Remote Sensing, Vol. 12, Pages 2615: Exploring Annual Urban Expansions in the Guangdong-Hong Kong-Macau Greater Bay Area: Spatiotemporal Features and Driving Factors in 1986–2017

Remote Sensing, Vol. 12, Pages 2615: Exploring Annual Urban Expansions in the Guangdong-Hong Kong-Macau Greater Bay Area: Spatiotemporal Features and Driving Factors in 1986–2017

Remote Sensing doi: 10.3390/rs12162615

Authors:
Jie Zhang
Le Yu
Xuecao Li
Chenchen Zhang
Tiezhu Shi
Xiangyin Wu
Chao Yang
Wenxiu Gao
Qingquan Li
Guofeng Wu

The Guangdong–Hong Kong–Macau Greater Bay Area (GBA) of China is one of the largest bay areas in the world. However, the spatiotemporal characteristics and driving mechanisms of urban expansions in this region are poorly understood. Here we used the annual remote sensing images, Geographic Information System (GIS) techniques, and geographical detector method to characterize the spatiotemporal patterns of urban expansion in the GBA and investigate their driving factors during 1986–2017 on regional and city scales. The results showed that: the GBA experienced an unprecedented urban expansion over the past 32 years. The total urban area expanded from 652.74 km2 to 8137.09 km2 from 1986 to 2017 (approximately 13 times). The annual growth rate during 1986–2017 was 8.20% and the annual growth rate from 1986 to 1990 was the highest (16.89%). Guangzhou, Foshan, Dongguan, and Shenzhen experienced the highest urban expansion rate, with the annual increase of urban areas in 51.51, 45.54, 36.76, and 23.26 km2 y−1, respectively, during 1986–2017. Gross Domestic Product (GDP), income, road length, and population were the most important driving factors of the urban expansions in the GBA. We also found the driving factors of the urban expansions varied with spatial and temporal scales, suggesting the general understanding from the regional level may not reveal detailed urban dynamics. Detailed urban management and planning policies should be made considering the spatial and internal heterogeneity. These findings can enhance the comprehensive understanding of this bay area and help policymakers to promote sustainable development in the future.

This information was first published on https://www.mdpi.com/2072-4292/12/16/2615