Abstract:Urban heat islands (UHI) are formed due to complex interactions between various factors. UHI, its contributing factors, and their interaction vary over time and location. Accordingly, understanding the causal relation between UHI and its contributing factors is essential to minimizing its adverse effects on the environment and human health. Here, we proposed a statistical method based on Hotelling's T-square test to analyze this association. The proposed test estimates the UHI trends across different urban districts and compares the UHI contributing factors between the districts with increasing and non-increasing UHI trends. This comparison, if significantly different, can be interpreted as evidence of a causal association between the factor and UHI. This research used the proposed test to analyze the UHI and its contributing factors across 22 municipal districts of Tehran between 2003 and 2021. We examined the time series of weather conditions (measured by precipitation, NDSI, and NDWI), vegetation cover (measured by NDVI and EVI), and urban density (measured by NDBI) as factors contributing to the UHI, which was measured through nighttime LST. The results showed that all districts in Tehran exhibited stable or increasing trends in LST, leading to UHI effects. The proposed test indicated that the temporal changes in NDWI and NDBI did not have a causal relationship with UHIs. Meanwhile, variations in other factors were identified as contributing to the intensification of UHIs.