Detecting the 20 year city-size dynamics in China with a rank clock approach and DMSP/OLS nighttime data

Huang, Qingxu; He, Chunyang; Gao, Bin; Yang, Yang; Liu, Zhifeng; Zhao, Yuanyuan; Dou, Yue

doi:10.1016/j.landurbplan.2015.01.004

Cited by 68 publications

(48 citation statements)

References 77 publications

(151 reference statements)

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“…Secondly, Landsat TM/OLI-TIRS images were employed to validate the spatial accuracy of urban areas. Considering Landsat TM/OLI-TIRS images have much higher spatial resolution (30 m) than the NSL data (1 km), they are efficient to represent the real pattern of urban areas [20,30,38,39]. The urban areas extracted from Landsat TM/OLI-TIRS images were produced by the maximum likelihood classifiers based on training data extracted from typical urban areas.…”

Section: Extracting Urban Expansionmentioning

confidence: 99%

Urban Expansion and Agricultural Land Loss in China: A Multiscale Perspective

et al. 2016

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China's rapid urbanization has contributed to a massive agricultural land loss that could threaten its food security. Timely and accurate mapping of urban expansion and urbanization-related agricultural land loss can provide viable measures to be taken for urban planning and agricultural land protection. In this study, urban expansion in China from 2001 to 2013 was mapped using the nighttime stable light (NSL), normalized difference vegetation index (NDVI), and water body data. Urbanization-related agricultural land loss during this time period was then evaluated at national, regional, and metropolitan scales by integrating multiple sources of geographic data. The results revealed that China's total urban area increased from 31,076 km 2 in 2001 to 80,887 km 2 in 2013, with an average annual growth rate of 13.36%. This widespread urban expansion consumed 33,080 km 2 of agricultural land during this period. At a regional scale, the eastern region lost 18,542 km 2 or 1.2% of its total agricultural land area. At a metropolitan scale, the Shanghai-Nanjing-Hangzhou (SNH) and Pearl River Delta (PRD) areas underwent high levels of agricultural land loss with a decrease of 6.12% (4728 km 2 ) and 6.05% (2702 km 2 ) of their total agricultural land areas, respectively. Special attention should be paid to the PRD, with a decline of 13.30% (1843 km 2 ) of its cropland. Effective policies and strategies should be implemented to mitigate urbanization-related agricultural land loss in the context of China's rapid urbanization.

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Section: Extracting Urban Expansionmentioning

confidence: 99%

Urban Expansion and Agricultural Land Loss in China: A Multiscale Perspective

et al. 2016

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“…Night light remote sensing has been widely used in many fields including socioeconomic parameter estimation [34][35][36], urbanization evaluation [37,38], fishing boat mapping [39], land cover mapping [40][41][42][43], and humanitarian disaster evaluation [44][45][46]. This technique provides an opportunity to map spatial distribution of GDP [47,48], energy consumption [49,50], and public services [51,52].…”

Section: Introductionmentioning

confidence: 99%

“…They found that the ULI has increased during 1992-2010, and the urbanization is most significant during 2004-2010 [54]. Huang and his colleagues made use of night light images to evaluate city size and rank in China during 1992-2008, they found that the distribution of city sizes became more even during the period and the greatest change in city size distribution occurred during 2000-2003 [42]. Tan investigated the spatial pattern of China's urbanization during 1992-2010 using night light images.…”

Section: Introductionmentioning

confidence: 99%

Multi-Scale Measurement of Regional Inequality in Mainland China during 2005–2010 Using DMSP/OLS Night Light Imagery and Population Density Grid Data

Yang

et al. 2015

Sustainability

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This study used the Night Light Development Index (NLDI) to measure the regional inequality of public services in Mainland China at multiple scales. The NLDI was extracted based on a Gini Coefficient approach to measure the spatial differences of population distribution and night light distribution. Population data were derived from the dataset of China's population density grid, and night light data were acquired from satellite imagery. In the multi-scale analysis, we calculated the NLDI for China as a whole, eight 13470The same pattern was observed from the provincial and prefectural analysis, suggesting that public services in Mainland China became more equal within the five-year period. A regression analysis indicated that provincial and prefectural regions with more public services per capita and higher population density had more equal public services.

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“…Li derived a time series vegetation adjusted NTL urban index (VANUI) from DMSP/OLS data and analyzed urban dynamics of the southeastern United States for 1992 to 2013 [42]. Gao [43] and Huang [44] used NTL data for 1992 to 2015 and compared common characteristics and distinctive features of city-size distributions of three urban agglomerations (Beijing-Tianjin-Hebei, the Yangtze River Delta, and the Pearl River Delta) via Pareto regression and rank clock methods. Zou detected urban changes from DMSP/OLS data for 1992 to 2011 and evaluated urban expansion intensity and landscape metrics of the middle reaches of the Yangtze River (MRYR) in China [45].…”

Section: Introductionmentioning

confidence: 99%

Expansion Analysis of Yangtze River Delta Urban Agglomeration Using DMSP/OLS Nighttime Light Imagery for 1993 to 2012

Zhang

Sun

et al. 2018

IJGI

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Abstract:Investigating the characteristics of urban expansion is helpful in managing the relationship between urbanization and the ecological and environmental issues related to sustainable development. The Defense Meteorological Satellite Program/Operational Line-scan System (DMSP/OLS) collects visible and near-infrared light from the Earth's surface at night without moonlight. It generates effective time series data for mapping the dynamics of urban expansion. As a major urban agglomeration in the world, the Yangtze River Delta Urban Agglomeration (YRDUA) is an important intersection zone of both the "Belt and Road Initiative" and the "Yangtze River Economic Belt" in China. Therefore, this paper analyses urban expansion characteristics of the YRDUA for 1993-2012 from urban extents extracted from the DMSP/OLS for 1993, 1997, 2002, 2007, and 2012. First, calibration procedures are applied to DMSP/OLS data, including intercalibration, intra-annual composition, and inter-annual series correction procedures. Spatial extents are then extracted from the corrected DMSP/OLS data, and a threshold is determined via the spatial comparison method. Finally, three models are used to explore urban expansion characteristics of the YRDUA from expansion rates, expansion spatial patterns, and expansion evaluations. The results show that the urban expansion of the YRDUA occurred at an increasing rate from 1993-2007 and then declined after 2007 with the onset of the global financial crisis. The Suxichang and Ningbo metropolitan circles were seriously affected by the financial crisis, while the Hefei metropolitan circle was not. The urban expansion of the YRDUA moved from the northeast to the southwest over the 20-year period. Urban expansion involved internal infilling over the first 15 years and then evolved into external sprawl and suburbanization after 2007.

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Detecting the 20 year city-size dynamics in China with a rank clock approach and DMSP/OLS nighttime data

Cited by 68 publications

References 77 publications

Urban Expansion and Agricultural Land Loss in China: A Multiscale Perspective

Urban Expansion and Agricultural Land Loss in China: A Multiscale Perspective

Multi-Scale Measurement of Regional Inequality in Mainland China during 2005–2010 Using DMSP/OLS Night Light Imagery and Population Density Grid Data

Expansion Analysis of Yangtze River Delta Urban Agglomeration Using DMSP/OLS Nighttime Light Imagery for 1993 to 2012

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