2013
DOI: 10.1016/j.jag.2011.12.012
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Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data

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Cited by 188 publications
(103 citation statements)
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“…The focus of these studies includes: (1) the extent and speed of urban expansion [11,12]; (2) landscape pattern and changes along the resultant urban-rural gradients, frequently quantified by landscape metrics [13,14]; and (3) the morphology of urban expansion, such as urban sprawl versus compactness [15], models of urban expansion [16]. Recognizing the importance of urban morphology for environmental and ecological issues [17,18], there is an increasing interest in quantifying the models of urban expansion [17,[19][20][21]. The BTH encompasses approximately 215,800 km 2 , with a total population of 110.53 million in 2014 (approximately 8.08% of the total population of China), and the gross domestic product (GDP) of 6647.90 billion Yuan, accounted for 10.45% of the GDP in China (National Bureau of Statistics of the People's Republic of China, 2014).…”
Section: Introductionmentioning
confidence: 99%
“…The focus of these studies includes: (1) the extent and speed of urban expansion [11,12]; (2) landscape pattern and changes along the resultant urban-rural gradients, frequently quantified by landscape metrics [13,14]; and (3) the morphology of urban expansion, such as urban sprawl versus compactness [15], models of urban expansion [16]. Recognizing the importance of urban morphology for environmental and ecological issues [17,18], there is an increasing interest in quantifying the models of urban expansion [17,[19][20][21]. The BTH encompasses approximately 215,800 km 2 , with a total population of 110.53 million in 2014 (approximately 8.08% of the total population of China), and the gross domestic product (GDP) of 6647.90 billion Yuan, accounted for 10.45% of the GDP in China (National Bureau of Statistics of the People's Republic of China, 2014).…”
Section: Introductionmentioning
confidence: 99%
“…Urbanization has been an important social and economic phenomenon taking place at an unprecedented scale and rate all over the world [1]. In addition, it is forecast that approximately 4.9 billion people are expected to settle down in urban areas by 2030 and 6.3 billion by 2050 [2].…”
Section: Introductionmentioning
confidence: 99%
“…This study aims to explore the trends and patterns of urban expansion in the MYRB urban agglomeration over past 16 years from the regional landscape to prefectural and inner-city levels using multi-temporal MODIS products and Landsat data integrated with GIS techniques and landscape ecology approaches. The specific objectives of this study comprise: (1) dynamically map the locations and extents of main urban area expansions; (2) analyze the similarities and differences of the general trends of urbanization, spatially explicit urban growth patterns, and spatiotemporal changes of landscape metrics; and (3) reveal spatiotemporal inequality of the socioeconomic development among the cities in the MYRB. Furthermore, the results of this study also offer a scientific decision-making platform for achieving the goals of macroeconomic regulation and control, town planning, land management for governmental eco-environmental protection and promoting healthy urbanization in the MYRB region.…”
Section: Introductionmentioning
confidence: 99%
“…Compared with U.S. and European cities, most cities in China have been identified to have undergone land-dominated urbanization. Urban expansion and urban sprawl have been discerned at the city level such as Beijing, Shanghai, Guangzhou and Wuhan, at the regional level such as Pearl River delta, Yangzi river delta, or even at the national and global level though Remote Sensing (RS) and Geographical Information System (GIS) techniques (Han, Hayashi, Cao, & Imura, 2009;Kuang, 2011;Sun, Wu, Lv, Yao, & Wei, 2013). Furthermore, the discovery of spatial dependence in the traditional statistical calculation and the widely present spatial correlation in regional science reflect the need for incorporating spatial effect into the operational model.…”
Section: Introductionmentioning
confidence: 99%