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Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data / P. Nagler in Remote sensing of environment, vol 94 n° 1 (15/01/2005)  

Public [article]  inRemote sensing of environment > vol 94 n° 1 (15/01/2005) . - pp 17 - 30 Titre : Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data Type de document : Article/Communication Auteurs : P. Nagler, Auteur ; J. Cleverly, Auteur Année de publication : 2005 Article en page(s) : pp 17 - 30 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] covariance [Termes IGN] données météorologiques [Termes IGN] évapotranspiration [Termes IGN] image Terra-MODIS [Termes IGN] indice de végétation [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Nouveau-Mexique (Etats-Unis) [Termes IGN] régression [Termes IGN] température de surface Résumé : (Auteur) A vegetation index (V1) model for predicting evapotranspiration (ET) from data from the Moderate Resolution Imaging Spectrometer on the EOS-1 Terra satellite and ground meteorological data was developed for riparian vegetation along the Middle Rio Grande River in New Mexico. Ground ET measurements obtained from eddy covariance towers at four riparian sites were correlated with MODIS Vis, MODIS land surface temperatures (LSTs), and ground micrometeorological data over four years. Sites included two saltcedar (Tamarix ramossissima) and two Rio Grande cottonwood (Populus deltoides ssp. Wislizennii) dominated stands. The Enhanced Vegetation Index (EVI) was more closely correlated (r =0.76) with ET than the Normalized Difference Vegetation Index (NDVI; r =0.68) for ET data combined over and species. Air temperature (Ta)measured over the canopy from towers was the meteorological variable that was most closely correlated with ET (r =0.82). MODIS LST data at 1- and 5-km resolutions were too coarse to accurately measure the radiant surface temperature within the narrow riparian corridor; hence, energy balance methods for estimating ET using MODIS LSTs were not successful. On the other hand, a multivariate regression equation for predicting ET from EVI and Ta had an r 2=0. 82 across sites, species, and years. The equation was similar to VI-ET models developed for crop species. The finding that ET predictions did not require species-specific equations is significant, inasmuch as these are mixed vegetation zones that cannot be easily mapped at the species level. Numéro de notice : A2005-017 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.08.009 En ligne : https://doi.org/10.1016/j.rse.2004.08.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27156 [article]