Search results for "sentinels"
showing 3 items of 3 documents
The Land Surface Temperature Synergistic Processor in BEAM: A Prototype towards Sentinel-3
2016
Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. With the advent of the European Space Agency (ESA) Sentinel 3 (S3) satellite, accurate LST retrieval methodologies are being developed by exploiting the synergy between the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temperature Radiometer (SLSTR). In this paper we explain the implementation in the Basic ENVISAT Toolbox for (A)ATSR and MERIS (BEAM) and the use of one LST algorithm developed in the framework of the Syner…
Importance of dogs as sentinels of West Nile Virus activity in urban and suburban areas
2012
Background: West Nile Virus (WNV) is a virus included in the Japanese encephalitis sero-complex within the genus Flavivirus. In August 2010, cases of West Nile disease were reported for the first time in Sicily. Neurological symptomswere observed in native horses resident in the rural areas around the province of Trapani, in the western part of the island. During the epidemic, important critical questions onwhen the viruswas introduced in the area and aboutwhether the virus had circulated/was circulating in theurban area, emerged and needed to be answered. A retrospective study using dog serum samples was designed to answer these questions. Methods: Between January 2009 and September 2010, …
Deep Gaussian processes for biogeophysical parameter retrieval and model inversion
2020
Parameter retrieval and model inversion are key problems in remote sensing and Earth observation. Currently, different approximations exist: a direct, yet costly, inversion of radiative transfer models (RTMs); the statistical inversion with in situ data that often results in problems with extrapolation outside the study area; and the most widely adopted hybrid modeling by which statistical models, mostly nonlinear and non-parametric machine learning algorithms, are applied to invert RTM simulations. We will focus on the latter. Among the different existing algorithms, in the last decade kernel based methods, and Gaussian Processes (GPs) in particular, have provided useful and informative so…