The Role of Urban Vegetation in Urban Heat Island (UHI) Mitigation and Outdoor Thermal Comfort Improvement : Case Study of Tampere, Finland
Atienza, Yasmin (2023)
Atienza, Yasmin
2023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2023110128288
https://urn.fi/URN:NBN:fi:amk-2023110128288
Tiivistelmä
Nowadays, cities face continuous exposure to the effects of urban heat island (UHI), a phenomenon where urban areas experience higher temperatures than rural areas (Oke et al., 2017). In Tampere, Finland, it is projected that by 2035, the number of hot days will increase by approximately 64%, and that more than 60% of the city’s population will be living in warmer urban zones (Sitowise, 2022b). In this regard, it is essential to consider UHI mitigation strategies which relates in an urban planning perspective to promote a climate-resilient development. In Tampere, urban vegetation, particularly trees, has been prioritised as a key measure for climate change mitigation and adaptation.
The main aim of this research is to assess the influence of urban vegetation on land surface temperature (LST) and outdoor thermal comfort (OTC) at both the city scale and block scale levels respectively. The study employed remote sensing and statistical methods for the city scale analysis which involves the correlation of LST and Normalised Difference Vegetation Index (NDVI), and the distribution of LST across different urban densities represented by Local Climate Zones (LCZ). The research utilised ENVI-met for the block scale analysis which includes the simulation of four (4) developed scenarios: BC (existing), C1 (no vegetation), C2 (greening) and C3 (building height increase) on both critical cold winter and hot summer days.
The results of the city scale analysis show that LST and NDVI has a moderate inverse (r=-0.55, -0.59) correlation during summers, and has a weak direct (r=0.18, 0.25) correlation during winters. Generally, the LST-LCZ distribution shows that built type LCZs with lesser pervious surface generates higher LSTs than the land cover types. In Tampere’s city centre, LCZ 2 consistently has the highest LSTs, while LCZ G has the lowest for both seasons. The results shows that this distribution is more consistent in summer than in winter following the rank order: LCZ 2 > 8 > E > 5 > 6 > 9 > D > B > A > G. Lastly, the simulation results assessed through air temperature (Tair), mean radiant temperature (MRT), and physiological equivalent temperature (PET), revealed that the presence and addition of vegetation, specifically deciduous trees (C2), brings a significant OTC improvement in both seasons. Moreover, the results exhibits that the absence of vegetation (C1) which leads to the increase in impervious surface cover resulted to an inverse effect, bringing more discomfort to users. Results also show that in C3, increasing the building height (h=23 mts.) brings insignificant effect especially to open spaces. Overall, the city can leverage these findings to inform its urban planning decisions, prioritize greening interventions, and create urban environments that enhance the well-being and comfort of its residents while mitigating the effects of UHI brought about by climate change.
The main aim of this research is to assess the influence of urban vegetation on land surface temperature (LST) and outdoor thermal comfort (OTC) at both the city scale and block scale levels respectively. The study employed remote sensing and statistical methods for the city scale analysis which involves the correlation of LST and Normalised Difference Vegetation Index (NDVI), and the distribution of LST across different urban densities represented by Local Climate Zones (LCZ). The research utilised ENVI-met for the block scale analysis which includes the simulation of four (4) developed scenarios: BC (existing), C1 (no vegetation), C2 (greening) and C3 (building height increase) on both critical cold winter and hot summer days.
The results of the city scale analysis show that LST and NDVI has a moderate inverse (r=-0.55, -0.59) correlation during summers, and has a weak direct (r=0.18, 0.25) correlation during winters. Generally, the LST-LCZ distribution shows that built type LCZs with lesser pervious surface generates higher LSTs than the land cover types. In Tampere’s city centre, LCZ 2 consistently has the highest LSTs, while LCZ G has the lowest for both seasons. The results shows that this distribution is more consistent in summer than in winter following the rank order: LCZ 2 > 8 > E > 5 > 6 > 9 > D > B > A > G. Lastly, the simulation results assessed through air temperature (Tair), mean radiant temperature (MRT), and physiological equivalent temperature (PET), revealed that the presence and addition of vegetation, specifically deciduous trees (C2), brings a significant OTC improvement in both seasons. Moreover, the results exhibits that the absence of vegetation (C1) which leads to the increase in impervious surface cover resulted to an inverse effect, bringing more discomfort to users. Results also show that in C3, increasing the building height (h=23 mts.) brings insignificant effect especially to open spaces. Overall, the city can leverage these findings to inform its urban planning decisions, prioritize greening interventions, and create urban environments that enhance the well-being and comfort of its residents while mitigating the effects of UHI brought about by climate change.
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