## 4 Discussion
### Validation of LST MODIS and Landsat with MMD  
Figure 4 displays the difference in correlation coefficients between meteorological temperature data and surface temperature obtained from the MODIS and Landsat satellites. The graph indicates a higher correlation value for the Landsat satellite (0.97) compared to that of the MODIS satellite (0.90). This difference can be attributed to the higher resolution of the Landsat (30 m) satellite compared to that of the MODIS (5600 m) satellite. These findings suggest that the data of both the Landsat and MODIS satellites accurately represent the surface temperature for studying the effects of ENSO on the temperature in Kuching City using remote sensing techniques. The accuracy of RS data and techniques in assessing the impact of ENSO events on temperature is 97% for Landsat and 90% for MODIS. Referring to Figure 3 there are differences in daily temperatures between the MMD data and the daily temperatures derived from the Landsat satellite. This study found the largest difference in December 1995, with a negative (\(-\)) 1.7 \({}^{\circ}\)C difference. The second-largest difference occurred in August 2004, with a negative (\(-\)) 1.4 \({}^{\circ}\)C difference, followed by negative (\(-\)) 1.3 \({}^{\circ}\)C in February 2011 as well as negative (\(-\)) 1.2 \({}^{\circ}\)C in September 2005 and October 2005. These differences arise because RS sensors, such as Landsat and MODIS, measure surface temperature, while meteorological stations measure air temperature [43]. Overall, the Landsat RS data shows differences of lower than positive (\(+\)) 0.5 \({}^{\circ}\)C or negative (\(-\)) 0.5 \({}^{\circ}\)C. This indicates that 97% of the data have small differences below 0.5 \({}^{\circ}\)C. There is a positive relationship with a correlation coefficient of 0.97 between the Landsat RS data and temperature data from the MMD. This indicates that the majority of daily data from the MMD and the Landsat satellite have differences below positive (\(+\)) 0.5 \({}^{\circ}\)C or negative (\(-\)) 0.5 \({}^{\circ}\)C.  
Regarding the differences between the monthly average temperatures from the MMD and the monthly average temperatures from MODIS (shown in Figure 12), the largest difference between the two datasets is observed in April 2008, with a positive (\(+\)) 1.2 \({}^{\circ}\)C difference. This is followed by a negative (\(-\)) 0.9 \({}^{\circ}\)C difference in January 2003, a positive (\(+\)) 0.9 \({}^{\circ}\)C difference in May 2006, and the third-largest difference of negative (\(-\)) 0.7 \({}^{\circ}\)C in July 2000. These differences arise because satellite RS, such as that by Landsat and MODIS, measures the surface temperature, whereas meteorological stations measure the air temperature [44]. This study found that nearly all of the 216 data points have differences below positive (\(+\)) 0.5 \({}^{\circ}\)C and negative (\(-\)) 0.5 \({}^{\circ}\)C. This means that 91% of MODIS data have differences of less than 0.5 \({}^{\circ}\)C compared to the MMD temperature data. This explains the positive correlation between the monthly temperatures from the MODIS satellite and the MMD, with a correlation coefficient (R) of 0.90. The findings of this study are consistent with the study conducted by [PERSON] [44], which examined the effect of global warming on global temperature patterns using 273 MODIS images and meteorological data. [PERSON] [44] reported that global warming leads to an increase in global temperatures. In order to evaluate the accuracy and validity of the data, [PERSON] [44] compared MODIS data with meteorological data and found an 84% accuracy rate for MODIS data in measuring the temperature, with a correlation coefficient of 0.84 (R\({}^{2}\)) between the MODIS satellite surface temperature data and the temperature data from the meteorological department. This result is similar to the 90% correlation reported by [PERSON] et al. [6] and the 85% correlation reported by [PERSON] et al. [45], both of whom also used MODIS or Landsat data.