Mainly digital images are under sampled. It is the same for SPOT digital image satellite. The very meaning is that the instrument is too much powerful for this sampling. The worth side effect is that artifacts (aliasi...
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ISBN:
(纸本)0819441880
Mainly digital images are under sampled. It is the same for SPOT digital image satellite. The very meaning is that the instrument is too much powerful for this sampling. The worth side effect is that artifacts (aliasing) are introduced in the image, the good side is that images can be improved if the sampling density is increased. In this paper we use images from the two HRVIR instruments onboard SPOT1-4 satellite to multiply by a factor two the density and the resolution of the image.
This paper investigates the improvements to the quality of ocean color data using an appropriate choice of ancillary data for National Oceanic and Atmospheric Administration (NOAA) operational ocean color data process...
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This paper investigates the improvements to the quality of ocean color data using an appropriate choice of ancillary data for National Oceanic and Atmospheric Administration (NOAA) operational ocean color dataprocessing, which requires routine ocean color product production in near real time. The ancillary data, such as the total column ozone amount, sea surface wind speed, atmospheric pressure, and total column water-vapor amount, are required for satellite ocean color dataprocessing for deriving ocean color products, e. g., normalized water-leaving radiance spectra data, chlorophyll-a concentration, water diffuse attenuation coefficient, etc. Currently, NOAA's CoastWatch program uses the climatology ancillary data for the near-real-time ocean color dataprocessing. Alternative ancillary data sets that can replace the climatology data for the near-real-time ocean color dataprocessing have been investigated and studied. The studies were carried out from four selected NOAA CoastWatch regions covering the U. S. coastal and Hawaii regions and for four months (January, April, July, and October), representing the four seasons. Based on the evaluation results, we propose to use the ancillary data produced from the Global Forecast System (GFS) model for the NOAA operational ocean color dataprocessing, as well as for any other near-real-time dataprocessing that requires ancillary data inputs. The effects of using the GFS model data on the accuracy of the derived ocean color products are also investigated and discussed.
Coastal zones and shelf-seas are important for tourism, commercial fishing and aquaculture. As a result the importance of good water quality within these regions to support life is recognised worldwide and a number of...
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Coastal zones and shelf-seas are important for tourism, commercial fishing and aquaculture. As a result the importance of good water quality within these regions to support life is recognised worldwide and a number of international directives for monitoring them now exist. This paper describes the AlgaRisk water quality monitoring demonstration service that was developed and operated for the UK Environment Agency in response to the microbiological monitoring needs within the revised European Union Bathing Waters Directive. The AlgaRisk approach used satellite Earth observation to provide a near-real time monitoring of microbiological water quality and a series of nested operational models (atmospheric and hydrodynamic-ecosystem) provided a forecast capability. For the period of the demonstration service (2008-2013) all monitoring and forecast datasets were processed in near-real time on a daily basis and disseminated through a dedicated web portal, with extracted data automatically emailed to agency staff. Near-real time dataprocessing was achieved using a series of supercomputers and an Open Grid approach. The novel web portal and java-based viewer enabled users to visualise and interrogate current and historical data. The system description, the algorithms employed and example results focussing on a case study of an incidence of the harmful algal bloom Karenia mikimotoi are presented. Recommendations and the potential exploitation of web services for future water quality monitoring services are discussed. (C) 2015 Elsevier Ltd. All rights reserved.
A new algorithm for retrieving the total content of atmospheric fine particulate matter (FPM) (particles with a size of less than 1.0 and 2.5 mu m) from multispectral satellite images in visible and IR regions of the ...
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A new algorithm for retrieving the total content of atmospheric fine particulate matter (FPM) (particles with a size of less than 1.0 and 2.5 mu m) from multispectral satellite images in visible and IR regions of the electromagnetic spectrum is described. The algorithm is based on the regression relations between the top of atmosphere (TOA) reflectance, microphysical parameters of aerosol, and geometrical parameters of the satellite scene. The regression equations are built based on the calculated TOA brightness in the spectral channels of the satellite instrument for the ensemble of randomly generated parameters of the atmospheric radiative transfer model and geometrical parameters of the satellite scenes. Subsequently, this allows real-time mapping of the atmospheric FPM pollution directly from the satellite images without solving ill-posed inverse problems based on the solar radiation transfer in the atmosphere and aerosol light scattering. The algorithm suggested is implemented and tested for the MERIS (Medium Resolution Imaging Spectrometer) satellite instrument. Comparison of the MERIS-retrieved total content of the atmospheric FPM with AERONET (Aerosol Robotic Network) data shows a standard deviation of similar to 0.5 mu g/cm(2). The applicability of the algorithm developed to real-time monitoring of the regional and transboundary transport of the atmospheric FPM pollutants during wildfires is demonstrated.
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