MERIS Products Research Articles

Evaluation of the Crosta method for the retrieval of water quality parameters from remote sensing data in the Pearl River estuary

Abstract In recent decades, many algorithms have been developed for the retrieval of water quality parameters using remotely sensed data. However, these algorithms are specific to a certain geographical area and cannot be applied to other areas. In this study, feature-orientated principal component (PC) selection, based on the Crosta method and using Landsat Thematic Mapper (TM) for the retrieval of water quality parameters (i.e., total suspended sediment concentration (TSM) and chlorophyll a (Chla)), was carried out. The results show that feature-orientated PC TSM, based on the Crosta method, obtained a good agreement with the MERIS-based TSM product for eight Landsat TM images. However, the Chla information, selected using the feature-orientated PC, has a poor agreement with the MERIS-based Chla product. The accuracy of the atmospheric correction method and MERIS product may be the main factors influencing the accuracy of the TSM and Chla information identified by the Landsat TM images using the Crosta method. The findings of this study would be helpful in the retrieval of spatial distribution information on TSM from the long-term historical Landsat image archive, without using coincident ground measurements. This article has been made Open Access thanks to the kind support of CAWQ/ACQE (https://www.cawq.ca).

Assessment of five global satellite products of fraction of absorbed photosynthetically active radiation: Intercomparison and direct validation against ground-based data

The fraction of absorbed photosynthetically active radiation (FAPAR) is a critical input parameter in many climate and ecological models. The accuracy of satellite FAPAR products directly influences estimates of ecosystem productivity and carbon stocks. The targeted accuracy of FAPAR products is 10%, or 0.05, for many applications. It is important to evaluate satellite FAPAR products and understand differences between the products to effectively use them in carbon cycling models. In this study, five global FAPAR products, namely MODIS, MISR, MERIS, SeaWiFS, and GEOV1 are intercompared over different land covers and directly validated with ground-based measurements at VAlidation of Land European Remote sensing Instruments (VALERI) and AmeriFlux sites. Intercomparison results show that MODIS, MISR, and GEOV1 agree well with each other and so do MERIS and SeaWiFS, but the difference between these two groups can be as large as 0.1. The temporal trends of these products agree better with each other in the Northern Hemisphere than in the Southern Hemisphere. The trends in the Northern Hemisphere are similar to those globally. However, the conclusions from the northern hemispheric scale could not be extended to the global scale for land covers such as savannahs and broadleaf evergreen forests. The differences between the products are consistent throughout the year over most of the land cover types, except over the forests, because of the different assumptions in the retrieval algorithms and the differences between green and total FAPAR products over forests. Direct validation results show that MERIS, MODIS, MISR, and GEOV1 FAPAR products have an uncertainty of 0.14 when validating with total FAPAR measurements, and 0.09 when validating with green FAPAR measurements. Overall, current FAPAR products are close to, but have not fulfilled, the accuracy requirement, and further improvements are still needed.

Modelling primary production in shallow well mixed lakes based on MERIS satellite data

Lakes play an important role in the global carbon cycle. Hence, data on seasonal and spatial variations of phytoplankton primary production (PP) is needed to estimate their ecological state. However, considerable difficulties arise when investigating the spatial and temporal variations of productivity in inland waters. Traditional in situ sampling approaches cannot provide the necessary data over large lakes or for lakes over large geographic regions. A solution can be to combine modelling with satellite data, by using different satellite products as inputs for a primary production model. The objective of this study is to evaluate and validate a lake primary production model based on satellite products. For that purpose we compared PP(sat) with PP(in situ) in two large, shallow, well mixed, and eutrophic Estonian lakes. A semi-empirical phytoplankton primary production model, derived by us earlier, was used. It allows estimating the values of phytoplankton primary production for lakes over large geographic areas. The primary production model operated well using MERIS products as input data. Our results show that spatial variability in primary production cannot be neglected in large lakes. Combining satellite data with model calculations allows monitoring of the state of lakes in space and time, providing a new perspective for lake primary production studies.

Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation

The accuracies of six global burned area (BA) products for year 2008 were compared using the same validation methods and reference data to quantify accuracy of each product. The selected products include MCD64, MCD45 and Geoland2, and three products developed within the Fire Disturbance project (fire_cci), which is part of the European Space Agency's (ESA) Climate Change Initiative (CCI) program. The latter three products were derived from MERIS and VEGETATION sensors (one product from each sensor separately, and a third one from the merging of MERIS and VGT products). The reference fire perimeters were mapped from two multi-temporal Landsat TM/ETM+ images at 103 non-overlapping Thiessen scene areas (TSA) selected with a stratified random sampling design. The validation results were based on cross tabulated error matrices from which six accuracy measures were computed following the requirements of end-users of burned area products. While overall accuracy (OA) exceeded 99% for all products, overall accuracy was lower for the burned class. Burned area commission error ratio was above 40% for all products and omission error ratio was above 65% for all products. The statistical significance of differences in accuracy between pairs of products was evaluated based on theory of the stratified combined ratio estimator. Statistical tests identified the MCD64 as the most accurate product, followed by MCD45 and the MERIS product.

Impact of iron associated to organic matter on remote sensing estimates of lake carbon content

There is a strong need to develop remote sensing methods for mapping lake carbon content on regional to global scales. The use of in situ methods is impractical for monitoring lake water quality over large geographical areas, which is a fundamental requirement to understand the true role of lakes in the global carbon cycle. The coloured component of dissolved organic carbon (DOC), called CDOM, absorbs light strongly in the blue part of the visible spectrum and can be used as a proxy for mapping lake DOC with remote sensing. However, iron associated to organic matter can cause extra browning of waters. Consequently, the remote sensing signal we interpret as DOC may partially be attributed to the presence of iron associated to organic matter, potentially hampering our ability to estimate carbon concentrations.A thorough analysis of biogeochemical parameters was carried out on Lake Mälaren on August 23, 2010, and a MERIS full resolution image was acquired simultaneously. MERIS standard, Case 2 Regional, and Boreal processors were used to calculate remote sensing products, which were compared with different lake water characteristics.The carbon to iron ratio was different from the rest of the lake in one of the basins. MERIS standard and Case 2 Regional processors were sensitive to this difference as the correlation between MERIS CDOM product and DOC was low (R2=0.43) for all sampling stations and increased to 0.92 when the one basin was excluded. The Boreal Lakes processor results were less disturbed by the different carbon–iron ratios found in one basin and produced reasonably good results (R2=0.65).We found MERIS products (e.g. total absorption) that provided good correlation (R2=0.80) with DOC-specific absorbance at 254nm, called SUVA, which is a metric commonly used to assess drinking water treatability. However, none of the MERIS products were suitable for mapping the total organic carbon in Lake Mälaren. MERIS total suspended matter product was a good (R2=0.73) proxy for particulate iron, meaning that the particulate iron content in Mälaren can be mapped from space.

Estimating lake carbon fractions from remote sensing data

Issues like monitoring lake water quality, studying the role of lakes in the global carbon cycle or the response of lakes to global change require data more frequently and/or over much larger areas than the in situ water quality monitoring networks can provide. The aim of our study was to investigate whether it is feasible to estimate different lake carbon fractions (CDOM, DOC, TOC, DIC, TIC and pCO2) from space using sensors like OLCI on future Sentinel 3. In situ measurements were carried out in eight measuring stations in two Swedish lakes within 2days of MERIS overpass. The results suggest that the MERIS CDOM product was not suitable for estimating CDOM in lakes Mälaren and Tämnaren and was not a good proxy for mapping lake DOC and TOC from space. However, a simple green to red band ratio and some other MERIS products like the total absorption coefficient, turbidity index, suspended matter and chlorophyll-a were correlated with different carbon fractions and could potentially be used as proxies to map these lake carbon fractions (CDOM, DOC, TOC, DIC, TIC and pCO2) from space.

Assessment of MODIS, MERIS, GEOV1 FPAR Products over Northern China with Ground Measured Data and by Analyzing Residential Effect in Mixed Pixel

Fraction of Photosynthetically Active Radiation (FPAR) is a critical parameter in land surface energy balance and climate modeling. Several global FPAR products are available, but these still require considerable assessment and validation due to low spatial resolution. Three major FPAR products that have covered China and provided continuous time series data—MODIS, MERIS and GEOV1—were assessed from 2006–2010. Based on the ground measurement data, the accuracies of these three FPAR products were directly validated for maize and winter wheat over northern China. This investigation also assessed the consistencies among the three FPAR products, and analyzed the residential area in mixed pixels effect on the FPAR products accuracy, at each of the main growth stages of maize and winter wheat. The GEOV1 FPAR product was found to be the most accurate with regression R2 values of 0.818 and 0.655 for ground measured maize and winter wheat FPAR. The maize FPAR data were generally more accurate than the winter wheat FPAR data. The MODIS, MERIS and GEOV1 products all indicated that FPAR variations among the growth stages differed from year to year. The scattered residential areas in mixed pixels were found to significantly affect the FPAR data uncertainties, and these were also analyzed in detail. The effect of residential area percentage in mixed pixels on FPAR values differed for different crops, and this was not necessarily in accordance with the FPAR product accuracy. For the mixed pixels, a quadratic polynomial was able to fit the residential area and FPAR data reasonably well with R2 values higher than 0.9 for most relationships. Quadratic polynomial fitting may provide a simple and convenient method to assess and reduce the residential area effect on FPAR in the mixed pixels.

A 4-D climatology (1979–2009) of the monthly tropospheric aerosol optical depth distribution over the Mediterranean region from a comparative evaluation and blending of remote sensing and model products

Abstract. Since the 1980s several spaceborne sensors have been used to retrieve the aerosol optical depth (AOD) over the Mediterranean region. In parallel, AOD climatologies coming from different numerical model simulations are now also available, permitting to distinguish the contribution of several aerosol types to the total AOD. In this work, we perform a comparative analysis of this unique multi-year database in terms of total AOD and of its apportionment by the five main aerosol types (soil dust, sea-salt, sulfate, black and organic carbon). We use 9 different satellite-derived monthly AOD products: NOAA/AVHRR, SeaWiFS (2 products), TERRA/MISR, TERRA/MODIS, AQUA/MODIS, ENVISAT/MERIS, PARASOL/POLDER and MSG/SEVIRI, as well as 3 more historical datasets: NIMBUS7/CZCS, TOMS (onboard NIMBUS7 and Earth-Probe) and METEOSAT/MVIRI. Monthly model datasets include the aerosol climatology from Tegen et al. (1997), the climate-chemistry models LMDz-OR-INCA and RegCM-4, the multi-model mean coming from the ACCMIP exercise, and the reanalyses GEMS and MACC. Ground-based Level-2 AERONET AOD observations from 47 stations around the basin are used here to evaluate the model and satellite data. The sensor MODIS (on AQUA and TERRA) has the best average AOD scores over this region, showing a relevant spatio-temporal variability and highlighting high dust loads over Northern Africa and the sea (spring and summer), and sulfate aerosols over continental Europe (summer). The comparison also shows limitations of certain datasets (especially MERIS and SeaWiFS standard products). Models reproduce the main patterns of the AOD variability over the basin. The MACC reanalysis is the closest to AERONET data, but appears to underestimate dust over Northern Africa, where RegCM-4 is found closer to MODIS thanks to its interactive scheme for dust emissions. The vertical dimension is also investigated using the CALIOP instrument. This study confirms differences of vertical distribution between dust aerosols showing a large vertical spread, and other continental and marine aerosols which are confined in the boundary layer. From this compilation, we propose a 4-D blended product from model and satellite data, consisting in monthly time series of 3-D aerosol distribution at a 50 km horizontal resolution over the Euro-Mediterranean marine and continental region for the 2003–2009 period. The product is based on the total AOD from AQUA/MODIS, apportioned into sulfates, black and organic carbon from the MACC reanalysis, and into dust and sea-salt aerosols from RegCM-4 simulations, which are distributed vertically based on CALIOP climatology. We extend the 2003–2009 reconstruction to the past up to 1979 using the 2003–2009 average and applying the decreasing trend in sulfate aerosols from LMDz-OR-INCA, whose AOD trends over Europe and the Mediterranean are median among the ACCMIP models. Finally optical properties of the different aerosol types in this region are proposed from Mie calculations so that this reconstruction can be included in regional climate models for aerosol radiative forcing and aerosol-climate studies.

Intercomparison and quality assessment of MERIS, MODIS and SEVIRI FAPAR products over the Iberian Peninsula

The fraction of absorbed photosynthetically active radiation (FAPAR) is a key variable in productivity and carbon cycle models. The variety of available FAPAR satellite products from different space agencies leads to the necessity of assessing the existing differences between them before using into models. Discrepancies of four FAPAR products derived from MODIS, SEVIRI and MERIS (TOAVEG and MGVI algorithms), covering the Iberian Peninsula from July 2006 to June 2007 are here analyzed. The assessment is based on an intercomparison involving the spatial and temporal consistency between products and a statistical analysis across land cover types. In general, significant differences are found over the Iberian Peninsula concentrated on the temporal variation and absolute values. The MODIS and MERIS/MGVI FAPAR products clearly show the highest and lowest absolute values, respectively, along with the lowest intra-annual variation. When considering individual land cover types, the largest FAPAR disagreements among the analyzed products were found between MODIS-MERI/MGVI and MERIS/TOAVEG-MERIS/MGVI over broadleaf and needleaf forests, with discrepancies quantified by RMSE higher than 0.30 and absolute bias higher than 0.25. These discrepancies can lead to relative gross primary production differences up to 65%.

An evaluation of satellite aerosol products against sunphotometer measurements

Because atmospheric aerosols scatter sunlight back to space, reflectance measurements from spaceborne radiometers can be used to estimate the aerosol load and its optical properties. Several aerosol products have been generated in a systematic way, and are available for further studies. In this paper, we evaluate the accuracy of such aerosol products derived from the measurements of POLDER, MODIS, MERIS, SEVIRI and CALIOP, through a statistical comparison with Aerosol Optical Depth (AOD) measurements from the AERONET sunphotometer network. Although this method is commonly used, this study is, to our knowledge, among the most extensive of its type since it compares the performance of the products from 5 different sensors using up to five years of data for each of them at global scale. The choice of these satellite aerosol datasets was based on their availability at the ICARE Data and Service Centre ( www.icare.univ-lille1.fr). We distinguish between retrievals over land and ocean and between estimates of total and fine mode AOD. Over the oceans, POLDER and MODIS retrievals are of similar quality, with RMS difference lower than 0.1 and a correlation with AERONET of around 0.9. The POLDER estimates suffer from a small positive bias for clean atmospheres, which weakens its statistics. The other aerosol products are of lesser quality, although the SEVIRI products may be of interest for some applications that require a high temporal resolution. The MERIS product shows a very high bias. Over land, only the MODIS product offers a reliable estimate of the total AOD. On the other hand, the polarization-based retrieval using POLDER data allows a better fine mode estimate than that from MODIS. These results suggest the need for a product combining POLDER and MODIS products over land. The paper also analyses how the statistics change with the spatial and temporal thresholds that are used. Spatio-temporal averaging improves the statistics only slightly, which indicates that random errors are not dominant in the error budget. The paper includes various statistical indicators at global scale, and detailed results at individual ground stations can be obtained on request from the authors.

Validation of the MERIS products on large European lakes: Peipsi, Vänern and Vättern

The Medium Resolution Imaging Spectrometer (MERIS/Envisat) was launched in March 2002 for coastal zone monitoring. Preliminary data from MERIS show that its imagery of large lakes is superior to that of other common ocean colour sensors. The main objective of the present study is to evaluate the MERIS data on large European lakes, Vanern and Vattern in Sweden and Peipsi in Estonia/Russia. In these lakes, coloured dissolved organic matter (CDOM) can be a major contributor to the optical properties of the water. Another characteristic of the waters under investigation is the large temporal and spatial variability in the concentrations of chlorophyll (C Chl) and suspended sediments (C TSS). Potentially toxic cyanobacterial blooms occur in Lake Peipsi in late summer. We have compared the MERIS products from the latest reprocessing (finished in March 2006) with available in situ data. There is a reasonably good correlation between the MERIS algal_2 product and the measured C chl over all three lakes, but no correlation was found for other optically active substances. A significant portion of the pixels (up to 90%) are flagged as invalid results after atmospheric correction.

Effects of MERIS L1b radiometric calibration on regional land cover mapping and land products

The information derived from remotely sensed data must be carefully used because there are many sources of error that potentially affect its quality. In this respect, an accurate full calibration process of any sensor is essential because it can minimise various uncertainties and errors that reduce the final quality of the products derived from remotely sensed data. This paper presents several calibration efforts performed on MERIS data and subsequently focuses on the smile effect as well as on the vicarious calibration corrections. The implications of these corrections are evaluated using a MERIS full resolution level 1b image that was acquired over The Netherlands. A thematic approach, based on regional land cover mapping using linear spectral unmixing, and a continuous approach, based on continuous variables (FAPAR, MTCI and NDVI), are used to quantify these implications. Even though MERIS has a very high radiometric quality, results point out that these radiometric effects are consistently present in the final MERIS products. We also conclude that MERIS, after including all potential corrections investigated here, does not exhibit significant (radiometric) deficiencies. However, from a strict point of view, all the proposed radiometric corrections should be applied to the data so that the retrieval of quantitative information can be done with the highest possible quality. The use of fully radiometrically corrected data will also facilitate multitemporal comparisons. Therefore, we finally conclude that a systematic application of all relevant calibration parameters will increase the long term comparability of MERIS measurements in such a way that more emphasis can be put on the retrieval of MERIS products.

Validation of MERIS water products and bio‐optical relationships in the Skagerrak

The MERIS Level 2 Reduced Resolution products for Case 2 water available in September 2003, and conversion functions used in the reference model, have been validated against in situ data from the Skagerrak, collected during the summers of 2002 and 2003. The MERIS water‐leaving reflectance deviated less than 20% from the measured reflectances in the blue‐green part of the spectrum, but it had a tendency of being overestimated by up to 40% in the blue part of the spectrum and underestimated by up to 20% in the red part. The average relative deviation between the MERIS product for total suspended material (dry weight) and the in situ values was 30%. The MERIS values for chlorophyll a were on an average a factor 2 higher than the in situ values, and a new conversion factor should be used for the Skagerrak area. The absorption coefficients for the sum of yellow substance and bleached particles at 442 nm were underestimated by a factor of up to 10 by the MERIS product. The mean values of the spectral slopes of particle scattering and bleached particle absorption were close to the values of the reference model, while the observed slope of yellow substance was slightly lower than the model slope.

Validation of MERIS Level‐2 products in the Baltic Sea, the Namibian coastal area and the Atlantic Ocean

Measurements of water‐leaving reflectance and optically active water constituents in the Baltic Sea, the Namibian coastal area and the Atlantic Ocean were performed to validate MERIS Level‐2 products. Two different validation methods were applied with the recommended match‐up analysis based on comparison of in situ measurements with MERIS Level‐2 products of simultaneous Envisat overpasses and the second analysis on comparison of natural variation ranges with derived MERIS product ranges. The MERIS water‐leaving reflectances correlate to in situ shapes and magnitudes in all investigated areas. The comparison shows mean deviations of MERIS reflectances between 23% and 26% for the current official instrument processing facility (IPF 4.07) but only 20% for the prototype version 7.0 up to now only available to the validation team. The comparison of water constituents shows the underestimation of MERIS ALGAL_2 index, YSBPA and TSM in turbid waters of the Baltic Sea of the current instrument processing facility (IPF 4.07). The mean MERIS ALGAL_1 index is close to in situ values but the mean MERIS ALGAL_2 index, the MERIS YSBPA and MERIS TSM products are still too low in Namibian coastal areas for the prototype version 7.0. The investigations demonstrate the quality improvement of all MERIS Level‐2 products from the current official instrument processing facility to the prototype version 7.0.

Comparison of different satellite sensors in detecting cyanobacterial bloom events in the Baltic Sea

Potentially toxic cyanobacterial blooms occur in the Baltic Sea in the middle of summer. Aggregations of cyanobacteria often form dense subsurface blooms or even surface scum, which are spatially extremely patchy . It has been shown by using bio-optical modelling together with the hyperspectral sensor Hyperion image from the western part of the Gulf of Finland that chlorophyll concentration may vary between one and hundreds of mg m − 3 within the 10-m scale during heavy bloom. The SeaWiFS, MODIS/Aqua and MERIS products over heavy bloom region are compared with each other, the modelling results, with the bio-optical modelling data and the available in situ data. In the early stage of bloom, these sensors give consistent results, which are in the same range as in situ data. During the heavy bloom of cyanobacteria, at the time of surface scum formation, results from different sensors are very variable, the values of chlorophyll concentration may exceed the standard processing limits and atmospheric correction often fails. The good capability of the MERIS and MODIS fine resolution bands to detect cyanobacterial bloom quantitatively is shown.