Application of satellite-based methods for estimating evapotranspiration in Thessalia plain, Greece

Tsouni, A; Koutsoyiannis, D; Contoes, C; Mamassis, N; Elias, P

dc.contributor.author	Tsouni, A	en
dc.contributor.author	Koutsoyiannis, D	en
dc.contributor.author	Contoes, C	en
dc.contributor.author	Mamassis, N	en
dc.contributor.author	Elias, P	en
dc.date.accessioned	2014-03-01T02:54:16Z
dc.date.available	2014-03-01T02:54:16Z
dc.date.issued	2003	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36785
dc.title	Application of satellite-based methods for estimating evapotranspiration in Thessalia plain, Greece	en
heal.type	conferenceItem	en
heal.publicationDate	2003	en
heal.abstract	Estimation of evapotranspiration using both meteorological ground-based measurements and satellite-derived information has been widely studied during the last few decades and various methods have been developed for this purpose. In our application, we estimated the regional daily actual evapotranspiration during the 2001 summer season (June-August) over Thessalia plain in Pinios river basin. It is an area of intensive agricultural activity. Satellite data were accounted for those days that were available. For this case study, two different methods were applied and compared to the conventional and well-known FAO Penman-Monteith method. Satellite data, adequately processed (radiometric calibration, sun illumination conditions correction and geometric correction), were used in conjunction with ground data from the three nearest meteorological stations. The methods, which were properly adapted, exploit surface temperature and surface albedo assessments, obtained respectively from the infrared channels 4-5 and the visible channels 1-2 of NOAA-AVHRR images. The first method requires daily mean surface temperatures, so NOAA-15 satellite images were used, while for the second one the average rate of surface temperature rise during the morning is required, so a combination of NOAA-14 and NOAA-15 satellite images was used. The results of the study are quite encouraging, especially for the first method. In the future we intend to combine the satellite-derived data (Tsurf, Albedo, NDVI) with detailed land-use and land-cover classification map based on high-resolution satellite data.	en