Remote sensing estimates of the surface energy balance, and daily evapotranspiration (LEd) in particular, have become essential in recent studies on climatology,meteorology and hydrology. High spatial resolution satellites such as Landsat or ASTER provide surface information at pixel resolutions on the order or below100 m, but the low frequency of repeated coverage limits the utility of these sensors in the routine monitoring of LEd. Daily coverage is provided by regional to global sensors such as MODIS (1000 m) or METEOSAT (5000 m). However, most of the surface variability is lost at these coarse spatial resolutions. Recent studies have explored the possibility to estimate subpixel energy fluxes, at the spatial resolution of the sensor visible bands, to recover the mentioned surface variability. In this work, it has been firstly evaluated the loss of information in surface temperature variability with the degradation of the spatial resolution of a satellite image. Secondly, a disaggregation procedure to estimate subpixel surface temperatures has been applied at different spatial resolutions. Finally, a Simplified Two-Source Energy Balance (STSEB) model has been used to evaluate the effect of the disaggregation technique on the surface fluxes retrieval. Three satellite images of the Basilicata southern Italian region, Landsat7-ETM+, Landsat5-TM and MODIS Terra have been used. Three different targets were selected within each image in order to analyze the effect of the field size on the obtained results.

Effect of the satellite spatial resolution on the surface energy fluxes retrieval. Application to the Basilicata Italian Region

COPERTINO, Vitantonio;TELESCA, Vito;
2007

Abstract

Remote sensing estimates of the surface energy balance, and daily evapotranspiration (LEd) in particular, have become essential in recent studies on climatology,meteorology and hydrology. High spatial resolution satellites such as Landsat or ASTER provide surface information at pixel resolutions on the order or below100 m, but the low frequency of repeated coverage limits the utility of these sensors in the routine monitoring of LEd. Daily coverage is provided by regional to global sensors such as MODIS (1000 m) or METEOSAT (5000 m). However, most of the surface variability is lost at these coarse spatial resolutions. Recent studies have explored the possibility to estimate subpixel energy fluxes, at the spatial resolution of the sensor visible bands, to recover the mentioned surface variability. In this work, it has been firstly evaluated the loss of information in surface temperature variability with the degradation of the spatial resolution of a satellite image. Secondly, a disaggregation procedure to estimate subpixel surface temperatures has been applied at different spatial resolutions. Finally, a Simplified Two-Source Energy Balance (STSEB) model has been used to evaluate the effect of the disaggregation technique on the surface fluxes retrieval. Three satellite images of the Basilicata southern Italian region, Landsat7-ETM+, Landsat5-TM and MODIS Terra have been used. Three different targets were selected within each image in order to analyze the effect of the field size on the obtained results.
9789059660618
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/17005
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