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An Improved Method to Identify Built-Up Areas of Urban Agglomerations in Eastern and Western China Based on Multi-Source Data Fusion

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Publicado en:Land vol. 13, no. 7 (2024), p. 974
Autor principal: Lu, Xiaoyi
Otros Autores: Yang, Guang, Chen, Shijun
Publicado:
MDPI AG
Materias:
China
Yangtze River Delta
Urbanization
Socioeconomic factors
Agglomeration
Identification methods
Identification
Cities
Image processing
Data integration
Monitoring
Economic factors
Dimensional analysis
Urban areas
Urban development
Image contrast
Research methodology
Remote sensing
Spatial data
Economic statistics
Socioeconomics
Gross Domestic Product > GDP
Algorithms
Qualitative research
Comparative analysis
Acceso en línea:Citation/Abstract
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Resumen:The rapid urbanization in China has significantly contributed to the vast expansion of urban built-up areas. Precisely extracting and monitoring these areas is crucial for understanding and optimizing the developmental process and spatial attributes of smart, compact cities. However, most existing studies tend to focus narrowly on a single city or on global scale with a single dimension, often ignoring mesoscale analysis across multiple urban agglomerations. In contrast, our study employs GIS and image-processing techniques to integrate multi-source data for the identification of built-up areas. We specifically compare and analyze two representative urban agglomerations in China: the Yangtze River Delta (YRD) in the east, and the Chengdu–Chongqing (CC) region in the west. We use different methods to extract built-up areas from socio-economic factors, natural surfaces, and traffic network dimensions. Additionally, we utilize a high-precision built-up area dataset of China as a reference for verification and comparison. Our findings reveal several significant insights: (1) The multi-source data fusion approach effectively enhances the extraction of built-up areas within urban agglomerations, achieving higher accuracy than previously employed methods. (2) Our research methodology performs particularly well in the CC urban agglomeration. The average precision rate in CC is 96.03%, while the average precision rate in YRD is lower, at 80.33%. This study provides an objective and accurate assessment of the distribution characteristics and internal spatial structure of built-up areas within urban agglomerations. This method offers a new perspective for identifying and monitoring built-up areas in Chinese urban agglomerations.
ISSN:2073-445X
DOI:10.3390/land13070974
Fuente:Publicly Available Content Database