## 2 Materials and Methods
By analyzing the temperature anomalies in this region, scientists can track the occurrence and magnitude of El Nino and La Nina events, enhancing our understanding of their impact on global weather patterns. The ONI data were obtained from the Climate Prediction Center [21]. In addition to RS data, daily air temperature data from the Kuching Airport station were collected. The temperature measurements were recorded at latitude 01\({}^{\circ}\)29\({}^{\prime}\) north and longitude 110\({}^{\circ}\)20\({}^{\prime}\) east. The data, provided in \({}^{\circ}\)C, included minimum, maximum, and average monthly temperature values calculated from daily measurements. The meteorological data from the Malaysia Meteorology Department (MMD) covered the period from 1988 to 2019. These data served as a reference to evaluate the accuracy and effectiveness of RS data in studying the impact of ENSO on the temperature in Kuching City, Sarawak. The RS data required preprocessing, including geometric, radiometric, and atmospheric corrections, before converting the digital numbers to land surface temperature, as mentioned in Figure 2. The conversion process follows the method applied by [PERSON] and [PERSON] [22]. Temporal or long-term geometric correction is important for accurately and effectively studying changes in remote sensing data analysis. This study utilizes a polynomial method to obtain low- and simple-resolution satellite image geometry. The relationship between image coordinates (X\({}^{\prime}\), Y\({}^{\prime}\)) and cartography (X, Y) is defined by the following:  
\[X^{\prime}=\mathrm{P}_{1}^{\mathrm{N}}(X,Y)Y^{\prime}=\mathrm{P}_{2}^{\mathrm{ N}}(X,Y)X^{\prime}\]  
The polynomial \(\mathrm{P}_{1}^{\mathrm{N}}\) (where N is the order) is represented by the following:  
\[\mathrm{P}_{1}^{\mathrm{N}}(X,Y)=\sum_{j=0}^{\mathrm{m}_{1}}\sum_{k=0}^{ \mathrm{m}_{2}}\mathrm{a}_{jk}X^{\prime}X^{k}\]  
with \(0\leq\mathrm{m}_{i}\leq\mathrm{n}_{i}\leq\mathrm{n}\), \(\mathrm{m}_{1}+\mathrm{m}_{2}\leq\mathrm{n}\). \begin{table}
\begin{tabular}{c c c} \hline \hline
**ONI Intensity Scale** & **El Niño Class** & **La Nina Class** \\ \hline Very Weak & 0.5 to 0.9 & \(-\)0.5 to \(-\)0.9 \\ Moderate & 1 to 1.4 & \(-\)1 to \(-\)1.4 \\ Strong & 1.5 to 1.9 & \(-\)1.5 to \(-\)1.9 \\ Very Strong & 2 and above & \(-\)2 and below \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Scale of intensity levels based on ONI. To determine the accuracy of polynomial geometric correction in Equation (1), ground control points (GCPs) for surface temperature within the image (X\({}^{\prime}\), Y\({}^{\prime}\)) need to be selected accurately on the map (X, Y). The minimum number of GCPs depends on the polynomial order through the equation (n + 1) \(\times\) (n + 2)/2, where n represents the polynomial degree. A large number of GCPs are used to achieve optimal conversion with the smallest overall positional error at the selected points [23]. Atmospheric correction for thermal channels aims to reduce and remove the atmospheric effects from thermal infrared data. The in-scene atmospheric correction (ISAC) algorithm, as proposed by [PERSON] et al. [24], is used in this study. ISAC utilizes radiance data at the aperture to estimate the atmospheric radiance and transmission according to Equation (3), employing Equation (1) for the total radiance at the aperture and assuming objects with the highest radiance are either black or blackbody emissive. \[\text{Lob}=\tau\text{B(T)}+\text{Lu}\]  
where Lob is the observed radiance at the aperture, \(\tau\) represents atmospheric transmission, B(T) denotes the Planck function, and Lu represents the radiance due to the atmosphere. ISAC estimates the surface radiance from the brightness temperature of each pixel. For each spectral channel, a scatter plot is constructed based on the Planck formula. A straight line is fitted to the upper part of the scatter plot, where pixels approach an emissivity value of 1.0. Subsequently, the estimation of transmission (slope) and upwelling (intercept) is performed.