# The Effect of Green Areas on Urban Microclimate: A University Campus Model Case
## 4 Conclusions  
This study, conducted within the scale of Recep Tayyip Erdogan University Zihni Derin Campus, has revealed surface temperature variations across different seasons and plant species. The findings reaffirm the critical role of green spaces in mitigating the urban heat island effect and regulating the microclimate. The measurements indicate that ivy-covered surfaces are among the most effective plant types in temperature regulation.  
The comparative evaluation of the four vegetation types--Deciduous Plants, Coniferous Plants, shrubs, and ivy--revealed consistent and statistically significant RSM models for each case (\(p<0.001\)). Among them, ivy exhibited the highest model fit (F = 81.76), while Coniferous Plants had the lowest (F = 69.34). In terms of explained variance, ivy also achieved the strongest model performance (92.49%), whereas Coniferous Plants showed the lowest (91.40%). The AT emerged as the most dominant variable across all models, with its impact being particularly prominent in ivy (71.45%) and Deciduous Plants (70.14%). The M showed the greatest effect in ivy (7.87%) and the least in shrubs (5.50%). The most influential two-way interaction observed was M\(\times\)AT, especially in shrubs (F = 41.35) and ivy (F = 41.04). This interaction was consistently strong across all plant types, supporting the physiological relevance of combined thermal and humidity effects. The WS\(\times\)AT interaction was statistically significant only for ivy and Coniferous Plants (\(p<0.05\)). The models demonstrated low error rates overall, with ivy showing the highest predictive reliability (error = 7.51%) and Coniferous Plants the lowest (error = 8.60%). Residual diagnostics, including normal probability plots and versus-fit analyses, confirmed the assumptions of normality and homoscedasticity, validating the robustness of the models. Additionally, contour plots revealed that optimal surface temperature responses were typically concentrated in red and yellow regions, indicating effective thermal regulation. These optimal zones were broader for ivy and Deciduous Plants, whereas shrubs and Coniferous Plants exhibited more localized response regions. Overall, these findings reinforce the dominant influence of AT and M on surface temperature regulation and highlight the effectiveness of RSM in capturing species-specific microclimatic behavior.  
Overall, the findings emphasize that species-specific physiological traits--such as canopy structure and transpiration efficiency--play a decisive role in microclimatic performance. The consistent dominance of AT and M across all models further reinforces their critical role in surface temperature regulation. Furthermore, the study demonstrates that data-driven modeling approaches like RSM are highly effective in capturing complex environmental interactions and can support the development of targeted climate-responsive green infrastructure strategies.  
Conceptualization, G.E.O. and C.A.; methodology, G.E.O.; software, C.A.; validation, C.A., G.E.O. and S.S.; formal analysis, C.A.; investigation, G.E.O. and S.S.; resources, S.S.; data curation, G.E.O.; writing--original draft preparation G.E.O. and C.A.; writing--review and editing, G.E.O.; visualization, G.E.O.; supervision, C.A.; project administration, G.E.O.; funding acquisition, S.S. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This study has been supported by the Recep Tayyip Erdogan University Development Foundation (Grant number: 02025003004333).  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding author.  
**Acknowledgments:** This study was conducted under the scope of a student project supported by TUBITAK 2023 Term 1 2209-A (Project number: 1919B012304029).  
**Conflicts of Interest:** The authors declare no conflicts of interest.