Spatiotemporal analysis of land surface temperature and land cover change: Assessing the impact of urbanization and vegetation dynamics

Abstract

Background: Land cover change refers to changes in the surface cover of an area over time due to natural and human factors. The urbanization of Cibadak District, near the toll exit, contrasts with the rural Cikidang District, resulting in different dynamics of land surface temperature (LST) and land cover change. This study focuses on the observed temperature increase in both districts from 2013 to 2023, aiming to analyze the relationship between land cover change and LST variation. Methods: This study used a spatiotemporal analysis method, with land cover as the independent variable and LST as the dependent variable. Clustered purposive sampling was used. Land cover was validated using Google Earth imagery, while LST was validated with air temperature data from BMKG. Landsat 8 imagery was processed using the Google Earth Engine (GEE) platform to create spatiotemporal maps of land cover and LST. The relationship between the two variables was analyzed through cross-sectional spatial analysis and statistical calculations, including Spearman correlation and multiple linear regression. Findings: From 2013 to 2023, the average increase in LST in land cover was 7.76°C. The analysis showed that vegetated land cover (forest and garden) showed temperatures between 24-32°C, while bare land had temperatures between 32-36°C, with bare land exceeding 40°C in 2023. The statistical results showed a strong positive correlation between land cover changes and LST increases. The correlation coefficient between 2013-2018 was 0.8117 (R² = 0.6588), and between 2018-2023, it was 0.7925 (R² = 0.6560). Conclusions: This study revealed a significant increase in LST in both study sites from 2013 to 2023, with land cover changes playing a key role in this trend. Urban areas with less vegetation contribute to higher temperatures, while vegetated areas help mitigate temperature increases. Novelty/Originality of this article: This study uniquely combines spatiotemporal analysis and statistical methods to assess the impact of land cover change on LST dynamics