1,355,971 research outputs found
Land cover classification using multi-temporal MERIS vegetation indices
Get PDFThe spectral, spatial, and temporal resolutions of Envisat's Medium Resolution Imaging Spectrometer (MERIS) data are attractive for regional- to global-scale land cover mapping. Moreover, two novel and operational vegetation indices derived from MERIS data have considerable potential as discriminating variables in land cover classification. Here, the potential of these two vegetation indices (the MERIS global vegetation index (MGVI), MERIS terrestrial chlorophyll index (MTCI)) was evaluated for mapping eleven broad land cover classes in Wisconsin. Data acquired in the high and low chlorophyll seasons were used to increase inter-class separability. The two vegetation indices provided a higher degree of inter-class separability than data acquired in many of the individual MERIS spectral wavebands. The most accurate landcover map (73.2%) was derived from a classification of vegetation index-derived data with a support vector machine (SVM), and was more accurate than the corresponding map derived from a classification using the data acquired in the original spectral wavebands
Assessment of the potential of MERIS near-infrared water vapour products to correct ASAR interferometric measurements
Get PDFAtmospheric water vapour is a major limitation for high precision Interferometric Synthetic Aperture Radar (InSAR) applications due to its significant impact on microwave signals. We propose a statistical criterion to test whether an independent water vapour product can reduce water vapour effects on InSAR interferograms, and assess the potential of the Medium Resolution Imaging Spectrometer (MERIS) near-infrared water vapour products for correcting Advanced SAR (ASAR) data. Spatio-temporal comparisons show c. 1.1mm
agreement between MERIS and GPS/radiosonde water vapour products in terms of standard deviations. One major limitation with the use of MERIS water vapour products is the frequency of cloud free conditions. Our analysis indicates that in spite of the low global cloud free conditions (~25%), the frequency can be much higher for certain areas such as Eastern Tibet (~38%) and Southern
California (~48%). This suggests that MERIS water vapour products show potential for correcting ASAR interferometric measurements in certain regions
In situ validation of MERIS marine reflectance off the southwest Iberian Peninsula: assessment of vicarious adjustment and corrections for near-land adjacency
Get PDFWater-leaving reflectance (ρw) data from the European Space Agency ocean colour sensor Medium Resolution Imaging Spectrometer (MERIS) was validated with in situ ρw 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 ρw, 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 ρw 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 ρw 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 ρw and in situ ρw were much better for Sagres than for BOUSSOLE. Strikingly, the matchup statistics for ρw 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
Satellite estimates of wide-range suspended sediment concentrations in Changjiang (Yangtze) estuary using MERIS data
Get PDFThe Changjiang (Yangtze) estuarine and coastal waters are characterized by suspended sediments over a wide range of concentrations from 20 to 2,500 mg l-1. Suspended sediment plays important roles in the estuarine and coastal system and environment. Previous algorithms for satellite estimates of suspended sediment concentration (SSC) showed a great limitation in that only low to moderate concentrations (up to 50 mg l-1) could be reliably estimated. In this study, we developed a semi-empirical radiative transfer (SERT) model with physically based empirical coefficients to estimate SSC from MERIS data over turbid waters with a much wider range of SSC. The model was based on the Kubelka–Munk two-stream approximation of radiative transfer theory and calibrated using datasets from in situ measurements and outdoor controlled tank experiments. The results show that the sensitivity and saturation level of remote-sensing reflectance to SSC are dependent on wavelengths and SSC levels. Therefore, the SERT model, coupled with a multi-conditional algorithm scheme adapted to satellite retrieval of wide-range SSC, was proposed. Results suggest that this method is more effective and accurate in the estimation of SSC over turbid water
Validating time series of a combined GPS and MERIS Integrated Water Vapor product
No full textIncreased knowledge of atmospheric water vapor can improve weather predictions and is expected to reduce errors in products derived from GPS and (In)SAR data. At GPS ground stations Integrated Water Vapor (IWV) is estimated from the GPS signal delay with a high temporal resolution. The Envisat MERIS spectrometer obtains spatially dense IWV observations but at limited moments in time. In this research the additional value of MERIS IWV is evaluated when added to GPS IWV for the purpose of obtaining a high quality spatial-temporalwater vapor product. At each of 39 stations, first GPS IWV from surrounding stations is used to produce a two months time series of IWV with a temporal resolution of one hour. Then both GPS and MERIS IWV are used together. The two resulting time series are validated against direct GPS IWV as measured at the station.Aerospace Engineerin
MERIS Eastern Australia Time Series
No full textThe allocation is to facilitate a trend analysis on eutrophication status of inland waters in Eastern Australia. It is part of a global project called GLASS. The allocation is used to house the images of Eastern Australia from the MERIS satellite for the period 2003-2012. The research data would be useful to water resource industry and researchers
A new approach for estimating northern peatland gross primary productivity using a satellite-sensor-derived chlorophyll index
No full textCarbon flux models that are largely driven by remotely sensed data can be used to estimate gross primary productivity (GPP) over large areas, but despite the importance of peatland ecosystems in the global carbon cycle, relatively little attention has been given to determining their success in these ecosystems. This paper is the first to explore the potential of chlorophyll-based vegetation index models for estimating peatland GPP from satellite data. Using several years of carbon flux data from contrasting peatlands, we explored the relationships between the MERIS terrestrial chlorophyll index (MTCI) and GPP, and determined whether the inclusion of environmental variables such as PAR and temperature, thought to be important determinants of peatland carbon flux, improved upon direct relationships. To place our results in context, we compared the newly developed GPP models with the MODIS (Moderate Resolution Imaging Spectrometer) GPP product. Our results show that simple MTCI-based models can be used for estimates of interannual and intra-annual variability in peatland GPP. The MTCI is a good indicator of GPP and compares favorably with more complex products derived from the MODIS sensor on a site-specific basis. The incorporation of MTCI into a light use efficiency type model, by means of partitioning the fraction of photosynthetic material within a plant canopy, shows most promise for peatland GPP estimation, outperforming all other models. Our results demonstrate that satellite data specifically related to vegetation chlorophyll content may ultimately facilitate improved quantification of peatland carbon flux dynamics
Integration of InSAR time series analysis and water vapour correction for mapping postseismic deformation after the 2003 Bam (Iran) Earthquake
Get PDFAtmospheric water-vapor effects represent a major limitation of interferometric synthetic aperture radar (InSAR) techniques, including InSAR time-series (TS) approaches (e.g., persistent or permanent scatterers and small-baseline subset). For the first time, this paper demonstrates the use of InSAR TS with precipitable water-vapor (InSAR TS + PWV) correction model for deformation mapping. We use MEdium Resolution Imaging Spectrometer (MERIS) near-infrafred (NIR) water-vapor data for InSAR atmospheric correction when they are available. For the dates when the NIR data are blocked by clouds, an atmospheric phase screen (APS) model has been developed to estimate atmospheric effects using partially water-vapor-corrected interferograms. Cross validation reveals that the estimated APS agreed with MERIS-derived line-of-sight path delays with a small standard deviation (0.3–0.5 cm) and a high correlation coefficient (0.84–0.98). This paper shows that a better TS of postseismic motion after the 2003 Bam (Iran) earthquake is achievable after reduction of water-vapor effects using the InSAR TS + PWV technique with coincident MERIS NIR water-vapor data
Application of clustering techniques to multispectral optical data over the ocean
Get PDFMERIS, on Envisat, provides high-resolution radiometric data at nine discrete channels in the visible band. This paper looks at the potential of an unsupervised classification technique for utilizing these multi-spectral data to provide better discrimination between water masses according to their optical properties, and in particular whether phytoplankton groups can be distinguished. Although the majority of data do show a spectral peak associated with chlorophyll's red fluorescence line, clustering using only the red bands was found to separate out coastal waters according to their sediment content. Red-end classification also appeared to identify sub-pixel cloud, and demonstrate that the smile correction had not removed all the striping from the data. Classification using bands from the blue-green end showed a response to changes in chlorophyll concentration, but also indicated other variations. However, without in situ data no firm conclusions can be drawn on which phytoplankton groupings are present
Radiometric validation of multi-spectral ocean colour satellite data in high biomass Southern Benguela waters
No full textIncludes bibliographical references (leaves 106-117).This study forms the first step towards a comprehensive ocean colour satellite validation strategy for the Southern Benguela region, and underlines the value of a statistical radiometric validation as a prerequisite to any geophysical validation exercise. A radiometric validation exercise was performed using co-incident MERIS RR data and in situ radiometer data from a mooring in the Southern Benguela near Lambert's Bay during the late summer bloom seasons of 2005 and 2006. The data are typified by very high biomass conditions. Sources of error associated with the in situ data are assessed and the magnitudes quantified. The satellite data is examined with particular reference to uncertainty derived from the atmospheric correction processes, which perform unreliably in many of the matchup instances. Results show that the accuracy of the atmospheric correction does not appear to be related to the in-water constituents and is more likely due to atmospheric variability or aerosol features that are not addressed in the models employed by the correction processes. It is also shown that while the radiometric data display a consistent bias in the red region of the spectrum, good correlation with the satellite measurements is observed here under high biomass conditions, underlining the importance of the red wavebands for coastal remote sensing. Recommendations towards the development of a comprehensive regional validation strategy include the establishment of low-cost measurement protocols for high biomass conditions, as well as further investigations into regional atmospheric variability to improve confidence in the atmospheric correction procedures
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