## 4 Discussion
### Validation of LST MODIS and Landsat with MMD
This explains why the correlation coefficient between the surface temperature from the MODIS or Landsat satellites and the temperature data from the MMD exceeds 0.80. The correlation relationship between meteorological data (temperature) and the ONI (Oceanic Nino Index) as an indicator for assessing the effectiveness of RS (remote sensing) techniques and data in studying the impact of ENSO events on the temperature in Kuching, Sarawak is shown in Figure 13. We found a direct and positive correlation pattern between the surface temperature from the MODIS and Landsat satellites and the ONI. The correlation coefficients were 0.71 for the Landsat satellite and 0.73 for the MODIS satellite (Figure 4). The findings of this study align with the research conducted by [PERSON] et al. [46], who also utilized MODIS data to measure temperatures in Africa and assessed their effectiveness in desert areas. [PERSON] et al. [46] reported a 90% accuracy rate for MODIS data in measuring temperatures in Africa, based on a correlation analysis with meteorological data. The correlation coefficient between the MODIS RS data and the temperature data from the MMD was 0.90, which is consistent with the findings of this study. This confirms that MODIS data are suitable for measuring surface temperature in desert and tropical regions. Both the Landsat and MODIS RS datasets have high correlation coefficients of 0.97 and 0.90, respectively, indicating their potential for studying land surface temperature characteristics in specific locations [13; 14; 15; 46; 47]. The quality of MODIS data undergoes rigorous processing and validation by experts, ensuring an accuracy rate of nearly 90% compared to that of the MMD's temperature data. RS technology bridges data gaps in areas without weather stations, especially remote and inaccessible regions, allowing us to access weather and climate information related to global climate change. The findings of [PERSON] et al. [48] also support the conclusions of [PERSON] et al. [46], as they conducted a global-scale study with similar results. The direct correlation between the ONI and air temperature over three months is shown in Figure 13, based on the ONI formula. The analysis includes 385 monthly average temperature data points from the MMD and ONI values from 1988 to 2019, organized in the format of three-month averages. The results reveal a strong positive correlation (R\({}^{2}\) = 0.75) between the ONI and temperature from the MMD, indicating the impact of ENSO events  
Figure 12: Temperature differences between LST (land surface temperature) MODIS satellite data and MMD (Malaysian Meteorological Department) data. on air temperature. El Nino events, associated with increased temperatures, lead to drought and aridity, resulting in higher temperatures in Kuching, Sarawak. On the other hand, La Nina events, characterized by increased rainfall, lead to a decrease in temperature. Table 5 demonstrates a positive correlation between the ONI and the temperature from MODIS and Landsat satellites, although with slightly lower correlation coefficients (0.68 for MODIS and 0.71 for Landsat) compared to that of the MMD (0.75). Nonetheless, RS data remains effective in studying the relationship between the ONI and temperature, with correlation coefficients exceeding 50% (68% for MODIS and 71% for Landsat). Changes in the ONI (Oceanic Nino Index) values are reflected in the temperature changes observed by the MODIS and Landsat satellites. When the ONI exceeds 0.5, indicating El Nino events, it corresponds to increased temperatures. On the other hand, La Nina events lead to decreased temperatures due to increased rainfall. These findings align with previous studies, such as those by [PERSON] [49] and [PERSON] and [PERSON] [4; 5], which reported similar effects of rainfall on temperature. El Nino events cause drought and below-average rainfall, resulting in temperature increases. Conversely, the increased rainfall during La Nina events contributes to a temperature reduction.