Objective
"Agricultural drought impacts global food security as well as financial flexibility of countries. Considering the natural variability
of climate, agricultural drought is common phenomenon within appropriate time-frame, while the expected change in climate
and the expected decrease in available water resources will further increase the stress exerted on vegetation. Precipitation-based indices are commonly used to trace the current status of the potential drought, while such indicators may miss the
onset and only give reliable information about long-term events. On the other hand agricultural drought and its onset can be
accurately traced via monitoring of soil moisture, which has been recently shown to be a skillful predictor of vegetation
conditions. In this study, soil moisture datasets from multiple platforms will be merged in least squares framework to obtain
an optimal soil moisture estimate, while the optimality will be assured through the use of product specific error estimates
obtained separately using triple collocation error estimation methodology. Validation will be performed via investigation of
lagged-correlation between soil moisture and Normalized Difference Vegetation Index (NDVI) which is very sensitive to the
conditions of vegetation and can be accurately obtained from space through remote sensing. In particular, this study will
consider merging The Atmosphere-Land Exchange Inverse (ALEXI)-, Noah-, Soil Moisture Ocean Salinity (SMOS)-, and
Advanced Scatterometer on METOP (ASCAT)-based soil moisture information. Resulting optimally merged soil moisture
product is expected to have higher skill in predicting NDVI than individual products alone."
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. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencesearth and related environmental scienceshydrology
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- engineering and technologyenvironmental engineeringremote sensing
- medical and health scienceshealth sciencesnutrition
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Call for proposal
FP7-PEOPLE-2013-CIG
See other projects for this call
Coordinator
06800 Ankara
Türkiye