Medium Resolution Imaging Spectrometer Measurements Research Articles

Remote Sensing of Secchi Depth in Highly Turbid Lake Waters and Its Application with MERIS Data

The Secchi disk depth (ZSD, m) has been used globally for many decades to represent water clarity and an index of water quality and eutrophication. In recent studies, a new theory and model were developed for ZSD, which enabled its semi-analytical remote sensing from the measurement of water color. Although excellent performance was reported for measurements in both oceanic and coastal waters, its reliability for highly turbid inland waters is still unknown. In this study, we extend this model and its evaluation to such environments. In particular, because the accuracy of the inherent optical properties (IOPs) derived from remote sensing reflectance (Rrs, sr−1) plays a key role in determining the reliability of estimated ZSD, we first evaluated a few quasi-analytical algorithms (QAA) specifically tuned for turbid inland waters and determined the one (QAATI) that performed the best in such environments. For the absorption coefficient at 443 nm (a(443), m−1) ranging from ~0.2 to 12.5 m−1, it is found that the QAATI-derived absorption coefficients agree well with field measurements (r2 > 0.85, and mean absolute percentage difference (MAPD) smaller than ~39%). Furthermore, with QAATI-derived IOPs, the MAPD was less than 25% between the estimated and field-measured ZSD (r2 > 0.67, ZSD in a range of 0.1–1.7 m). Furthermore, using matchup data between Rrs from the Medium Resolution Imaging Spectrometer (MERIS) and in-situ ZSD, a similar performance in the estimation of ZSD from remote sensing was obtained (r2 = 0.73, MAPD = 37%, ZSD in a range of 0.1–0.9 m). Based on such performances, we are confident to apply the ZSD remote sensing scheme to MERIS measurements to characterize the spatial and temporal variations of ZSD in Lake Taihu during the period of 2003–2011.

Investigation of Ground Deformation in Taiyuan Basin, China from 2003 to 2010, with Atmosphere-Corrected Time Series InSAR

Excessive groundwater exploitation is common through the Taiyuan basin, China, and is well known to result in ground subsidence. However, most ground subsidence studies in this region focus on a single place (Taiyuan city), and thus fail to demonstrate the regional extent of the deformation phenomena in the whole basin. In this study, we used Interferometric Synthetic Aperture Radar (InSAR) time series analysis to investigate land subsidence across the entire Taiyuan basin region. Our data set includes a total of 75 ENVISAT ASAR images from two different frames acquired from August 2003 to September 2010 and 33 TerraSAR-X scenes spanning between March 2009 and March 2010. ERA-Interim reanalysis was used to correct the stratified delay to reduce the bias expected from the systematic components of tropospheric delay. The residual delay after correction of stratified delay can be considered as a stochastic component and be mitigated through spatial-temporal filtering. A comparison with MERIS (Medium-Resolution Imaging Spectrometer) measurements indicates that our atmospheric corrections improved agreement over the conventional spatial-temporal filtering by about 20%. The displacement results from our atmosphere-corrected time series InSAR were further validated with continuous GPS data. We found eight subsiding centers in the basin and a surface uplift to the north of Taiyuan city. The causes of ground deformation are analyzed and discussed in relation to gravity data, pre-existing faults, and types of land use.

Correcting InSAR Topographically Correlated Tropospheric Delays Using a Power Law Model Based on ERA-Interim Reanalysis

Tropospheric delay caused by spatiotemporal variations in pressure, temperature, and humidity in the lower troposphere remains one of the major challenges in Interferometric Synthetic Aperture Radar (InSAR) deformation monitoring applications. Acquiring an acceptable level of accuracy (millimeter-level) for small amplitude surface displacement is difficult without proper delay estimation. Tropospheric delay can be estimated from the InSAR phase itself using the spatiotemporal relationship between the phase and topography, but separating the deformation signal from the tropospheric delay is difficult when the deformation is topographically related. Approaches using external data such as ground GPS networks, space-borne spectrometers, and meteorological observations have been exploited with mixed success in the past. These methods are plagued, however, by low spatiotemporal resolution, unfavorable weather conditions or limited coverage. A phase-based power law method recently proposed by Bekaert et al. estimates the tropospheric delay by assuming the phase and topography following a power law relationship. This method can account for the spatial variation of the atmospheric properties and can be applied to interferograms containing topographically correlated deformation. However, the parameter estimates of this method are characterized by two limitations: one is that the power law coefficients are estimated using the sounding data, which are not always available in a study region; the other is that the scaled factor between band-filtered topography and phase is inverted by least squares regression, which is not outlier-resistant. To address these problems, we develop and test a power law model based on ERA-Interim (PLE). Our version estimates the power law coefficients by using ERA-Interim (ERA-I) reanalysis. A robust estimation technique was introduced in the PLE method to estimate the scaled factor, which is insensitive to outliers. We applied the PLE method to ENVISAT ASAR images collected over Southern California, US, and Tianshan, China. We compared tropospheric corrections estimated from using our PLE method with the corrections estimated using the linear method and ERA-I method. Accuracy was evaluated by using delay measurements from the Medium Resolution Imaging Spectrometer (MERIS) onboard the ENVISAT satellite. The PLE method consistently delivered greater standard deviation (STD) reduction after tropospheric corrections than both the linear method and ERA-I method and agreed well with the MERIS measurements.

Towards a practical remote-sensing model of suspended sediment concentrations in turbid waters using MERIS measurements

A new empirical index, termed the normalized suspended sediment index (NSSI), is proposed to predict total suspended sediment (TSS) concentrations in inland turbid waters using Medium Resolution Imaging Spectrometer (MERIS) full-resolution (FR) 300 m data. The algorithm is based on the normalized difference between two MERIS spectral bands, 560 and 760 nm. NSSI shows its potential in application to our study region – Poyang Lake – the largest freshwater lake in China. An exponential function (R2 = 0.90, p < 0.01) accurately explained the variance in the in situ data and showed better performance for the TSS range 10–524 mg l−1. The algorithm was then validated with TSS estimates using an atmospheric-corrected MERIS FR image. The validation showed that the NSSI algorithm was a more robust TSS algorithm than the band-ratio algorithms. Findings of this research imply that NSSI can be successfully used on MERIS images to obtain TSS in Poyang Lake. This work provided a practical remote-sensing approach to estimate TSS in the optically and hydrologically complex Poyang Lake and the method can be easily extended to other similar waters.

Remote sensing of diffuse attenuation coefficient of photosynthetically active radiation in Lake Taihu using MERIS data

Especially for a shallow and extremely turbid lake, light availability in the water column can determine the euphotic zone, and the horizontal and vertical distribution of algae species. Light attenuation is traditionally quantified as the diffuse attenuation coefficient of the photosynthetically available radiation (Kd(PAR)). Global coverage of Kd(PAR) at high spatial and temporal resolution can be provided by satellite measurements, and these data can be used to improve our understanding of the physical, chemical and biological processes in Lake Taihu, a large shallow lake in China, of considerable importance as a source of drinking water for several large cities.The primary dominated contributor to Kd(PAR) was determined firstly using linear regression. There was a significant positive correlation between Kd(PAR) and concentrations of total suspended matter (TSM). The determination coefficient between Kd(PAR) and TSM (R2=0.91) was significantly higher than that between Kd(PAR) and chlorophyll-a concentrations (Chl-a) (R2=0.11), and between Kd(PAR) and absorption of chromophoric dissolved organic matter (CDOM) (R2=0.01). Our results therefore could demonstrate that TSM usually plays a dominant role in the attenuation of light in Lake Taihu.A retrieval model of Kd(PAR) values for Lake Taihu was subsequently developed using top-of-atmosphere (TOA) radiance of Medium Resolution Imaging Spectrometer (MERIS) image data at band 10, which was strongly correlated with in situ Kd(PAR) (R2=0.74, p<0.005, N=48). In contrast, the atmospheric corrected reflectance of MERIS image data was not strongly correlated with in situ Kd(PAR). Thus, atmospheric correction was not a prerequisite for estimations of Kd(PAR) in this highly turbid and hyper-eutrophic lake, and a simple empirical model of the Kd(PAR) estimation for Lake Taihu was effective.With the simple model, the seasonal and spatial distributions of Kd(PAR) in Lake Taihu were studied using the MERIS measurements from 2003 to 2010. Our results show distinct seasonal, spatial, and wind driven, Kd(PAR) values in Lake Taihu. The highest and the lowest Kd(PAR) values were found in summer and in winter, respectively. The increase of Kd(PAR) in summer can be attributed to the phytoplankton blooms, and wind-driven sediment resuspension. Spatially, the Kd(PAR) values were high in the southern part and the lake center, and low Kd(PAR) in East Lake Taihu. Based on the MERIS derived Kd(PAR) values, a significant correlation was found between Kd(PAR) and wind speeds, suggesting a critical role of wind speeds in the Kd(PAR) variations in Lake Taihu.

Empirical Correction of Stray Light within the MERIS Oxygen A-Band Channel

Abstract Spaceborne spectrometers like the Medium Resolution Imaging Spectrometer (MERIS) on board the Environmental Satellite (Envisat) are widely used for the remote sensing of atmospheric and oceanic properties and make an important contribution to the monitoring of the earth’s atmosphere system. To enable retrievals with high accuracy, the spectral and radiometric properties of the instruments have to be characterized with high precision. One of the main sources of radiometric errors is stray light caused by multiple reflections and scattering at the optical elements within the instruments. If not corrected for properly, the stray light–induced offsets of measured intensity can lead to significant errors in the derived parameters. The effect of stray light is particularly momentous in the case of measurements inside strong absorption bands like the oxygen A band at 0.76 μm or the ρστ absorption band of water vapor around 0.9 μm. For example, the retrieval of surface and cloud-top pressure from MERIS measurements in the O2 A band can be biased because of an insufficient correction of stray light in the operational processing chain. To correct for the residual stray light influence after the operational stray light correction in the O2 A-band channel of MERIS, an empirical stray light correction of the measured radiance at 0.76 μm has been developed based on optimizing the coefficients of a simple brightness-dependent stray light model. The optimal model coefficients were found by adjusting the retrievals of surface and cloud-top pressure to accurate reference data for several selected scenes. To account for the limited accuracy of the MERIS spectral calibration, the center wavelength of the O2 A-band channel was additionally adjusted within a ±0.1-nm tolerance range. The correction was tested on a variety of clear and cloudy scenes at different locations by applying the surface and cloud-top pressure retrieval algorithms to data recorded over the whole lifetime of MERIS. The results indicate the potential to greatly improve the accuracy of the retrieved pressure values using the proposed correction factors.

Remote Sensing of Multilayer Cloud-Top Pressure Using Combined Measurements of MERIS and AATSR on board Envisat

Abstract A novel and unique algorithm for the retrieval of multilayer cloud-top pressure is presented, relying on synergetic observations of the Medium Resolution Imaging Spectrometer (MERIS) and Advanced Along Track Scanning Radiometer (AATSR) on board the Environmental Satellite (Envisat). The retrieval is based on the exploitation of the differing signals observed in the thermal infrared spectral region (AATSR) and the oxygen A band at 0.76 μm (MERIS). Past studies have shown that the cloud-top pressure retrieved from MERIS measurements is highly accurate in the case of low single-layered clouds. In contrast, in the presence of multilayered clouds like cirrus overlying water clouds, the derived cloud height is biased. In this framework, an optimal estimation algorithm for the correction of the measured O2 A transmission for the influence of the upper cloud layer was developed. The algorithm is best applicable in cases of optically thin cirrus (1 ≤ τ ≤ 5) above optically thick water clouds (τ &amp;gt; 5), as found frequently in the vicinity of convective or frontal cloud systems. The split-window brightness temperature difference technique is used for the identification of suitable cases. The sensitivities of the AATSR and MERIS measurements to multilayered clouds are presented and discussed, revealing that in the case of dual-layered clouds, the AATSR-derived cloud height is close to the upper cloud layer, even if it is optically thin. In contrast, the cloud height retrieved from MERIS measurements represents the optical center of the cloud system, which is close to the lower layer in cases where the upper layer is optically thin. Two case studies of convective, multilayered cloud systems above the northern Atlantic Ocean are shown, demonstrating the plausibility of the approach. The presented work is relevant especially in view of the upcoming Global Monitoring for Environment and Security Sentinel-3 satellite to be launched in 2012 that will carry the respective MERIS and AATSR follow-up instruments Ocean and Land Colour Instrument (OLCI) and Sea and Land Surface Temperature Radiometer (SLSTR).

Remote sensing of cyanobacteria-dominant algal blooms and water quality parameters in Zeekoevlei, a small hypertrophic lake, using MERIS

Eutrophication and cyanobacterial algal blooms present an increasing threat to the health of freshwater ecosystems and to humans who use these resources for drinking and recreation. Remote sensing is being used increasingly as a tool for monitoring these phenomena in inland and near-coastal waters. This study uses the Medium Resolution Imaging Spectrometer (MERIS) to view Zeekoevlei, a small hypertrophic freshwater lake situated on the Cape Flats in Cape Town, South Africa, dominated by Microcystis cyanobacteria. The lake's small size, highly turbid water, and covariant water constituents present a challenging case for both algorithm development and atmospheric correction. The objectives of the study are to assess the optical properties of the lake, to evaluate various atmospheric correction procedures, and to compare the performance of empirical and semi-analytical algorithms in hypertrophic water. In situ water quality parameter and radiometric measurements were made simultaneous to MERIS overpasses. Upwelling radiance measurements at depth 0.66 m were corrected for instrument self-shading and processed to water-leaving reflectance using downwelling irradiance measurements and estimates of the vertical attenuation coefficient for upward radiance, K u, generated from a simple bio-optical model estimating the total absorption, a( λ), and backscattering coefficients, b b( λ). The normalised water-leaving reflectance was used for assessing the accuracy of image-based Dark Object Subtraction and 6S Radiative Transfer Code atmospheric correction procedures applied to MERIS. Empirical algorithms for estimating chlorophyll a (Chl a), Total Suspended Solids (TSS), Secchi Disk depth ( z SD) and absorption by CDOM ( a CDOM) were derived from simultaneously collected in situ and MERIS measurements. The empirical algorithms gave high correlation coefficient values, although they have a limited ability to separate between signals from covariant water constituents. The MERIS Neural Network algorithms utilised in the standard Level 2 Case 2 waters product and Eutrophic Lakes processor were also used to derive water constituent concentrations. However, these failed to produce reasonable comparisons with in situ measurements owing to the failure of atmospheric correction and divergence between the optical properties and ranges used to train the algorithms and those of Zeekoevlei. Maps produced using the empirical algorithms effectively show the spatial and temporal variability of the water quality parameters during April 2008. On the basis of the results it is argued that MERIS is the current optimal sensor for frequent change detection applications in inland waters. This study also demonstrates the considerable potential value for simple TOA algorithms for hypertrophic systems. It is recommended that regional algorithm development be prioritized in southern Africa and that remote sensing be integrated into future operational water quality monitoring systems.

Determination of the cloud fraction in the SCIAMACHY ground scene using MERIS spectral measurements

SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY) is a passive remote sensing spectrometer observing backscattered radiation from the atmosphere and the Earth's surface, in the wavelength range between 240 and 2380 nm. The instrument is onboard ENVironmental SATellite (ENVISAT) which was launched on 1 March 2002. The Medium Resolution Imaging Spectrometer (MERIS) is also one of the 10 instruments onboard the ENVISAT satellite. MERIS is a 68.5° field-of-view nadir-pointing imaging spectrometer which measures the solar radiation reflected by the Earth in 15 spectral bands (visible and near-infrared). It obtains a global coverage of the Earth in three days. Its main objective is to measure sea colour and quantify ocean chlorophyll content and sediment, thus providing information on the ocean carbon cycle and thermal regime. It is also used to derive the cloud top height, aerosol and cloud optical thickness, and water vapour column. The ground spatial resolution of the instrument is 260 m × 290 m. This paper is aimed at determining the cloud fraction in SCIAMACHY pixels (typically, 30 km × 60 km ground scenes) using MERIS observations and number of thresholds for MERIS top-of-atmosphere reflectances and their ratios. Thresholds utilize the fact that clouds are bright white objects having similar reflectances in the blue and red. The MERIS cloud fraction has been derived for a number of SCIAMACHY states with area of 916 km × 400 km. The results are compared with correspondent cloud fractions obtained using SCIAMACHY polarization measurement devices (PMDs). Large differences are found between cloud fractions derived using SCIAMACHY and MERIS measurements. It is recommended to use highly spatially resolved MERIS observations instead of SCIAMACHY PMD measurements to retrieve cloud fractions in SCIAMACHY pixels. The improvements advised will enhance SCIAMACHY trace gas and cloud retrievals in the presence of broken cloud fields.

The Retrieval of Land Surface Pressure from MERIS Measurements in the Oxygen A Band

AbstractMeasurements of the Medium-Resolution Imaging Spectrometer (MERIS) on the Environmental Satellite (Envisat) are used for the retrieval of surface pressure above land and ice surfaces. The algorithm is based on the exploitation of gaseous absorption in the oxygen A band at 762 nm. The strength of absorption is directly related to the average photon pathlength, which in clear-sky cases above bright surfaces is mainly determined by the surface pressure, with minor influences from scattering at aerosols.Sensitivity studies regarding the influences of aerosol optical thickness and scale height and the temperature profile on the measured radiances are presented. Additionally, the sensitivity of the retrieval to the accuracy of the spectral characterization of MERIS is quantified. The algorithm for the retrieval of surface pressure (SPFUB) is presented and validated against surface pressure maps constructed from ECMWF sea level pressure forecasts in combination with digital elevation model data. The accuracy of SPFUB was found to be within 10 hPa above ice surfaces at Greenland and 15 hPa above desert and mountain scenes in northern Africa and southwest Asia. In a case study above Greenland the accuracy of SPFUB could be enhanced to be better than 3 hPa by spatial averaging over areas of 40 km × 40 km.

Retrieval of atmospheric and oceanic properties from MERIS measurements: A new Case‐2 water processor for BEAM

A freely available data processor for the B asic E RS & ENVISAT ( A )ATSR and M ERIS Toolbox (BEAM) was developed to retrieve atmospheric and oceanic properties above and of Case‐2 waters from Medium Resolution Imaging Spectrometer (MERIS) Level1b data. The processor was especially designed for European coastal waters and uses MERIS Level1b Top‐Of‐Atmosphere (TOA) radiances to retrieve atmospherically corrected remote sensing reflectances at the Bottom‐Of‐Atmosphere (BOA), spectral aerosol optical thicknesses (AOT) and the concentration of three water constituents, namely chlorophyll‐a (CHL), total suspended matter (TSM) and the absorption of yellow substance at 443 nm (YEL). The retrieval is based on four separate artificial neural networks which were trained on the basis of the results of extensive radiative transfer (RT) simulations by taking various atmospheric and oceanic conditions into account. The accuracy of the retrievals was acquired by comparisons with concurrent in situ ground measurements and was published in full detail elsewhere. For the remote sensing reflectance product a mean absolute percentage error (MAPE) of 18% was derived within the spectral range 412.5–708.75 nm while the accuracy of the AOT at 550 nm in terms of MAPE was calculated to be 40%. The accuracies for CHL, TSM and YEL were derived from match‐up analysis with MAPEs of 50%, 60% and 71%, respectively.

The semianalytical cloud retrieval algorithm for SCIAMACHY II. The application to MERIS and SCIAMACHY data

Abstract. The SemiAnalytical CloUd Retrieval Algorithm (SACURA) is applied to the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. In particular, we derive simultaneously cloud optical thickness (COT) and cloud top height (CTH), using SCIAMACHY measurements in the visible (442 nm, COT) and in the oxygen A-band (755–775 nm, CTH). Some of the results obtained are compared with those derived from the Medium Resolution Imaging Spectrometer (MERIS), which has better spatial resolution and observes almost the same scene as SCIAMACHY. The same cloud algorithm is applied to both MERIS and SCIAMACHY data. In addition, we perform the vicarious calibration of SCIAMACHY at the wavelength 442 nm, using MERIS measurements at the same wavelength. Differences in the retrieved COT for the same cloud field obtained using MERIS and SCIAMACHY measurements are discussed.

Simulation of MERIS measurements above selected ocean waters

We report on a number of radiative transfer calculations that have been performed in order to predict Medium Resolution Imaging Spectrometer (MERIS) measurements for the anticipated spectral bands and observation geometries for selected open ocean and coastal waters. The simulations show that, above coastal waters, significant levels of the water-leaving radiance must be expected in several of the MERIS channels dedicated to the atmospheric correction. These channels should be included in the algorithms to retrieve concentrations of water constituents. In addition, sunglint may affect large parts of MERIS satellite images, especially in the lower latitudes between ca 20 N and 20 S. Radiative transfer calculations similar to those presented here are used to derive algorithms for the assessment of constituent concentrations in Case II waters from ocean colour measurements.