The new method produced chl concentration values for 78,938 and 1,074 lakes in the northern and southern hemispheres, respectively. The mean chl for lakes visible in the MERIS composite was 19.2 ± 19.2, the median was 13.3, and the interquartile range was 3.90–28.6 mg m^?3. The accuracy of the MERIS-derived values was assessed by comparison with temporally near-coincident and globally distributed in situ measurements from the literature (n = 185, RMSE = 9.39, R² = 0.72). This represents the first global-scale dataset of satellite-derived chl estimates for medium to large lakes.     

A new three-band spectral index for mitigating the saturation in the estimation of leaf area index in wheat

The normalized difference vegetation index (NDVI) is a commonly used index for monitoring crop growth status. Previous studies have shown that the leaf area index (LAI) estimation based on NDVI is limited by saturation that occurs under conditions of relatively dense canopies (LAI > 2 m² m^–2). To reduce the saturation effect, we suggested new spectral indices through the spectral indices approach. The results suggested that the two-band normalized difference spectral index (NDSI = ((ρ_{940 –} ρ₇₃₀) /(ρ₉₄₀ + ρ₇₃₀))) resulted from the two-band spectral indices approach and the three-band modified normalized difference spectral index (mNDSI = ((ρ_{940 –} 0.8 × ρ₉₅₀) – ρ₇₃₀) /((ρ_{940 –} 0.8 × ρ₉₅₀) + ρ₇₃₀)) resulted from the three-band spectral indices approach, and they were able to mitigate saturation and improve the LAI prediction with a determination coefficient (R²) of 0.77 and 0.78, respectively. In the validation based on data from independent experiments, these new indices exhibited an accuracy with relative root mean square error (RRMSE) lower than 23.38% and bias higher than –0.40. These accuracies were significantly higher than those obtained with some existing indices with good performance in LAI estimation, such as the enhanced vegetation index (EVI) (RRMSE = 30.19%, bias = –0.34) and the modified triangular vegetation index 2 (MTVI2) (RRMSE = 29.30%, bias = –0.28), and the indices with the ability to mitigate the saturation, such as the wide dynamic range vegetation index (WDRVI) (RRMSE = 31.37%, bias = –0.54), the red-edge wide dynamic range vegetation index (red-edge WDRVI) (RRMSE = 26.34%, bias = –0.54), and the normalized difference red-edge index (NDRE) (RRMSE = 28.41%, bias = –0.56). Additionally, these new indices were more sensitive under moderate to high LAI conditions (between 2 and 8 m² m^–2). Between these two new developed spectral indices, there was no significant difference in the accuracy and sensitivity assessments. Considering the index structure and convenience in application, we demonstrated that the two-band spectral index NDSI((ρ_{940 –} ρ₇₃₀) /(ρ₉₄₀ + ρ₇₃₀)) is efficient in mitigating saturation and has considerable potential for estimating the LAI of canopies throughout the entire growing season of wheat (Triticum aestivum L.), whereas the three-band spectral index contributes lesser in the saturation mitigation provided the red-edge band has been contained.     

Atmospheric correction algorithm for MERIS above case‐2 waters

The development and validation of an atmospheric correction algorithm designed for the Medium Resolution Imaging Spectrometer (MERIS) with special emphasis on case‐2 waters is described. The algorithm is based on inverse modelling of radiative transfer (RT) calculations using artificial neural network (ANN) techniques. The presented correction scheme is implemented as a direct inversion of spectral top‐of‐atmosphere (TOA) radiances into spectral remote sensing reflectances at the bottom‐of‐atmosphere (BOA), with additional output of the aerosol optical thickness (AOT) at four wavelengths for validation purposes. The inversion algorithm was applied to 13 MERIS Level1b data tracks of 2002–2003, covering the optically complex waters of the North and Baltic Sea region. A validation of the retrieved AOTs was performed with coincident in situ automatic sun–sky scanning radiometer measurements of the Aerosol Robotic Network (AERONET) from Helgoland Island located in the German Bight. The accuracy of the derived reflectances was validated with concurrent ship‐borne reflectance measurements of the SIMBADA hand‐held field radiometer. Compared to the MERIS Level2 standard reflectance product generated by the processor versions 3.55, 4.06 and 6.3, the results of the proposed algorithm show a significant improvement in accuracy, especially in the blue part of the spectrum, where the MERIS Level2 reflectances result in errors up to 122% compared to only 19% with the proposed algorithm. The overall mean errors within the spectral range of 412.5–708.75 nm are calculated to be 46.2% and 18.9% for the MERIS Level2 product and the presented algorithm, respectively.     

Estimating sub-pixel temperatures using the triangle algorithm

In water-deficient areas, water resource management requires evapotranspiration at high spatiotemporal resolution – an impossible situation given the trade-off between spatial and temporal resolutions in space-borne systems. Some researchers have suggested sharpening the Moderate Resolution Imaging Spectroradiometer (MODIS) land-surface temperature product with a resolution from 1 km to 250 m and a functional relationship between surface temperature (T _r) and normalized difference vegetation index (NDVI). Evapotranspiration at 250 m resolution can be obtained once every few days using this technique. Based on the interpretation of the triangular T _r–NDVI space and assuming uniform soil moisture conditions in a coarse pixel, this paper suggests an alternative algorithm – the triangle algorithm – for sharpening. The triangle algorithm was tested using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data from an arid zone. Sharpened surface temperatures and reference temperatures were compared at 60 m and 240 m resolutions. Root mean square errors with the triangle algorithm are smaller than those with a functional relationship between T _r and NDVI. This paper will also discuss the impact of soil moisture variations in the coarse pixel on the triangle algorithm. Finally we should mention that the triangle algorithm only applies to regions with non-stressed vegetation canopies.     

A regional algorithm for separating light absorption by chlorophyll-a and coloured detrital matter in the Black Sea,using 480–560 nm bands from ocean colour scanners

The aim of this study is to modify the regional algorithm for Moderate Resolution Imaging Spectroradiometer (MODIS) and Medium-spectral Resolution Imaging Spectrometer (MERIS) bands using newly available data of seasonal and spatial variability of light absorption by all optically active components in the Black Sea, and to obtain a merged product based on data retrieved from all the colour scanners that have operated since September 1997. Comparison of chlorophyll-a concentration (chl-a) simulated by the standard National Aeronautics and Space Administration (NASA) algorithm with in situ chl-a measurements showed that the NASA algorithm provided incorrect chl-a assessment of Black Sea shelf and deep-sea waters during spring?summer. Originally the standard NASA algorithm could be applied if there was a high correlation between light absorption by phytoplankton (a_ph) and that by coloured dissolved and suspended organic matter (a_CDM), which is not the case in the Black Sea. Consequently, development of the correct regional chl-a algorithm requires splitting of light absorption into a_ph and a_CDM. This issue has been resolved by the proposed regional algorithm developed for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) using remote-sensing reflectance in three (as minimum) spectral bands from 480 to 560 nm. Operation of the SeaWiFS and MERIS colour scanners ceased in December 2010 and April 2012, respectively, while the MODIS scanner is still working on the Terra and Aqua satellites. In this research, level 2 data (products of standard atmosphere correction at three bands filtered by masks/flags) of SeaWiFS, MODIS (on Terra and Aqua satellites), and MERIS scanners were retrieved for their mission lifetime. The regional algorithm was validated independently for each scanner, based on the adequacy of the algorithm-derived chl-a and a_CDM to in situ-measured data for the same day. The results suggest a satisfactory accuracy of the modified regional algorithm.