Analysis of urbanization dynamics in mainland China using pixel-based night-time light trajectories from 1992 to 2013. Issue 21 (2nd November 2017)
- Record Type:
- Journal Article
- Title:
- Analysis of urbanization dynamics in mainland China using pixel-based night-time light trajectories from 1992 to 2013. Issue 21 (2nd November 2017)
- Main Title:
- Analysis of urbanization dynamics in mainland China using pixel-based night-time light trajectories from 1992 to 2013
- Authors:
- Ju, Yang
Dronova, Iryna
Ma, Qin
Zhang, Xiang - Abstract:
- ABSTRACT: Understanding urbanization dynamics, or how intensity of urbanization changes over time, is an important basis for urban planning and management, which has been investigated using various data-driven approaches. Considering the advantages and constraints of different data sources, we use pixel-based, time-series night-time light (NTL) trajectories to characterize urbanization dynamics in mainland China where massive urban development has been occurring in recent decades. After pre-processing the data, we extracted time-series NTL trajectories for each 1 km × 1 km pixel between 1992 and 2013 and used the unsupervised k -means classification to identify the major typologies of these trajectories as urbanization dynamics based on their main statistical parameters. The classification identified five urbanization dynamics, namely, stable urban activity, high-level steady growth, acceleration, low-level steady growth, and fluctuation. Their distributions and spatial patterns were further summarized and compared among different Chinese administrative divisions. We specifically analysed the acceleration trajectories that showed rapid transitions from rural to urban, as we considered these trajectories as potential indicators for aggressive urbanization. We found several clusters at prefecture city and county levels with high proportion of the acceleration, and referred to the underlying socioeconomic characteristics and developmental history to understand how theseABSTRACT: Understanding urbanization dynamics, or how intensity of urbanization changes over time, is an important basis for urban planning and management, which has been investigated using various data-driven approaches. Considering the advantages and constraints of different data sources, we use pixel-based, time-series night-time light (NTL) trajectories to characterize urbanization dynamics in mainland China where massive urban development has been occurring in recent decades. After pre-processing the data, we extracted time-series NTL trajectories for each 1 km × 1 km pixel between 1992 and 2013 and used the unsupervised k -means classification to identify the major typologies of these trajectories as urbanization dynamics based on their main statistical parameters. The classification identified five urbanization dynamics, namely, stable urban activity, high-level steady growth, acceleration, low-level steady growth, and fluctuation. Their distributions and spatial patterns were further summarized and compared among different Chinese administrative divisions. We specifically analysed the acceleration trajectories that showed rapid transitions from rural to urban, as we considered these trajectories as potential indicators for aggressive urbanization. We found several clusters at prefecture city and county levels with high proportion of the acceleration, and referred to the underlying socioeconomic characteristics and developmental history to understand how these clusters could had been formed. Through this study, we revealed the dominant tendencies of urbanization in China over space and time, and developed an analysis framework that could be extended to other regions. … (more)
- Is Part Of:
- International journal of remote sensing. Volume 38:Issue 21(2017)
- Journal:
- International journal of remote sensing
- Issue:
- Volume 38:Issue 21(2017)
- Issue Display:
- Volume 38, Issue 21 (2017)
- Year:
- 2017
- Volume:
- 38
- Issue:
- 21
- Issue Sort Value:
- 2017-0038-0021-0000
- Page Start:
- 6047
- Page End:
- 6072
- Publication Date:
- 2017-11-02
- Subjects:
- Remote sensing -- Periodicals
Télédétection -- Périodiques
621.3678 - Journal URLs:
- http://www.tandfonline.com/toc/tres20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/01431161.2017.1302114 ↗
- Languages:
- English
- ISSNs:
- 0143-1161
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.528000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 5105.xml