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Landscape Architecture Frontiers

ISSN 2096-336X

ISSN 2095-5413 (Online)

CN 10-1105/TU

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Landsc. Archit. Front.    2024, Vol. 12 Issue (3) : 73-88    https://doi.org/10.15302/J-LAF-1-020097
Research on the Influencing Mechanism of Historic Urban Landscape Characteristics on Public Sentiments and the Spatio-temporal Differentiation Patterns—A Case Study of Shaoxing Ancient City in Zhejiang Province, China
Tuo SHI, Wanchen SANG, Yunuo ZHENG()
Zhejiang University Urban-Rural Planning & Design Institute Co., Ltd., Hangzhou 310030, China
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Abstract

Combining research methods such as semantic analysis and Space-Time Cube, this paper proposes a "historic urban landscape–cognition–sentiment" analysis framework, covering aspects of heritage intrinsic value, urban functional value, and urban landscape value, and reveals the influencing mechanism of the characteristics of historic urban landscape (HUL) on public sentiments and the spatio-temporal differentiation patterns through the case study of the Shaoxing ancient city in China. The research findings include that different HUL characteristics had differentiated effects on public sentiments, and the effect of a same HUL characteristic on public sentiments varied between weekdays and weekends/holidays, and among different HULs. On weekends/holidays, public sentiments were more influenced by the intrinsic value factors of HUL (e.g., heritage level, heritage age), whereas on weekdays, they were more affected by urban functional value factors, and urban landscape value factors played a greater role in arousing people's positive sentiments. This study aims to provide scientific references for enhancing public perception and emotional experience in urban spaces and for identifying potential spatial improvement opportunities in historic cities.

● Innovatively proposes "HUL–Cognition–Sentiment" analysis framework, and systematically explores the influencing mechanism of HUL characteristics on public sentiments

● Studies the spatio-temporal differentiation patterns of public sentiments from the dimensions of HUL intrinsic value, urban functional value, and urban landscape value

● On weekends/holidays, public sentiments were more influenced by the intrinsic value factors of HUL, while on weekdays were more affected by urban functional value and urban landscape value factors

Keywords Historic Urban Landscape      Public Sentiments      Weibo Check-in Data      Spatio-temporal Differentiation Patterns      Space-Time Cube      Historic Urban Landscape–Cognition–Sentiment Analysis Framework     
Corresponding Author(s): Yunuo ZHENG   
Issue Date: 28 June 2024
 Cite this article:   
Tuo SHI,Wanchen SANG,Yunuo ZHENG. Research on the Influencing Mechanism of Historic Urban Landscape Characteristics on Public Sentiments and the Spatio-temporal Differentiation Patterns—A Case Study of Shaoxing Ancient City in Zhejiang Province, China[J]. Landsc. Archit. Front., 2024, 12(3): 73-88.
 URL:  
https://academic.hep.com.cn/laf/EN/10.15302/J-LAF-1-020097
https://academic.hep.com.cn/laf/EN/Y2024/V12/I3/73
Fig.1  HCS analysis framework.
Fig.2  Study area.
UserTextual dataRelease timeLongitudeLatitude
A"Xu Wei Art Museum is a surprise in Shaoxing. It has a sense of ideal pureness, and I like the building so much."2022-08-12120.574°E29.998°N
B"Extreme passion is spontaneous! Everyday on the road of enthusiasm, with light in the eyes and a beautiful future..."2022-10-01120.582°E30.004°N
C"Walking around the Cangqiao Zhijie Street, where I lived for two years many, many years ago. This is an old street, every morning the seniors chatting on the street and used to be busy all day long. Now there are various small shops including several cafes, with quite a charming style."2022-11-17120.573°E30.005°N
D"Kong Yiji has not been the figure of sadness, but has become a celebrity for fennel beans."2023-01-07120.578°E29.995°N
Tab.1  Examples of Weibo check-in data
CategoryWordAssigned value
PositiveContent2.1
Joyful2.6
Happy2.6
Peaceful0.8
NegativeIrritable–4.4
Disturbed–6.5
Scared–4.1
Unscrupulous–4.1
NeutralAccording to0.0
Phenomenon0.0
South Zone0.0
Adverb of degreeRemarkably1.8
Very1.8
A little0.7
Deactivated wordToo; also; thus; besidesEliminated, no assigned value
Tab.2  Examples of word value assignment by the BosonNLP sentiment dictionary
Fig.3  Space-Time Cube.
VariableMeanSDMinimumMaximum
Score of public sentiments6.9836.664–22.60065.896
Intensity of public sentiments7.1606.4740.00065.896
Tab.3  Descriptive statistics of public sentiments
Fig.4  Analysis of the number of Weibo posts per day.
Fig.5  Analysis of the daily average score of public sentiments.
Fig.6  Spatial distribution of public sentiments on weekdays.
Fig.7  Spatial distribution of public sentiments on weekends/holidays.
Fig.8  Hot and cold spot analysis of public sentiments.
VariableDescriptionSource
Dependent variable
Score of public sentiments (weekday)Score of public sentiments on weekdays
Score of public sentiments (weekend/holiday)Score of public sentiments on weekends/holidays
Independent variable
Heritage intrinsic valueHeritage levelAssigned value of the level of heritage conservation unitsRefs. [32] [33]
Heritage ageAssigned value of the age of heritage conservation unitsRefs. [32] [33]
Natural asset valueDEM calculation of slopeRef. [46]
Urban functional valueBuilding heightOverall height of the building (m)Ref. [48]
Internet popularityCount of internet postsRefs. [26] [37]
Density of recreational and entertainment facilityDistribution density of recreational and entertainment POI (per m2)Refs. [26] [37] [47]
Density of medical service facilityDistribution density of medical service POI (per m2)Refs. [26] [37] [47]
Density of transportation facilityDistribution density of transportation POI (per m2)Refs. [26] [37] [47]
Urban landscape valueOpenness of water bodyArea of water body (m2)Ref. [27]
Openness of green spaceArea of green space (m2)Ref. [27]
Degree of mixed land usePiln(Pi)Pi is the area ratio of the land use type i to the gridRefs. [27] [47]
Tab.4  Explanatory variables for the impact of public sentiments
R2RADJ2AICσ2SDPseudo-t statistics correction key values
Weekday0.87530.86777163.82531.37061.29223.4140
Weekend/holiday0.90140.89546836.80191.18351.11593.4134
Tab.5  Results of GWR models
Explanatory variableMeanSDMinimumMedianMaximum
Heritage intrinsic valueHeritage level0.71130.4162–12.26280.605520.2484
Heritage age1.18730.5980–14.95690.546334.6736
Natural aesthetic value0.02690.0377–0.73110.01211.3360
Urban functional valueBuilding height0.00100.0032–0.03800.00010.0508
Internet popularity (weekday)0.00070.0005–0.04580.00010.1445
Density of recreational and entertainment facility–0.00020.0048–0.39380.00040.1557
Density of medical service facility–0.08760.0268–1.4089–0.04801.0971
Density of transportation facility0.04300.0169–0.75310.02180.6314
Urban landscape valueOpenness of water body0.00050.0010–0.01090.00040.0131
Openness of green space0.00010.0006–0.00880.00010.0124
Degree of mixed land use0.01540.1506–1.76350.03961.6686
Tab.6  Results of GWR model coefficients for public sentiments on weekdays
Explanatory variableMeanSDMinimumMedianMaximum
Heritage intrinsic valueHeritage level0.05420.3853–30.98360.061912.8814
Heritage age0.50940.5495–27.66640.134248.1832
Natural aesthetic value–0.00590.0351–0.6519–0.01051.0412
Urban functional valueBuilding height–0.00180.0029–0.0692–0.00080.1014
Internet popularity (weekend/holiday)–0.00160.0006–0.0887–0.00020.0772
Density of recreational and entertainment facility–0.00090.0044–0.74860.00070.2605
Density of medical service facility–0.01470.0248–1.88100.00481.5385
Density of transportation facility0.00810.0156–0.7623–0.00040.9051
Urban landscape valueOpenness of water body0.00040.0000–0.00460.00010.0049
Openness of green space0.00050.0006–0.00860.00010.0063
Degree of mixed land use–0.00340.1400–1.60720.00681.0713
Tab.7  Results of GWR model coefficients for public sentiments on weekends/holidays
Fig.9  Spatio-temporal differentiation of the impact of five HUL characteristics on public sentiments.
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