Exploring the Impact of El Niño–Southern Oscillation (ENSO) on Temperature Distribution Using Remote Sensing: A Case Study in Kuching City

Malaysia’s location in Southeast Asia exposes it to various weather patterns influenced by El Niño–Southern Oscillation (ENSO), monsoons, the Madden–Julian (MJO), and Indian Ocean Dipole (IOD). To overcome limitations of previous studies due insufficient spatial information, this study utilizes remote sensing (RS) data from Landsat MODIS satellites, along with Oceanic Niño Index (ONI), analyze distribution temperature affected (ENSO). This employs radiometric atmospheric corrections on data, converting them surface data. Our analysis reveals a correlation coefficient 0.73 (MODIS) 0.71 (Landsat) between ONI RS During events, recorded increases 0–1.6 °C, while showed 2.2–2.8 °C. The information obtained assists identifying areas facilitating implementation mitigation measures government. By utilizing research enhances our understanding ENSO–temperature relationship, surpassing providing valuable insights into climate dynamics.