## 4 Discussion  
In this paper, we present a new methodology to assess frost damage using RS technology. To analyze this phenomenon, we used LST data collected by the MSG satellite over the past 20 years, focusing on the months most prone to frost: January, February,  
Figure 19: Global damage intensity map for the Valencian Community during the period 2004–2023. Figure 20: Linear correlation graph between the overall frost damage intensity registered over the study period (2004–2023) in the Valencian Community and altitude. March, April, November, and December. To ensure that the LST recorded by the satellite accurately represented the actual temperature of the area, we conducted a correlation analysis between the satellite data and in situ measurements provided by AEMET for the Villafranca station. The results show a high level of reliability, with strong R\({}^{2}\) values and low RMSE, particularly during nighttime hours. This result is significant because, outside of these hours, the temperature is generally too high for frost to occur or cause damage to the crops. Therefore, the fact that the validation demonstrates the reliability of our data, especially during the night, ensures a strong analytical capability [43]. This result confirms the high reliability of our methodology, which was then used to study frost events in the Villafranca area. From this study, we can observe that although frosts are relatively frequent in this region, it is rare for them to cause severe or lasting damage. Additionally, the temporal analysis reveals how the distribution and intensity of frost events have changed over the past decades, with a notable decrease in frost risk during March, November, and December. We then extended our analysis to the entire region, examining the entire LST time series. The data shows that certain years were particularly cold (2005 and 2010), while others were notably warm (2014, 2019, 2023). We also observe that warm years have recently become more frequent than cold ones, with an increasing trend, as also highlighted by the temperature study conducted by the Agencia Estatal de Meteorologia (AEMET) for the Valencian Community. According to this study, the years identified by us as warm are classified as very warm (2014), warm (2019), and extremely warm (2023). Conversely, the cold years (2005 and 2010) are classified as very cold. This consistency provides further validation of the quality of the satellite data, confirming the effectiveness of this system in detecting LST. These results are further confirmed by data found in governmental statistic sources [44] and publications, such as [PERSON]'s article [45], which highlights the significant losses sustained by the citrus industry in the region due to severe frosts in 2005 and 2010. In this way, we were able to verify that not only does our methodology effectively detect frosts, but also that these events have indeed caused damage to the crops, making them a matter of concern for the agricultural sector. When analyzing the results from the seasonal Kendall trend test, we observe a clear upward trend in mean, maximum, and minimum temperatures over the study period, consistent with the predicted aridification of the region due to climate change. This finding is particularly significant in our study, as rising temperatures can ultimately lead to a decrease in frost events and less frost damage to vegetation. These observations are supported by the comparison of temperatures between the decades 2004-2013 and 2014-2023, which indicates that minimum, mean, and maximum temperatures have increased significantly in the last decade. Subsequently, we conducted a damage intensity analysis using the methodology we developed, applied to the various months and years within the study period. The results indicate that the months with the most significant damage align with the winter months, specifically January and February, with January showing the highest frequency of frost events.