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Poster De Conférence Année : 2018

Monitoring evapotranspiration with remote sensing data and ground data using ensemble model averaging

Gilles Boulet
Emilie Delogu
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  • PersonId : 1093992
Jérôme Demarty

Résumé

Evapotranspiration (ET) can be mapped using thermal infrared and spectral reflectance data. Various ET models have been developed but there was no competitive evaluation of them over a large range of situations. Ensemble model averaging is a tool that can be used for deriving ET from multi-model simulations. In this study, we used bayesian model averaging, which consists in weighting each model according to their performances when deriving the ensemble average. It was applied to the monitoring of ET over a saltmarsh scrub area in South France from MODIS data. ET monitoring was improved (RMSE = 0.57 mm d(-1)) when using a weighted averaging procedure as compared to the performances of a simple average or to the performances of each individual model.

Domaines

Météorologie
Fichier non déposé

Dates et versions

hal-02738340 , version 1 (02-06-2020)

Identifiants

Citer

Albert Olioso, Aubin Allies, Gilles Boulet, Emilie Delogu, Jérôme Demarty, et al.. Monitoring evapotranspiration with remote sensing data and ground data using ensemble model averaging. 38. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2018, Valencia, Spain. IEEE, IEEE International Geoscience and Remote Sensing Symposium Proceedings, pp.7656 - 7659, 2018, ⟨10.1109/IGARSS.2018.8517532⟩. ⟨hal-02738340⟩
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