Latent heat flux estimation using trapezoidal relationship between MODIS land surface temperature and fraction of vegetation-application and validation in a humid tropical region

dc.contributor.authorLaxmi, K.
dc.contributor.authorNandagiri, Lakshman
dc.date.accessioned2020-03-31T08:35:46Z
dc.date.available2020-03-31T08:35:46Z
dc.date.issued2014
dc.description.abstractThe present study was taken up with the objective of developing a methodology for estimation of actual evapotranspiration (AET) using only satellite data. Accordingly, an algorithm based on the popular Priestley-Taylor method was developed. While previous studies have assumed a triangular relationship between land surface temperature (LST) and fraction of vegetation (FV) to calculate the Priestley-Taylor parameter (?), a trapezoidal relationship was adopted in the present study to enable applications in forested regions in the humid tropics. The developed algorithm was applied to the humid tropical Mae Klong region, Thailand, and latent heat flux (ET) estimates were validated with measurements made at a flux tower located at the centre of the region. Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing satellite data products corresponding to the study area were used to derive various inputs required by the algorithm. Comparison of estimated and measured fluxes on five cloud-free days in 2003 yielded root mean square error (RMSE) of 64.73 W m-2 which reduced to 18.65 W m-2 when one day was treated as an outlier. The methodology developed in this study derived inputs only from satellite imagery and provided reasonably accurate estimates of latent heat flux at a humid tropical location. 2014 Taylor & Francis.en_US
dc.identifier.citationRemote Sensing Letters, 2014, Vol.5, 11, pp.981-990en_US
dc.identifier.urihttps://idr.nitk.ac.in/jspui/handle/123456789/11871
dc.titleLatent heat flux estimation using trapezoidal relationship between MODIS land surface temperature and fraction of vegetation-application and validation in a humid tropical regionen_US
dc.typeArticleen_US

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