Page 51 - JCAU-6-3

Journal of Chinese
Architecture and Urbanism Utilization of rural heritage

Table 1. Results of the linear regression analysis of LS with RH, ESPL, WS, GVI, SVI, and R&PVI
Model Non-standardized Standardized t Significant Collinearity statistics F-value R 2 Durbin–
coefficient coefficient Watson
B Standard β Tolerance Variance
error inflation factor
LS
(Constant) 42.271 12.892 - 3.589 0.002 - - 3.787* 0.545 2.206
RH −0.110 0.196 −0.119 −0.564 0.580 0.540 1.852
ESPL 0.335 0.129 0.476 2.594 0.018 0.712 1.404
WS −1.722 1.431 −0.223 −1.203 0.244 0.699 1.431
GVI −0.010 0.031 −0.067 −0.332 0.743 0.583 1.716
SVI −0.072 0.066 −0.223 −1.093 0.288 0.576 1.737
R&PVI −0.011 0.054 −0.034 −0.202 0.842 0.872 1.147
Notes: *Indicates the correlation coefficient was significant at the p<0.05.
Abbreviations: CVI: Construction view index; ESPL: Equivalent sound pressure level; GVI: Green view index; LS: Level of stress; R&PVI: Road and
pavement view index; RH: Relative humidity; SVI: Sky view index; T : Air temperature; WS: Wind speed.
a
correlation between the sample data points and enhancing significantly positively correlated with pedestrian walking
the overall model validity. Regarding the significance pleasure (Gao & Dong, 2023; Wu et al., 2017; Yang et al.,
of individual regression coefficients, ESPL exhibits a 2009). However, in rural heritage tourism sites, especially
significant positive effect on LS, with a coefficient value in historic towns, the correlation between ESPL, R&PVI,
of 0.335 (t = 2.594; p = 0.018 [<0.05]). However, RH, SVI, and CVI and tourists’ stress levels surpasses that of GVI.
and R&PVI do not demonstrate a statistically significant This result may be attributed to the frequent positioning
relationship with LS, as their coefficient values exceed of historic towns on the outskirts of urban areas, where
0.05. To summarize, the analysis highlights the significant tourists have already experienced the transition from urban
influence of ESPL on LS. Therefore, in subsequent spatial to natural landscapes en route to the site, thereby elevating
optimization, focusing on the optimization of the acoustic their emotional thresholds toward natural landscapes.
environment in public spaces is necessary. However, the distinctive feature of historic towns in

4. Discussion rural heritage sites lies in the predominance of cultural
landscapes, comprising traditional dwellings and streets
Initially, when using the Kriging interpolation method rather than natural scenery. In this study, the roads and
in ArcGIS Pro to visualize the spatial distribution of buildings associated with R&PVI and CVI are exclusively
spatial perceptual element data and tourist stress data, artificial structures. It is evident that tourists in historic
several noteworthy observations emerge. The circular towns perceive cultural landscapes to a greater extent than
pattern observed in the LS distribution validates previous natural ones. In addition, the positive correlation between
research, which emphasizes the dynamic nature of tourists’ ESPL and LS indicates that within the context of historic
experiences (Fallon & Schofield, 2006; Wang et al., 2019). towns, experiencing the spatial ambiance elicits more
Subsequently, it becomes evident that areas predominantly positive emotions among tourists than simply appreciating
characterized by rural dwellings exhibit higher LS compared the visual scenery. Hence, it is evident that design methods
to those dominated by natural landscapes. This finding for urban renewal or rural human settlement improvement
aligns with the assertion made by (Chen et al., 2023; Luo cannot be directly applied to the spatial optimization of
et al., 2021) that panoramic views incorporating forests historic towns. Designers and managers should prioritize
and integrated residential areas significantly contribute to the creation of a pleasant spatial ambiance in public spaces
stress recovery and evoke low-intensity pleasure emotions and ensure proper maintenance of historic towns, which
among tourists. can enhance the perception and preference for the rural
In addition, correlation analyses were conducted using environment, thereby attracting people to relieve pressure
SPSS to explore the relationship between physical and in the town.
visual environment elements and stress data. On the one Finally, this study performed a linear regression
hand, the results diverge from those of spatial perception analysis of RH, ESPL, WS, GVI, SVI, R&PVI, and LS.
studies conducted in urban areas. In such studies, GVI was ESPL was found to significantly and positively affect stress,

Volume 6 Issue 3 (2024) 12 https://doi.org/10.36922/jcau.2481