Assessment of the impact of impervious surface increase on urban heat island and vegetation by remote sensing and statistical analysis: the case of Türkiye/Niğde city center (2013-2024)

Year 2025, Volume: 7 Issue: 1, 69 - 90, 30.06.2025

Münevver Gizem Gümüş , Kutalmış Gümüş

https://doi.org/10.51489/tuzal.1663695

Abstract

The expansion of impervious surfaces, reduction of vegetation cover, and heat-retaining properties of artificial materials intensify the Urban Heat Island (UHI) effect, leading to higher surface temperatures in urban areas compared to rural surroundings. This phenomenon increases energy demand, interacts with climate change, and negatively impacts public health. This study investigates the spatial and temporal changes in vegetation, impervious surface density, and land surface temperature (LST) in Niğde, Türkiye, between 2013 and 2024. NDVI (Normalized Difference Vegetation Index), NDBI (Normalized Difference Built-up Index), and LST were derived from Landsat 8 OLI/TIRS satellite imagery and analyzed using Google Earth Engine (GEE) and ArcGIS 10.8. Index values were extracted from 500 randomly distributed points. Data normality was assessed using Kolmogorov-Smirnov and Shapiro-Wilk tests. Paired sample t-tests and Wilcoxon signed-rank tests were used to evaluate temporal differences, while Pearson, Spearman's rho, and Kendall's tau-b correlation coefficients were used to determine the level of relationship between variables. Results show no significant change in NDVI (p > 0.05), but statistically significant increases in both NDBI and LST (p < 0.05). A strong negative correlation was observed between NDVI and NDBI (r = -0.91), and a positive correlation between NDBI and LST (r = 0.39). Between 2013 and 2024, impervious surfaces expanded by 59.63% (from 14.02 km² to 22.38 km²), while dense vegetation areas declined by 50%. These findings confirm that urbanization has led to vegetation loss and increased surface temperatures. The study offers valuable insights into the UHI effect using remote sensing and statistical analysis and contributes to sustainable urban planning and climate adaptation strategies.

Keywords

LST , NDBI , NDVI , Google Earth Engine , Spatial analysis , Imprevious surface

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