Digital twin-based system to support urban planners in mitigating the urban heat island (UHI) effect in Lahti
Himihami Mudiyanselage, Iresha Bandaranayake (2025)
Diplomityö
2025
School of Engineering Science, Tietotekniikka
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe20251207115391
https://urn.fi/URN:NBN:fi-fe20251207115391
Tiivistelmä
The Urban Heat Island (UHI) effect is a phenomenon where some urban areas experience higher temperatures than nearby rural regions. The effect is rapidly worsening as the population tends to move to city-centred areas and built-up environments expand. Additionally, reducing green spaces and natural cooling sources worsens these environmental changes. However, given current economic conditions and growing human needs, large construction and development projects have become unavoidable. Therefore, identifying sustainable strategies to minimize adverse effects, such as the UHI effect, is vital.
It has already been identified that modifications applied to city areas are affecting the UHI effect. Therefore, designing a digital tool to identify and understand how new modifications affect temperature conditions plays a crucial role in optimized city planning. The digital twin (DT) concept can be considered as one approach to address this scenario. A DT is a digital platform that works as a one-to-one mapping between a real-world environment and a digital simulation. This thesis proposes a solution for this scenario using a digital-twin system based on the city of Lahti, Finland. In particular, this work presents a DT system that allows users to implement modifications, including trees, built ups, and water bodies in the Lahti city area, and forecasts how they affect land surface temperature (LST). Design science research methodology was followed in the research.
The DT is combined with a machine learning model, which was trained to predict the LST of the city of Lahti, focusing on factors including geographical locations and spectral indices. The LST is forecasted, considering the changes that occurred after the modifications.
It has already been identified that modifications applied to city areas are affecting the UHI effect. Therefore, designing a digital tool to identify and understand how new modifications affect temperature conditions plays a crucial role in optimized city planning. The digital twin (DT) concept can be considered as one approach to address this scenario. A DT is a digital platform that works as a one-to-one mapping between a real-world environment and a digital simulation. This thesis proposes a solution for this scenario using a digital-twin system based on the city of Lahti, Finland. In particular, this work presents a DT system that allows users to implement modifications, including trees, built ups, and water bodies in the Lahti city area, and forecasts how they affect land surface temperature (LST). Design science research methodology was followed in the research.
The DT is combined with a machine learning model, which was trained to predict the LST of the city of Lahti, focusing on factors including geographical locations and spectral indices. The LST is forecasted, considering the changes that occurred after the modifications.