4.7 Article

An improved nightlight threshold method for revealing the spatiotemporal dynamics and driving forces of urban expansion in China

期刊

JOURNAL OF ENVIRONMENTAL MANAGEMENT
卷 289, 期 -, 页码 -

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2021.112574

关键词

Nighttime light; Dynamic threshold; Urban extraction; Driving forces; China

资金

  1. National Key R&D Program of China [2017YFC0505703]
  2. National Natural Science Foundation of China [41401638, 41801314]
  3. Shanghai Committee of Science and Technology Fund [19DZ1203303]
  4. Shanghai Philosophy and Social Sciences Planning Project [2020BCK009]
  5. Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration
  6. Fundamental Research Funds for the Central Universities [SHUES2020C01]
  7. Institute of Belt and Road & Global Development Project [ECNU-BRGD201803]
  8. China Scholarship Council [201706140147]

向作者/读者索取更多资源

The study introduces an improved dynamic nightlight threshold method combined with urban population data to determine urban mapping yearly continued and city-class-wide threshold, proving to be more accurate than traditional NTL threshold method. China's urban area has more than quadrupled from 25.2 thousand km2 in 1992 to 108.2 thousand km2 in 2013, showing significant growth rates.
An accurate and efficient extraction of urban extent is important for understanding the dynamics of urban expansion process and for sustainable planning and management of cities. We proposed an improved dynamic nightlight threshold method to model urban extent and to reveal the spatiotemporal dynamics and driving forces of urban expansion. Differing from previous studies, we correct the blooming and over-saturation problems of nighttime light (NTL), and highlight a combination of NTL with urban population data for determining a yearlycontinued and city-class-wide threshold for urban mapping. China is selected as a case study area to test the improved method and to gain insights to its urban expansion process. Through the validation, our method has been proven to be more accurate than the traditional NTL threshold method. Accordingly, the yearly-continued NTL data can better describe the changing patterns and driving forces of urban expansion than the yearlydiscontinued land use and land cover data do. It is found that the total urban area in China has more than quadrupled from 25.2 in 1992 to 108.2 thousand km2 in 2013. Some significant pulses of urban expansion have been detected in our study, which may be attributed to the policy and socioeconomic impacts. Moreover, the panel regression based on annual NTL data indicates that GDP is a more important driver of urban expansion than urban population.

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