## 4 Discussion  
Analysing the Impact of ENSO on Temperature Distribution Using Remote Sensing Techniques in the City of Kuching (Landsat Satellite and MODIS)  
The temperature distribution map during El Nino and La Nina events in Kuching City, Sarawak is depicted in Figures 7 and 8. El Nino is characterized by higher surface temperatures, represented by yellow shades, while La Nina exhibits lower temperatures, represented by blue shades. The heat concentration zones are divided into urban and industrial areas. During El Nino events, there are hotter zones compared to those of La Nina events. For example, almost all zones (B, C, D, E, F, G, H, I, and J) have temperatures exceeding 30 \({}^{\circ}\)C during El Nino, causing discomfort to residents. Figure 9 highlights the specific heat concentration zones during El Nino, which are more extensive than during La Nina. This increase in concentrated hot areas exceeding 30 \({}^{\circ}\)C occurs during both El Nino and La Nina events. To analyze the impact of ENSO events on the temperature distribution in Kuching City, statistical values derived from Landsat satellite remote sensing (RS) data are used. Table 5 provides detailed information on these statistical values during La Nina and El Nino events in the city. The statistical values are based on cloud-free Landsat satellite RS data when the Oceanic Nino Index (ONI) exceeds \(-1\) for La Nina and +1 for El Nino events in Kuching City, Sarawak. Table 6 confirms that the average, maximum, and minimum temperatures are higher during El Nino than during La Nina events. For instance, an ONI of 1.1 in April 1998 (El Nino) corresponds to an average temperature of 27.81 \({}^{\circ}\)C, whereas an ONI of \(-1.1\) in November 2011 (La Nina) corresponds to an average temperature of 24.91 \({}^{\circ}\)C. This demonstrates the impact of El Nino on the temperature in the study area when compared with climatology data from the Meteorological Department (MMD). Similarly, El Nino events exhibit higher maximum and minimum values compared to La Nina events. The temperature distribution patterns during El Nino and La Nina events in Kuching City, Sarawak are captured in Figures 7 and 8. The analysis of statistical values derived from Landsat satellite RS data reveals higher average, maximum, and minimum temperatures during El Nino compared to those during La Nina. This increase in temperature during El Nino events has a direct impact on the land surface, leading to the occurrence of hotspots where the temperature exceeds 30 degrees Celsius. These extreme land surface temperatures of more than 30 degrees Celsius are more prevalent during El Nino events compared to La Nina events, as demonstrated in Figures 7 and 8. Our study found that there were more core hotter areas during El Nino events, indicating higher temperatures in the study area compared to those of La Nina events. This observation further supports the finding that the rise in temperature during El Nino events directly influences the land surface temperature in the study area. Overall, our research indicates that the temperature distribution in Kuching City, Sarawak is influenced by ENSO events, with El Nino events leading to higher temperatures compared to La Nina events. The analysis of satellite RS data provides valuable insights into these temperature variations, which can help in understanding and monitoring the impact of ENSO events on the study area. The distribution of surface temperatures exceeding 30 \({}^{\circ}\)C (heat concentration) during the La Nina and El Nino events is shown in Figure 9. Based on our observations, it is clear that the extent of concentrated hot areas during El Nino events is higher compared to that of La Nina events. Figure 9 provides a more detailed explanation of the differences in the extent of concentrated hot areas during the La Nina and El Nino events. The left side of Figure 9 displays the temperature distribution during El Nino events, characterized by ONI values ranging from 2.2 to 2.6.