Grid Density Algorithm-Based Second-Hand Housing Transaction Activity and Spatio-Temporal Characterization: The Case of Shenyang City, China

Second-hand housing transactions constitute a significant segment of the real estate market and are vital for its robust development. The dynamics of these transactions mirror the housing preferences of buyers, and their spatial and temporal analysis elucidates evolving market patterns and buyer beh...

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Bibliographic Details
Published inISPRS international journal of geo-information Vol. 13; no. 8; p. 286
Main Authors Ren, Jiaqiang, Gao, Xiaomeng
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.08.2024
Subjects
activity level
Algorithms
Bargaining
Bayesian analysis
Bayesian optimization
Clustering
Density
Equilibrium
grid density algorithm
Housing
Housing prices
Influence
Investigations
Land use
Methods
Probability theory
Real estate
second-hand housing transactions
Spatial analysis
spatio-temporal characteristics
Tax assessments
Taxation
Trends
Urban areas
China
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Summary:Second-hand housing transactions constitute a significant segment of the real estate market and are vital for its robust development. The dynamics of these transactions mirror the housing preferences of buyers, and their spatial and temporal analysis elucidates evolving market patterns and buyer behavior. This study introduces an innovative grid density clustering algorithm, dubbed the RScan algorithm, which integrates Bayesian optimization with grid density techniques. This composite methodology is employed to assess clustering outcomes, optimize hyperparameters, and facilitate detailed visualization and analysis of transaction activity across various regions. Focusing on Shenyang, a major urban center in Northeast China, the research spans from 2018 to 2023, exploring the second-hand housing transaction activity and its spatio-temporal attributes. The results reveal temporal fluctuations in transaction intensity across different Shenyang regions, although core areas of high activity remain constant. These regions display a heterogeneous pattern of irregularly stepped and clustered distributions, with a notable absence of uniformly high-activity zones. This study pioneers a novel methodological framework for investigating second-hand housing transactions, offering crucial insights for market development and policy formulation in Shenyang.
ISSN:2220-9964
DOI:10.3390/ijgi13080286