Abstract Urban Heat Island (UHI) is a condition where urban areas suffer from a higher temperature compared to its surrounding counterparts. This phenomenon has brought many adverse effects in today’s densely populated city. This research studied the role of Urban Green Infrastructure (UGI) in mitigating Urban Heat Island (UHI) effects, by analysing the cooling intensity of the selected high-dense city areas which are Barcelona and Milan. This research is running through the use of GIS-based spatial analysis to evaluate the relationship between the vegetated area and its temperature which known as Normalized Difference Vegetation Index (NDVI) and the Land Surface Temperature (LST) respectively. By using the GIS software specifically ArcGIS, the dependant variables, NDVI and LST are calculated, standardized, and statistically synthesis using the Zonal Statistic tools in the mentioned software. Results from this research revealed a consistent inverse relationship between NDVI and LST value in both cities which affirm the understanding that higher NDVI (dense-vegetated area) leads to lower LST (cooler temperature condition). On the other hand, the relationship between cooling intensity and NDVI difference is proportional where larger cooling intensity will have a larger NDVI difference. However, due to variables such as geographical locations as well as the vegetative composition, there is still difference recorded in the cooling efficiency between both cities whereby Barcelona has a slightly higher cooling intensity than one calculated in Milan. The outcomes of this research acknowledge the benefits of UGI not only from its aesthetical and ecological value but rather its significant measures in cooling the areas. Hence, from this research, it is affirmed that the integration of UGI in planning the city is important and should be induced greatly. Apart from all these, the study also highlights the limitations that should be considered for further improvement such as the reliance on single-season satellite data, limited cooling metrics, and exclusion of other variables such as social and geographical variables. Overall, this study still achieves its mentioned objectives and is reliable with the planned methodology and available resources.