Next Article in Journal
Enhancing Land Cover Mapping through Integration of Pixel-Based and Object-Based Classifications from Remotely Sensed Imagery
Previous Article in Journal
Ocean Dynamics Observed by VIIRS Day/Night Band Satellite Observations
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Remote Sens. 2018, 10(1), 47; https://doi.org/10.3390/rs10010047

Assessing Spatiotemporal Characteristics of Urbanization Dynamics in Southeast Asia Using Time Series of DMSP/OLS Nighttime Light Data

1,2,3
,
3,4,* , 1,2,3,4
,
1,2
,
5
and
3
1
School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
2
Collaborative Innovation Center of South China Sea Studies, Nanjing 210093, China
3
State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
4
Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing 210023, China
5
Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China
*
Author to whom correspondence should be addressed.
Received: 15 November 2017 / Revised: 20 December 2017 / Accepted: 26 December 2017 / Published: 8 January 2018
View Full-Text   |   Download PDF [11520 KB, uploaded 8 January 2018]   |  

Abstract

Intraregional spatial variations of satellite-derived anthropogenic nighttime light signals are gradually applied to identify different lighting areas with various socioeconomic activity and urbanization levels when characterizing urbanization dynamics. However, most previous partitioning approaches are carried out at local scales, easily leading to multi-standards of the extracted results from local areas, and this inevitably hinders the comparative analysis on the urbanization dynamics of the large region. Therefore, a partitioning approach considering the characteristics of nighttime light signals at both local and regional scales is necessary for studying spatiotemporal characteristics of urbanization dynamics across the large region using nighttime light imagery. Based on the quadratic relationships between the pixel-level nighttime light brightness and the corresponding spatial gradient for individual cities, we here proposed an improved partitioning approach to quickly identify different types of nighttime lighting areas for the entire region of Southeast Asia. Using the calibrated Defense Meteorological Satellite Program/Operational Line-scan System (DMSP/OLS) data with greater comparability, continuity, and intra-urban variability, the annual nighttime light imagery spanning years 1992–2013 were divided into four types of nighttime lighting areas: low, medium, high, and extremely high, associated with different intensity of anthropogenic activity. The results suggest that Southeast Asia has experienced a rapid and diverse urbanization process from 1992 to 2013. Areas with moderate or low anthropogenic activity show a faster growth rate for the spatial expansion than the developed areas with intense anthropogenic activity. Transitions between different nighttime lighting types potentially depict the trajectory of urban development, the darker areas are gradually transitioning to areas with higher lighting, indicating conspicuous trends of gradually intensified anthropogenic activity from central areas to periphery areas, and from megacities to small cities. Additionally, satellite-derived nighttime lighting areas are in good agreement with the radar-derived human settlements, with dense human settlements in extremely high and high nighttime lighting areas, while sparse human settlements in low nighttime lighting areas. View Full-Text
Keywords: nighttime light; urbanization; nighttime lighting types; Southeast Asia nighttime light; urbanization; nighttime lighting types; Southeast Asia
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Zhao, M.; Cheng, W.; Zhou, C.; Li, M.; Huang, K.; Wang, N. Assessing Spatiotemporal Characteristics of Urbanization Dynamics in Southeast Asia Using Time Series of DMSP/OLS Nighttime Light Data. Remote Sens. 2018, 10, 47.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top