Multiscale analysis of human social sensing of urban appearance and its effects on house price appreciation in Wuhan, China

Jia, Jia; Xiao-qing, Zhang; Huang, Caihong; Luan, Hao

doi:10.1016/j.scs.2022.103844

Cited by 22 publications

(3 citation statements)

References 68 publications

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“…Cluster analysis is a multivariate statistical analysis method that divides a sample into multiple categories comprising similar objects. Cluster analysis allows for the exploration of homogeneity within groups, correlations, and major differences across groups [ 65 ]. K-means clustering methods perform clustering through continuous iterations until the desired result is achieved.…”

Section: Methodsmentioning

confidence: 99%

Spatial impacts of the intercity flow of long stay international visitors based on mobile phone data in Yangtze River Delta, China

Wang,

Zhu,

Meng

2023

PLoS ONE

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The intercity daily flow of long stay international visitors (LSIV) reflects the economic globalisation and regional integration of a region. We made the first attempt to use mobile phone data to identify international visitors who stayed longer than one month in the Yangtze River Delta (YRD) region in 2019, analysed the spatial patterns of LSIV, and revealed the impact factors associated with the daily intercity flow of LSIV. We discussed spatial dependence using multiscale geographically weighted regression (MGWR), and performed cluster analysis to understand the combination effects. The results show that enterprises have the largest effect, AQI and administrative hierarchy have relatively low effects, and income, imports and exports do not have any significant effect. Overall, the economically developed eastern regions of the YRD region are more attractive for daily travel by LSIV, with the Shanghai metropolitan area being the most attractive. Our findings provide new insights into the relationship between the intercity daily flow of LSIV and the urban economy and society in the delta region to help suggest planning recommendations to enhance the globalisation development strategy and provide a better environment for international visitors in the delta region.

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Section: Methodsmentioning

confidence: 99%

Spatial impacts of the intercity flow of long stay international visitors based on mobile phone data in Yangtze River Delta, China

Wang,

Zhu,

Meng

2023

PLoS ONE

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“…The government also pays attention to the issue of housing prices in order to balance the interests of different parts of the city through the location selection of public facilities, so as to maintain social harmony in a long-term sustainable manner [2]. Simultaneously, researchers hope to use house prices as a reference standard to measure the value of space so as to conduct long-term exploration of variables that affect it, which allows them to maintain a high enthusiasm for the issue of property prices [3]. Consequently, in essence, the reason why different groups pay attention to property prices is to maintain a highquality living environment in a long-term sustainable manner.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Rail Accessibility and Road Spatial Pattern Effects on House Prices

et al. 2022

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The continuous change process in the impact of differences in public transport accessibility has not been explained specifically in previous studies. This study reveals that the interaction between two continuous explanatory variables has a significant impact on the explained variable in the hedonic model. The study takes the accessibility variable in the house price model as an instance, dividing the accessibility variable of the residential community into two parts. The first part is the rail accessibility defined by the Euclidean distance from the residential community to the nearest rail transportation station. The second part is the road accessibility defined by two Space Syntax indicators, connectivity and carrying capacity, according to the spatial pattern of the road network. As demonstrated by the spatial interactive regression model, this research finds that road connectivity has a significant regulating effect on the impact of the distance to the closest rail station on house prices based on the empirical evidence from Fuzhou, China.

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“…The model can well simulate the geospatial response process of independent and dependent variables [24,25] to accurately identify the different scales, degrees, and directions of the effects of different factors on the dependent variable. MGWR was widely used in various disciplines, such as modeling of spatial relationship between geographic changes in housing prices and influencing factors [26,27]; quantification of spatial non-stationarity between ecosystem service and landscape structure [28]; and study of carbon emissions and the spatial heterogeneity of impact factors [29].…”

Section: Introductionmentioning

confidence: 99%

Detecting Spatially Non-Stationary between Vegetation and Related Factors in the Yellow River Basin from 1986 to 2021 Using Multiscale Geographically Weighted Regression Based on Landsat

et al. 2022

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As an important ecological barrier in northern China, the ecological environment of the Yellow River Basin (YRB) has been greatly improved in recent decades. However, due to spatially non-stationarity, the contribution of human activities and natural factors to vegetation restoration may exhibit different coupling effects in various areas. In this paper, the Normalized Difference Vegetation Index (NDVI) of the YRB from 1986 to 2021 was used as the dependent variable, and terrain, meteorological, and socioeconomic factors were used as independent variables. With the help of Multiscale Geographically Weighted Regression (MGWR), which could handle the scale difference well, combined with Ordinary Least Squares (OLS) and traditional Geographically Weighted Regression (GWR), the spatial non-stationary relationship between vegetation and related factors was discussed. The results showed that: (1) The vegetation was subject to fluctuating changes from 1986 to 2021, mainly improving, with a growth rate of 0.0018/year; the spatial distribution pattern of vegetation in the basin was high in the southeast and low in the northwest. (2) Compared with the OLS and GWR, the MGWR could better explain the relationship between vegetation and various factors. (3) The response scale of vegetation and related factors was significantly variant, and this scale changed with time. The effect scale of terrain factor is lower than climate and social factors. (4) There was obvious spatial heterogeneity in the effects of various influencing factors on vegetation. The vegetation of the upstream was mainly positively affected by mean annual temperature (coefficients ∈ [1.507, 1.784]); while potential evapotranspiration was the dominant factor of vegetation in the middle and lower reaches of the basin (coefficients ∈ [−1.724, −1.704]); it was worth noting that the influence of social factors on vegetation was relatively small. This study deeply explores the spatial non-stationarity of vegetation and various related factors, thereby revealing the evolution law of vegetation pattern and providing scientific support for monitoring and improving the ecological environment quality of the YRB.

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Multiscale analysis of human social sensing of urban appearance and its effects on house price appreciation in Wuhan, China

Cited by 22 publications

References 68 publications

Spatial impacts of the intercity flow of long stay international visitors based on mobile phone data in Yangtze River Delta, China

Spatial impacts of the intercity flow of long stay international visitors based on mobile phone data in Yangtze River Delta, China

Nonlinear Rail Accessibility and Road Spatial Pattern Effects on House Prices

Detecting Spatially Non-Stationary between Vegetation and Related Factors in the Yellow River Basin from 1986 to 2021 Using Multiscale Geographically Weighted Regression Based on Landsat

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