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Estimation of spatially distributed surface energy fluxes using remotely-sensed data for agricultural fields

โœ Scribed by Assefa M. Melesse; Vijay Nangia


Publisher
John Wiley and Sons
Year
2005
Tongue
English
Weight
338 KB
Volume
19
Category
Article
ISSN
0885-6087

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โœฆ Synopsis


Land surface energy fluxes are required in many environmental studies, including hydrology, agronomy and meteorology. Surface energy balance models simulate microscale energy exchange processes between the ground surface and the atmospheric layer near ground level. Spatial variability of energy fluxes limits point measurements to be used for larger areas. Remote sensing provides the basis for spatial mapping of energy fluxes. Remote-sensing-based surface energy flux-mapping was conducted using seven Landsat images from 1997 to 2002 at four contiguous crop fields located in Polk County, northwestern Minnesota. Spatially distributed surface energy fluxes were estimated and mapped at 30 m pixel level from Landsat Thematic Mapper and Enhanced Thematic Mapper images and weather information. Net radiation was determined using the surface energy balance algorithm for land (SEBAL) procedure. Applying the two-source energy balance (TSEB) model, the surface temperature and the latent and sensible heat fluxes were partitioned into vegetation and soil components and estimated at the pixel level. Yield data for wheat and soybean from 1997 to 2002 were mapped and compared with latent heat (evapotranspiration) for four of the fields at pixel level. The spatial distribution and the relation of latent heat flux and Bowen ratio (ratio of sensible heat to latent heat) to crop yield were studied. The root-mean-square error and the mean absolute percentage of error between the observed and predicted energy fluxes were between 7 and 22 W m 2 and 12 and 24% respectively. Results show that latent heat flux and Bowen ratio were correlated (positive and negative) to the yield data. Wheat and soybean yields were predicted using latent heat flux with mean R 2 D 0ร67 and 0ร70 respectively, average residual means of 4ร2 bushels/acre and 0ร11 bushels/acre respectively, and average residual standard deviations of 16ร2 bushels/acre and 16ร6 bushels/acre respectively (1 bushel/acre ยณ 0ร087 m 3 ha 1 ). The flux estimation procedure from the SEBAL-TSEB model was useful and applicable to agricultural fields.


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