*3.5. Validation of the Land-Use Driven Model*

We test the derived regression model (Equation (4)) for its predicted LSTs on another hottest day (1 June 2016) by using the statistical dataset of 2016. Figure 10 shows the land-use composition—driven predictions of LST for the hottest day of 2016 (1 June) versus the LST observed by Landsat-8 for (a) 510 × 510 m and (b) 330 × 330 m window sizes. High correlations of 0.897 and 0.869 for 510 × 510 m and 330 × 330 m window sizes, respectively, were obtained. RMSEs for the window sizes 510 × 510 m and 330 × 330 m were 1.71 ◦C and 1.94 ◦C, respectively. The ratios RMSE/STD\_LSTLS8 are also

low (below 0.5), at 0.44 and 0.5 for the window sizes 510 × 510 m and 330 × 330 m, respectively. They indicate that the regression model reasonably predicts the LST for the hottest day of 2016. That is, the developed model can be used to retrieve LST for the needs of land-use management and planning with high reliability.

**Figure 10.** Land-use composition-driven predictions of LST for the hottest day of 2016 (1 June) versus LST observed by Landsat-8 for (**a**) 510 × 510 m and (**b**) 330 × 330 m window sizes.
