## 5 Conclusions  
This study was carried out with the aim of mapping, quantifying, and analyzing the spatiotemporal variation in UHIs over the arid Al-Ahsa area, in the Kingdom of Saudi Arabia. Additionally, it aimed to scope the extent of urban growth and its relative heat island effect from 1990 to 2020. The work was accomplished by quantifying the spatial variety of the UHIs, assessing the crucial factors and forms of the LST and NDBI distribution through space and time, and assessing the impact of LULC change on surface temperature throughout the 30 year period. The subsequent concluding points have been inferred as study findings:  
* The technique of change detection was performed (with classification accuracies between 90 and 96%) to measure and map possible growth in urbanization and its effect on UHIs and UHI intensity quantification. The obtained change values revealed a considerable rate of growth in the urban area of 17.15% to 45.8% of the total LULC from 1990 to 2020, respectively. * Considering the intensity of heat islands (which represents the difference between heat islands for urban areas and heat islands for suburbs), no abrupt variations were observed. The intensities ranged between 10.4 \({}^{\circ}\)C for 1990 and 8.7 \({}^{\circ}\)C for 2020. * Taking into account the spatial distribution of UHIs, a remarkable consistency was observed throughout all study periods between NDBI and the LST, specifically over the western, eastern, and northern parts of the study site, where intense built-up complexes of main cities and villages are situated. * A spatial autocorrelation analysis consisting of hot spots analysis and the BiLISA approach was implemented to identify particular relationships and clustering of variables. Further, it was intended to reveal the extent to which the nature of the association between the urban sprawl and UHIs can change. We found that most of the areas in the western, eastern, and southeastern parts (designated as built-up surfaces) had experienced hot spots, while areas covered with palm trees experienced clustering zones of cold spots, with 99% confidence for both. On the other hand, the BiLISA spatial autocorrelation revealed a significant consistency between LST and NDBI, with Moran's \(I\) values of 0.41 and 0.45 for 1990 and 2020, respectively, with a significance (\(p\)-value) of 0.001 for all periods. The spatiotemporal development in the built-up surfaces cover and its interaction with emissivity and LST could be employed as an assessment mechanism for the spatial fluctuation of metropolitan heat islands, which are considered a primary cause of supplemental hot days and heat waves that increase heat-related deaths in metropolis areas. However, this finding may be unique to the topographic, climatic, geographic, and environmental conditions in the Eastern region, where the study site was located. Co-occurring urbanization in other geographic regions may differ sufficiently to alter the UHI intensity and distribution. In addition, it is uncertain how UHI intensity and distribution may be affected by environmental conditions such as desertification. Future investigations will require a better understanding of factors controlling the long-term effects of urban development on UHIs. In particular, more comparisons of UHI intensity with sand encroachment or other types of land degradation are needed to determine how and under what circumstance these factors may differentially influence UHI patterns. Conceptualization, A.S. and A.H.; methodology, A.H. and A.S.; software, A.S.; validation, A.H. and A.S.; formal analysis, A.H.; investigation, A.S.; resources, A.H.; data curation, A.S.; writing--original draft preparation, A.H. and A.S.; writing--review and editing, A.S.; visualization, A.S. and A.H.; supervision, A.H.; project administration, A.S.; funding acquisition, A.H. All authors have read and agreed to the published version of the manuscript.