Objective
Remote sensing provides the only viable solution for obtaining estimates of both surface fluxes and soil moisture content (SMC) at the spatiotemporal scales and accuracy levels required by many applications. Despite the wide range of methods available and the recognition by the space agencies globally for the necessity in estimating those parameters, global operational mapping of the above parameters from remote sensing is lacking or is underdeveloped, particularly so in Europe. Generally, these methods vary including also methods based on the information derived from a scatterplot developed between satellite-derived vegetation index (VI) and surface radiometric temperature (Ts) measures. The latter group also includes some approaches based on the combined use of a Ts/VI scatterplot with simulations from a biosphere model, specifically a Soil Vegetation Atmosphere Transfer (SVAT) model, the so-called “triangle” method. The operational potential capability of the technique is seen and by the fact that variants of it are currently investigated in deriving operational products by Space agencies in both Europe (ESA) and United States (NPOESS).
In TRANSFOrM-EO, recognising the gap that currently exists in the operational retrieval of both surface heat fluxes and Mo from remote sensing sensors as well as the strong relevance of the so-called Ts/VI-based “triangle” method to a number of key efforts ongoing for the operational retrieval of those parameters, we propose to develop a fundamental understanding of the ability of the “triangle” in deriving LE/H fluxes as well as of SMC. In addition, we aim to provide a first investigation of the ability of the technique in deriving the above parameters when using advanced technologically remote sensing sensors, specifically the EUMETSAT SEVIRI radiometer on-board the recently launched MSG-3 platform as well as of the GMES Sentinels 2 and 3 that have already been planned to be launched in 2013/2014.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologyenvironmental engineeringremote sensing
- natural sciencesearth and related environmental sciencesatmospheric sciencesmeteorologybiosphera
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
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Call for proposal
FP7-PEOPLE-2012-CIG
See other projects for this call
Coordinator
SY23 3BF Aberystwyth
United Kingdom