Water is an indispensable requirement for every creature on the earth's surface. Water is closely... more Water is an indispensable requirement for every creature on the earth's surface. Water is closely related to the hydrological cycle, one of the processes that occurs during that cycle is evapotranspiration both actually and potentially. However, information in terms of spatial distribution of actual evapotranspiration is very rare, particularly in Indonesia. Landsat-8 satellite data offers opportunity in coping with this need, since the image dataset is available in both reflective and thermal spectral bands. Those bands can be generated to land-cover and temperature information, which are important to surface energy balance computation including evapotranspiration. The purposes of this study were (1) to understand the capability of Landsat 8 for deriving actual evapotranspiration (ETa) parameters estimation, (2) to know its accuracy according to data obtained from meteorological and climatology stations, and (3) to determine the spatial distribution of ETa based on land cover information. The ETa can be extracted from remotely sensed images using Surface Energy Balance System (SEBS) algorithms. ETa estimation made use of SEBS algorithm comprising several parameters, i.e. net radiation (Rn), which is proportional to the amount of soil surface heat flux (G0), sensible heat flux (H) and latent heat flux (λE). ETa is part of the λE which is calculated based on SEBS algorithms. The parameters required for SEBS include albedo, emissivity, land surface temperature, NDVI, vegetation fraction, LAI, surface roughness momentum transfer (Z0m), canopy height, and elevation represented by digital elevation model (DEM). Each of these parameters serves to establish the elements of energy balance of Rn, G0, H, or λE. The land surface temperature was computed on a pixel basis using split-window algorithm. The results showed that all parameters have good accuracies in comparison with the reference data to built SEBS algorithm. ETa accuracy results referring to the data from meteorological dan climatology stations showed standard error of estimates of 0.99 mm/day, 2.18 mm/day, and 2.66 mm /day at 3 different station locations. The highest ETa value was located in the objects of body of water, i.e. at 9.6 mm/day; while the lowest one was located in the objects of zinc roof, i.e. at 5.6 mm/day. This study demonstrated the advantages of spatial data like Landsat-8 satellite images and DEM over meteorological station data, particularly in modelling the spatial distribution of ETa in a relatively small area, which could not be done using data obtained from meteorological stations.
Water is an indispensable requirement for every creature on the earth's surface. Water is closely... more Water is an indispensable requirement for every creature on the earth's surface. Water is closely related to the hydrological cycle, one of the processes that occurs during that cycle is evapotranspiration both actually and potentially. However, information in terms of spatial distribution of actual evapotranspiration is very rare, particularly in Indonesia. Landsat-8 satellite data offers opportunity in coping with this need, since the image dataset is available in both reflective and thermal spectral bands. Those bands can be generated to land-cover and temperature information, which are important to surface energy balance computation including evapotranspiration. The purposes of this study were (1) to understand the capability of Landsat 8 for deriving actual evapotranspiration (ETa) parameters estimation, (2) to know its accuracy according to data obtained from meteorological and climatology stations, and (3) to determine the spatial distribution of ETa based on land cover information. The ETa can be extracted from remotely sensed images using Surface Energy Balance System (SEBS) algorithms. ETa estimation made use of SEBS algorithm comprising several parameters, i.e. net radiation (Rn), which is proportional to the amount of soil surface heat flux (G0), sensible heat flux (H) and latent heat flux (λE). ETa is part of the λE which is calculated based on SEBS algorithms. The parameters required for SEBS include albedo, emissivity, land surface temperature, NDVI, vegetation fraction, LAI, surface roughness momentum transfer (Z0m), canopy height, and elevation represented by digital elevation model (DEM). Each of these parameters serves to establish the elements of energy balance of Rn, G0, H, or λE. The land surface temperature was computed on a pixel basis using split-window algorithm. The results showed that all parameters have good accuracies in comparison with the reference data to built SEBS algorithm. ETa accuracy results referring to the data from meteorological dan climatology stations showed standard error of estimates of 0.99 mm/day, 2.18 mm/day, and 2.66 mm /day at 3 different station locations. The highest ETa value was located in the objects of body of water, i.e. at 9.6 mm/day; while the lowest one was located in the objects of zinc roof, i.e. at 5.6 mm/day. This study demonstrated the advantages of spatial data like Landsat-8 satellite images and DEM over meteorological station data, particularly in modelling the spatial distribution of ETa in a relatively small area, which could not be done using data obtained from meteorological stations.
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