Warming trends in the Nile Delta: A high-resolution Spatial statistical approach

Abstract

The Nile Delta, a region of historical significance, is facing significant environmental changes driven by climate change. This study employs a novel pixel-level spatial statistical analysis to assess the intensity and trends in the daytime and nighttime urban heat island (UHI) from 2003 to 2021. We employed high-resolution data from the Global Artificial Impermeable Area (GAIA) dataset (30 m), land surface temperature (LST) from the MODIS Aqua satellite 1000 m, and the MOD13A3 Normalized Difference Vegetation Index (NDVI) (1000 m). Bivariate choropleth maps were used to illustrate the spatial relationships between daytime and nighttime LST and NDVI. Ordinary least squares (OLS) regression method was used to calculate the trend for each pixel and the Mann-Kendall test was used to assess the statistical significance of the trend at 95% confidence level (p < 0.05). The central and southern regions of the delta experienced significant LST increases, highlighting the risk of warming due to vegetation degradation. Specifically, the diurnal LST trend ranged from −0.46 °C to 0.34 °C/year, while the nocturnal trend ranged from −0.12 °C to 0.26 °C/year. Spatially, the study also indicates cooling trends in coastal cities such as Port Said, New Damietta and Alexandria due to the moderate influence of the Mediterranean Sea. In contrast, the inland and southern Delta cities are warming rapidly. The relationship between diurnal UHI average and the NDVI showed a modest negative correlation (R = −0.31, p < 0.0001). This association was much stronger at night, with a negative correlation of (R = −0.71, P < 0.0001) A strong negative correlation between diurnal UHI trend and NDVI (R = −0.68, p < 0.0001). The relationship between nocturnal UHI trend and NDVI is negative (R = −0.61, p < 0.0001). The analysis reveals that 13 cities exhibited significant warming during the daytime, compared to 35 cities at night. The results highlight the importance of pixel-level data to accurately assess environmental changes and inform urban planning strategies to mitigate the effects of warming on the Nile Delta.