Impact of Urban Green Spaces Based on Geographic Information System on Residential Area Prices and Development Strategies: A Case Study of Wuhan City, Hubei Province

In this study, we utilized the ArcGIS Geographic Information System (ArcGIS) to study the relevant datasets of park green and residential subsidiary green spaces in Wuhan City, and at the same time, scraped residential area prices data in Wuhan using big data technology.The inverse distance weight spatial interpolation method is employed to analyze the spatial patterns of residential area prices.Distances from each residential area to park green spaces at different scales are calculated to investigate their impact on residential area prices.Three strategies are proposed: the tailored allocation of different types of park based on regional characteristics, the implementation of "quantity guarantee and quality improvement" measures to enhance the quality of residential green spaces, and the promotion of interaction between park green and residential green spaces.These strategies aim to particularly uplift housing prices in economically disadvantaged areas, ultimately achieving shared prosperity.

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Publication Details

Journal
Sensors and Materials
Published
2024-10-25
DOI
https://doi.org/10.18494/sam5154
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
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article

Impact of Urban Green Spaces Based on Geographic Information System on Residential Area Prices and Development Strategies: A Case Study of Wuhan City, Hubei Province

Ying Yu, Di Li, Li Cheng, Li Xiong et al.
Sensors and Materials
Remote Sensing and Land Use
article

Impact of Urban Green Spaces Based on Geographic Information System on Residential Area Prices and Development Strategies: A Case Study of Wuhan City, Hubei Province

Ying Yu, Di Li, Li Cheng, Li Xiong, X. Lin
article en

Abstract

In this study, we utilized the ArcGIS Geographic Information System (ArcGIS) to study the relevant datasets of park green and residential subsidiary green spaces in Wuhan City, and at the same time, scraped residential area prices data in Wuhan using big data technology.The inverse distance weight spatial interpolation method is employed to analyze the spatial patterns of residential area prices.Distances from each residential area to park green spaces at different scales are calculated to investigate their impact on residential area prices.Three strategies are proposed: the tailored allocation of different types of park based on regional characteristics, the implementation of "quantity guarantee and quality improvement" measures to enhance the quality of residential green spaces, and the promotion of interaction between park green and residential green spaces.These strategies aim to particularly uplift housing prices in economically disadvantaged areas, ultimately achieving shared prosperity.

Sensors and MaterialsVol. 36(10)
Beijing Forestry University (CN)
Sustainable cities and communities
Openalex Percentile: Top 78%
Remote Sensing and Land Use
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Impact of Urban Green Spaces Based on Geographic Information System on Residential Area Prices and Development Strategies: A Case Study of Wuhan City, Hubei Province — Ying Yu, Di Li, et al. · Sensors and Materials (2024) | TGRS Research Map | TGRS