## 5 Results and Validation  
### Validation with Ground Component Temperature Measurements  
In this study, ground component temperature measurements were used to validate the instantaneous soil and vegetation component temperatures from the ASTER images. Using a high-resolution thermal camera over heterogeneous surfaces can allow the acquisition of the soil and vegetation component temperatures including sunlit and shaded soil and vegetation temperatures over land surface areas exceeding 500 m\({}^{2}\). However, because the soil and vegetation temperatures were manually observed on the ground, their measured times cannot exactly match satellite overpass times. The surface soil and vegetation temperatures at the specific times of satellite overpass were interpolated from the ground observed data and the diurnal temperature cycle (DTC) model [47, 48]. The simulated temperatures agreed well with the observed temperatures at specific manual measurement times (Figure 6), indicating that the simulated temperatures can be applied to validate the separated soil and vegetation component temperatures when the timely ground observed data are absent. The performance of the proposed _T_-\(\alpha\) space approach was validated with the interpolated ground-based soil and vegetation temperatures. Figure 6 shows the comparisons among the separated component temperatures, the ground measurements from the thermal cameras and the simulated data from multiple daytime ground measurements. There is a good agreement in the component temperatures derived from the ASTER images using the _T_-\(\alpha\) space approach when compared with the measured soil and vegetation component temperatures, with the exception of the significant underestimation of the vegetation temperature on DOY 224 and 231. The errors in vegetation temperature on these days are due to the underestimation of land surface temperatures from the ASTER TIR data by more than \(-1.7\) K, compared to the measured land surface temperatures calculated from the four-component radiometers and meteorological observations and computed composite emissivity. Further error analysis shows that the bias for the soil temperature ranges from \(-1.68\) to \(0.67\) K, with an average of \(-0.27\) K and an RMSE value of \(0.83\) K, and the bias of the vegetation temperatures range from \(-3.46\) to \(0.95\) K, with an average of \(-1.29\) K and an RMSE of \(1.64\) K, compared with the measured/interpolated component temperatures from the thermal camera. These errors are tolerable and comparable for soil and vegetation component temperatures separated using the _T_-\(\alpha\) space method from the ASTER images, even though the soil and vegetation component temperatures are both underestimated. Figure 6: The interpolation of daytime surface soil temperatures (**a**) and vegetation temperatures (**b**) validated with the observed temperatures. For this study area it appears that the component temperatures from the ground-based thermal camera are in good agreement with soil and canopy temperatures derived from the _T_-\(\alpha\) space using ASTER images having 90 m pixel resolution. Underestimated land surface temperature from the satellite will lead to underestimates of the component temperatures, so it is important to have accurate land surface temperatures compared to the ground measurements associated with the underestimations of both separated soil and vegetation temperatures [35]. Finally, the accuracy in deriving soil temperature is higher than vegetation temperature. Relatively large errors were found for vegetation temperature estimates, especially on DOY 224 and 231 (Figure 6b), which were caused by an underestimate in land surface temperature from the satellite. Increased errors in estimating vegetation temperatures may be due in part to errors in estimated fraction of vegetation cover, which is most significant during the growing period when canopy cover is less than 75%.