Abstract

During Hajj, Muslims throughout the globe assemble at the holy sites in Makkah, Saudi Arabia. The Saudi government aims to increase the number of pilgrims. To ensure the pilgrims’ safety from the impact of surface urban heat island (SUHI), a scientific approach using artificial intelligence and Earth observation (EO) is recommended for crowd management and human health. SUHI is usually measured using satellite LST data. UHIs impact the walkability of cities in hot climates. The development of digital technologies has provided researchers with a better understanding of crowd management modeling to control such a mass gathering, especially within the summer season and in drought regions. In this study, an approach was used to detect the UHI in holy sites and understand the factors causing them. To achieve this goal, EO data were used to calculate the LST using the Landsat 8 thermal band (TIRS) and calculating the surface emissivity and Normalized Difference Vegetation Index (NDVI). Then, UHIs were identified by adding the mean of the LST to half of its standard deviation. Based on the results of this study, LST had a strong correlation with NDVI (negative) in Arafah. In addition, the strength of the correlation became much weaker within Mina and Muzdalifah. As for the correlation of LST and elevation, the strength appeared to be weak but negative in Arafah, but stronger in Muzdalifah and Mina. The results show that there is a certain correlation between LST, NDVI, and NDBI and elevation in the study area. Using Earth observation technologies can help in studying climate change.

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