## 1 Introduction  
Malaysia's location in Southeast Asia exposes it to climate influences, such as the El Nino-Southern Oscillation (ENSO), the Madden-Julian Oscillation (MJO), the Indian Ocean Dipole (IOD), and monsoons [1]. El Nino events lead to warmer weather and prolonged droughts in Southeast Asian countries [2], resulting in extreme temperatures [3, 4] and health risks. El Nino has had a significant impact on Malaysia, particularly in Sabah and Sarawak, causing hot and dry weather [2, 5]. Historical records from the Malaysia Meteorology Department indicate that a severe El Nino occurred approximately 17 years ago, resulting in haze, drought, and extreme heat. On 9 April 1998, the temperature in Chuping, Perlis rose above 40.1 \({}^{\circ}\)C [2]. Globally, the El Nino events in 1997-1998 led to damages in 15 countries, with estimated losses of up to USD 13 billion, and claimed 2000 lives [6]. Droughts and dry weather caused by El Nino pose a threat to vulnerable groups, particularly in urban hotspots [2]. Previous studies have primarily focused on sea surface temperatures [6], neglecting the effects of El Nino on land temperature and urban climate. However, understanding these impacts is crucial, especially considering the higher degree of warming and the urban heat island effect in urban areas [5]. The scarcity of studies on temperature distribution during ENSO events highlights the need for spatial information to understand their impacts. Remote sensing methods can provide valuable data for mapping affected areas and aiding disaster management efforts. The objective of this study is to explore and understand the impact of El Nino-Southern Oscillation (ENSO) on the temperature distribution in Kuching City, utilizing remote sensing techniques. The occurrence of El Nino events poses a significant threat to human life, resulting in extreme temperatures and health risks [6; 7]. In tropical and subtropical climates, research using remote sensing to comprehend the long-term effects of El Nino on urban temperature remains limited. Spatial information on affected areas during ENSO events is vital for identifying high-risk locations and implementing measures to reduce their impact. The scarcity of meteorological stations in certain areas [8; 9], such as Kuching City, Sarawak, necessitates the use of remote sensing technology to provide temperature information in areas without station coverage. Placing temperature gauges on vehicles can aid in mapping temperature distributions, but this method is time consuming, expensive, and limited to areas accessible by roads [10; 11; 12]. Remote sensing and GIS technologies offer a more efficient and comprehensive approach. Remote sensing technology and geographic information systems (GISs) are widely used to study land use changes and their effect on urban temperature [6]. Previous studies have demonstrated the effectiveness of these technologies in mapping urban growth and its contribution to the urban heat island effect, resulting in higher temperature increases in urban areas compared to those in rural regions [6; 12]. There have been efforts to examine the influence of the formation of urban heat islands during ENSO [6]. Additionally, [PERSON] and [PERSON] [13] examined the variability of land surface temperatures for different land cover types during ENSO events, but they only used the Landsat sensor. In a study of the Amazon, [PERSON] et al. [14] observed a temperature difference of 7.5-8 \({}^{\circ}\)C between El Nino and La Nina events using MODIS data. The impact of ENSO events on temperature, as identified by [PERSON] et al. [14], varies depending on factors such as topography, with lowland areas exhibiting higher temperatures compared to areas near the Andes Mountains. Similarly, [PERSON] and [PERSON] [15] utilized MODIS data to examine the effect of El Nino on global temperature and vegetation systems. They found that El Nino resulted in temperature increases ranging from 0.5 to 2.5 \({}^{\circ}\)C, with variations depending on the specific location.