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Estimation of Landscape Pattern Changes in BRICS from 1992 to 2013 Using DMSP-OLS NTL Images
Fan, Junfu1; He, Huixin1; Hu, Taoying1; Zhang, Peng1; Yu, Xiao1; Zhou, Yuke2
2019-05-01
Source PublicationJOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
ISSN0255-660X
Volume47Issue:5Pages:725-735
Corresponding AuthorFan, Junfu(fanjf@sdut.edu.cn)
AbstractNighttime light data from the Defense Meteorological Satellite Program's Operational Linescan System are widely used for monitoring urbanization development. Brazil, Russia, India, China and South Africa (BRICS) countries have global economic and cultural influence in the new era. It was the first time for the researches about BRICS countries adopting nighttime light data to analyze the urbanization process. In this paper, we calibrated and extracted annual urbanized area patches from cities in BRICS based on a quadratic polynomial model. Nine landscape indexes were calculated to analyze urbanization process characteristics in BRICS. The results suggested that China and India both expanded more rapidly than other countries, with urban areas that increased by more than 100%. The expansion of large core cities was dominant in the urbanization of China, while emerging and expanding small urban patches were major forces in the urbanization of India. Since 1992, urbanization declined and urban areas shrunk in Russia, but core cities still maintained strength of urbanization. Due to economic recovery, urban areas near large cities in Russia began to expand. From 1992 to 2013, the urbanization process in South Africa developed slowly, as evidenced by time series fluctuations, but overall the development remained stable. The degree of urbanization in Brazil was greater than that in South Africa but less than that in Russia. Large-sized cities expanded slowly and small-sized cities clearly expanded in BRICS from 1992 to 2013.
KeywordBRICS DMSP-OLS Landscape pattern Nighttime lights Urbanization
DOI10.1007/s12524-019-00963-1
WOS KeywordSPATIAL-ANALYSIS ; CITY LIGHTS ; NIGHTTIME ; CHINA ; URBANIZATION ; GROWTH
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41501425] ; National Natural Science Foundation of China[41601478] ; National Natural Science Foundation of China[41471330] ; National Key Research and Development Program of China[2017YFB0503500] ; Project of Shandong Province Higher Educational Science and Technology Program[J16LH03] ; Shandong Provincial Natural Science Foundation, China[ZR2016DL02] ; Young Teacher Development Support Program of the Shandong University of Technology[4072-115016]
Funding OrganizationNational Natural Science Foundation of China ; National Key Research and Development Program of China ; Project of Shandong Province Higher Educational Science and Technology Program ; Shandong Provincial Natural Science Foundation, China ; Young Teacher Development Support Program of the Shandong University of Technology
WOS Research AreaEnvironmental Sciences & Ecology ; Remote Sensing
WOS SubjectEnvironmental Sciences ; Remote Sensing
WOS IDWOS:000466161200001
PublisherSPRINGER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/68611
Collection中国科学院地理科学与资源研究所
Corresponding AuthorFan, Junfu
Affiliation1.Shandong Univ Technol, Sch Civil & Architectural Engn, Zibo 255000, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Ecol Observing Network & Modeling Lab, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Fan, Junfu,He, Huixin,Hu, Taoying,et al. Estimation of Landscape Pattern Changes in BRICS from 1992 to 2013 Using DMSP-OLS NTL Images[J]. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING,2019,47(5):725-735.
APA Fan, Junfu,He, Huixin,Hu, Taoying,Zhang, Peng,Yu, Xiao,&Zhou, Yuke.(2019).Estimation of Landscape Pattern Changes in BRICS from 1992 to 2013 Using DMSP-OLS NTL Images.JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING,47(5),725-735.
MLA Fan, Junfu,et al."Estimation of Landscape Pattern Changes in BRICS from 1992 to 2013 Using DMSP-OLS NTL Images".JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING 47.5(2019):725-735.
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