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Remote Sensing, Vol. 16, Pages 3405: ​​Mapping the impact of Olympic Games urban planning on land surface temperatures: an estimation using Landsat series and Google Earth Engine

Remote Sensing, Vol. 16, Pages 3405: ​​Mapping the impact of Olympic Games urban planning on land surface temperatures: an estimation using Landsat series and Google Earth Engine

Remote Sensing, Vol. 16, Pages 3405: ​​Mapping the impact of Olympic Games urban planning on land surface temperatures: an estimation using Landsat series and Google Earth Engine

Remote Sensing doi: 10.3390/rs16183405

Authors: Joan-Cristian Padró Valerio Della Sala Marc Castelló-Bueno Rafael Vicente-Salar

The Olympic Games are a sporting event and a catalyst for urban development in their host city. In this study, we used remote sensing and GIS techniques to investigate the impact of Olympic infrastructure on the surface temperature of urban areas. Using Landsat Series Collection 2 Tier 1 Level 2 data and Google Earth Engine (GEE) cloud computing, this study investigates the effects of different forms of urban planning of Olympic facilities in different historical moments and location typologies, as follows: monocentric, polycentric, peripheral, and clustered Olympic ring. The GEE code applies to the Olympic Games that took place from Paris 2024 to Montreal 1976. However, this paper focuses specifically on the representative cases of Paris 2024, Tokyo 2020, Rio 2016, Beijing 2008, Sydney 2000, Barcelona 1992, Seoul 1988, and Montreal 1976. The study is not concerned with obtaining absolute land surface temperatures (LST) alone, but rather with the relative influence of mega-event infrastructures on mitigating or increasing urban heat. As such, the locally normalized land surface temperature (NLST) was used for this purpose. In some cities (Paris, Tokyo, Beijing, and Barcelona), it has been found that Olympic planning resulted in the development of green spaces, creating “green patches” that contribute to lower than average temperatures. However, it should be noted that there is significant variation in temperature within intensely built-up areas, such as Olympic Villages and the surrounding areas of the Olympic stadium, which can become “hotspots”. Therefore, it is important to recognize that different planning typologies of Olympic infrastructure can have different effects on urban heat islands, with the polycentric and clustered Olympic ring typologies showing a mitigating effect. This research contributes to a cloud computing methodology that can be updated for future Olympic Games or adapted for other mega-events and uses a widely available remote sensing data source to study a specific urban planning context.

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