Determination of instantaneous and daily net radiation from TM – Landsat 5 data in a subtropical watershed

The use of remote sensing for reliable estimation of net radiation and its components: a case study for contrasting land covers in an agricultural hotspot of the Brazilian semiarid region

“…Therefore, the local and regional atmospheric circulation in the Caatinga has being affected (Correia et al, 2006;Melo et al, 2015). These alterations in biophysical surface variables impact the surface net radiation balance, as observed by Silva et al (2015) who studied the replacement of woody savanna by agricultural crops and eucalyptus plantation, and by Liu et al (2019) who investigated the radiative effects of the conversion of croplands to grasslands.…”

“…Important variables for the upwelling radiation fluxes are albedo (shortwave radiation), and land surface temperature and surface emissivity, that together determine the longwave upwelling radiation, again calculated by Stefan Boltzmann's law. All of these atmospheric and surface variables display considerable spatial and temporal variability, which directly affect heat and mass exchanges in the planetary boundary layer (Silva et al, 2015;Kilic et al, 2016).…”

“…Estimation of R n is very important in the context of turbulent energy flux estimates (latent heat flux (i.e., evapotranspiration), and sensible heat flux), particularly in those studies devoted to the assessment of evapotranspiration based on remote sensing techniques (Bastiaanssen et al, 1998(Bastiaanssen et al, , 2005Allen et al, 2007;Silva et al, 2015;Elnmer et al, 2019) and those employing the Bowen ratio method, where R n (as a key component of the available energy) is crucial for the reliable calculation of latent and sensible heat fluxes (Verhoef and Campbell, 2005). Reliable values of R n are also required to check the closure of the energy balance when turbulent energy fluxes have been directly determined with the eddy covariance technique, because there may be an underestimation due to the existence of storage of heat in canopies or in the layer below the instrumentation, horizontal advection, errors in the frequency response of sensors, and regional scale heterogeneity that can cause large-scale eddies that are not readily sensed by eddy covariance systems.…”

A Framework for Estimating the 30 m Thermal‐Infrared Broadband Emissivity From Landsat Surface Reflectance Data

“…The Landsat satellites provide the longest temporal record (over 40 years) of land surface observations, which is the primary sensor to assess energy balances at relatively high‐spatial resolutions (30–120 m) (Gao, Anderson, et al, ; Silva et al, ; Wulder et al, ). Numerous studies have retrieved the key variables or components of surface radiation budgets (SRBs) from Landsat data, including the albedo (Shuai et al, ), shortwave net radiation (Wang et al, ) and land surface temperature (Sobrino, Jimenez‐Munoz, & Paolini, ).…”

“…Regarding BBE, only a few studies are conducted to obtain high‐spatial‐resolution BBE from Landsat data. For example, Silva et al () adopted the formula of Tasumi () to represent the land surface spectral emissivity and BBE, which was described as a linear function of the leaf area index (LAI) when 0 < LAI ≤ 3; the land surface spectral emissivity and BBE are set as constant when LAI ≥ 3. Mira et al () used a relationship between the normalized difference vegetation index (NDVI) and a spectral database of soil and plant canopy properties to calculate the land surface spectral emissivity (10.4–1.5 μm) and BBE (8–13.5 μm).…”