Study on the Distribution Characteristics and Dynamic Evolution of Green Buildings in China Based on the K-means Algorithm

With the concept of green and sustainable development, the gap of green building growth among provinces in China is becoming increasingly obvious. Based on the data of wastewater discharge, air pollution and urban environmental infrastructure investment in China Statistical Yearbook, K-means clustering algorithm is used to classify the distribution of green buildings, and the key influencing factors and dynamic evolution trend are analyzed. At the same time, focusing on the energy consumption of each region, PCA main city analysis is used to study the main indicators affecting the green performance of buildings, and the differences and connections of these analysis methods are analyzed in depth. The results show that: (1) There are obvious regional differences. Green building development in eastern coastal and highly urbanized areas is faster (such as Yangtze River Delta and Pearl River Delta), while that in northwest and underdeveloped areas is slower. (2) Industrial wastewater emission, sulfur dioxide emission, industrial smoke (dust) emission and population density are the main energy indicators affecting the green performance of buildings.(3) Economic development, policy support, environmental governance and market demand are key determinants of green building concentration. Efficient provinces (e.g. Beijing, Shanghai) benefit from strong economic fundamentals, policy incentives, advanced environmental management and high market demand, making them leaders in green building development. (4)The evolution of green building has experienced three stages: policy-driven, market-led and technology-driven. In the early stages, government policies play a crucial role; in the medium stage, market demand becomes the main driving force; in the later stage, technological innovation, resource recycling and green social system development become key factors for sustainable growth. In the future, provinces should adopt collaborative innovation, policy optimization and resource sharing strategies to promote the development of high-quality green buildings and contribute to carbon neutrality goals and ecological sustainability.

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Publication Details

Published
2025-03-21
DOI
https://doi.org/10.1109/iscait64916.2025.11010510
Primary Topic
Digital Media and Visual Art
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article
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article

Study on the Distribution Characteristics and Dynamic Evolution of Green Buildings in China Based on the K-means Algorithm

Xinhua Wu, Zhao Bao
Digital Media and Visual Art
article

Study on the Distribution Characteristics and Dynamic Evolution of Green Buildings in China Based on the K-means Algorithm

Xinhua Wu, Zhao Bao
article en

Abstract

With the concept of green and sustainable development, the gap of green building growth among provinces in China is becoming increasingly obvious. Based on the data of wastewater discharge, air pollution and urban environmental infrastructure investment in China Statistical Yearbook, K-means clustering algorithm is used to classify the distribution of green buildings, and the key influencing factors and dynamic evolution trend are analyzed. At the same time, focusing on the energy consumption of each region, PCA main city analysis is used to study the main indicators affecting the green performance of buildings, and the differences and connections of these analysis methods are analyzed in depth. The results show that: (1) There are obvious regional differences. Green building development in eastern coastal and highly urbanized areas is faster (such as Yangtze River Delta and Pearl River Delta), while that in northwest and underdeveloped areas is slower. (2) Industrial wastewater emission, sulfur dioxide emission, industrial smoke (dust) emission and population density are the main energy indicators affecting the green performance of buildings.(3) Economic development, policy support, environmental governance and market demand are key determinants of green building concentration. Efficient provinces (e.g. Beijing, Shanghai) benefit from strong economic fundamentals, policy incentives, advanced environmental management and high market demand, making them leaders in green building development. (4)The evolution of green building has experienced three stages: policy-driven, market-led and technology-driven. In the early stages, government policies play a crucial role; in the medium stage, market demand becomes the main driving force; in the later stage, technological innovation, resource recycling and green social system development become key factors for sustainable growth. In the future, provinces should adopt collaborative innovation, policy optimization and resource sharing strategies to promote the development of high-quality green buildings and contribute to carbon neutrality goals and ecological sustainability.

Shandong University of Science and Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 78%
Digital Media and Visual Art
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