Sustainable Urbanization in the Yangtze River Basin Through Built-Up Area Extraction

The Yangtze River Economic Belt (YREB), spanning nine provinces and cities in eastern, central, and western China, is a key region for China’s urbanization. This study utilizes the Google Earth Engine (GEE) platform to integrate four land cover and impervious surface datasets, constructing built-up area datasets for the YREB at five-year intervals from 1985 to 2020. The employed random forest model achieved an overall accuracy (OA) and kappa coefficient both exceeding 90%, demonstrating high reliability and precision in the generated datasets. Using this dataset, we then calculated the United Nations Sustainable Development Goal 11.3.1 (SDG11.3.1) index for the YREB and its nine constituent provinces, which includes the land consumption rate (LCR), population growth rate (PGR), and ratio of land consumption rate to population growth rate (LCRPGR). The results show that the LCRPGR index for the entire region over the 35-year period is −0.006, 4.84, 0.44, 0.77, 5.15, 0.09, and 2.13, respectively. These values suggest that the land consumption rate significantly outpaced the population growth rate during 1990–1995, 2005–2010, and 2015–2020, reflecting periods of rapid urban development. This study offers important insights into urban expansion in the YREB, offering valuable data to inform sustainable urbanization practices.

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Published
2024-12-03
DOI
https://doi.org/10.3390/proceedings2024110011
Primary Topic
Land Use and Ecosystem Services
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article

Sustainable Urbanization in the Yangtze River Basin Through Built-Up Area Extraction

Zeshuo Li, Yan Jin, Haoyu Fan
Land Use and Ecosystem Services
article

Sustainable Urbanization in the Yangtze River Basin Through Built-Up Area Extraction

Zeshuo Li, Yan Jin, Haoyu Fan
article en

Abstract

The Yangtze River Economic Belt (YREB), spanning nine provinces and cities in eastern, central, and western China, is a key region for China’s urbanization. This study utilizes the Google Earth Engine (GEE) platform to integrate four land cover and impervious surface datasets, constructing built-up area datasets for the YREB at five-year intervals from 1985 to 2020. The employed random forest model achieved an overall accuracy (OA) and kappa coefficient both exceeding 90%, demonstrating high reliability and precision in the generated datasets. Using this dataset, we then calculated the United Nations Sustainable Development Goal 11.3.1 (SDG11.3.1) index for the YREB and its nine constituent provinces, which includes the land consumption rate (LCR), population growth rate (PGR), and ratio of land consumption rate to population growth rate (LCRPGR). The results show that the LCRPGR index for the entire region over the 35-year period is −0.006, 4.84, 0.44, 0.77, 5.15, 0.09, and 2.13, respectively. These values suggest that the land consumption rate significantly outpaced the population growth rate during 1990–1995, 2005–2010, and 2015–2020, reflecting periods of rapid urban development. This study offers important insights into urban expansion in the YREB, offering valuable data to inform sustainable urbanization practices.

Nanjing University of Posts and Telecommunications (CN), Nanjing Health and Health Commission (CN)
Sustainable cities and communities
Openalex Percentile: Top 81%
Land Use and Ecosystem Services
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Sustainable Urbanization in the Yangtze River Basin Through Built-Up Area Extraction — Zeshuo Li, Yan Jin, et al. · (2024) | TGRS Research Map | TGRS