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A time series of urban extent in China using DSMP/OLS nighttime light data

Urban extent data play an important role in urban management and urban studies, such as monitoring the process of urbanization and changes in the spatial configuration of urban areas. Traditional methods of extracting urban-extent information are primarily based on manual investigations and classifi...

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Autores principales: Yao, Yao, Chen, Dongsheng, Chen, Le, Wang, Huan, Guan, Qingfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993125/
https://www.ncbi.nlm.nih.gov/pubmed/29795685
http://dx.doi.org/10.1371/journal.pone.0198189
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author Yao, Yao
Chen, Dongsheng
Chen, Le
Wang, Huan
Guan, Qingfeng
author_facet Yao, Yao
Chen, Dongsheng
Chen, Le
Wang, Huan
Guan, Qingfeng
author_sort Yao, Yao
collection PubMed
description Urban extent data play an important role in urban management and urban studies, such as monitoring the process of urbanization and changes in the spatial configuration of urban areas. Traditional methods of extracting urban-extent information are primarily based on manual investigations and classifications using remote sensing images, and these methods have such problems as large costs in labor and time and low precision. This study proposes an improved, simplified and flexible method for extracting urban extents over multiple scales and the construction of spatiotemporal models using DMSP/OLS nighttime light (NTL) for practical situations. This method eliminates the regional temporal and spatial inconsistency of thresholding NTL in large-scale and multi-temporal scenes. Using this method, we have extracted the urban extents and calculated the corresponding areas on the county, municipal and provincial scales in China from 2000 to 2012. In addition, validation with the data of reference data shows that the overall accuracy (OA), Kappa and F1 Scores were 0.996, 0.793, and 0.782, respectively. We increased the spatial resolution of the urban extent to 500 m (approximately four times finer than the results of previous studies). Based on the urban extent dataset proposed above, we analyzed changes in urban extents over time and observed that urban sprawl has grown in all of the counties of China. We also identified three patterns of urban sprawl: Early Urban Growth, Constant Urban Growth and Recent Urban Growth. In addition, these trends of urban sprawl are consistent with the western, eastern and central cities of China, respectively, in terms of their spatial distribution, socioeconomic characteristics and historical background. Additionally, the urban extents display the spatial configurations of urban areas intuitively. The proposed urban extent dataset is available for download and can provide reference data and support for future studies of urbanization and urban planning.
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spelling pubmed-59931252018-06-17 A time series of urban extent in China using DSMP/OLS nighttime light data Yao, Yao Chen, Dongsheng Chen, Le Wang, Huan Guan, Qingfeng PLoS One Research Article Urban extent data play an important role in urban management and urban studies, such as monitoring the process of urbanization and changes in the spatial configuration of urban areas. Traditional methods of extracting urban-extent information are primarily based on manual investigations and classifications using remote sensing images, and these methods have such problems as large costs in labor and time and low precision. This study proposes an improved, simplified and flexible method for extracting urban extents over multiple scales and the construction of spatiotemporal models using DMSP/OLS nighttime light (NTL) for practical situations. This method eliminates the regional temporal and spatial inconsistency of thresholding NTL in large-scale and multi-temporal scenes. Using this method, we have extracted the urban extents and calculated the corresponding areas on the county, municipal and provincial scales in China from 2000 to 2012. In addition, validation with the data of reference data shows that the overall accuracy (OA), Kappa and F1 Scores were 0.996, 0.793, and 0.782, respectively. We increased the spatial resolution of the urban extent to 500 m (approximately four times finer than the results of previous studies). Based on the urban extent dataset proposed above, we analyzed changes in urban extents over time and observed that urban sprawl has grown in all of the counties of China. We also identified three patterns of urban sprawl: Early Urban Growth, Constant Urban Growth and Recent Urban Growth. In addition, these trends of urban sprawl are consistent with the western, eastern and central cities of China, respectively, in terms of their spatial distribution, socioeconomic characteristics and historical background. Additionally, the urban extents display the spatial configurations of urban areas intuitively. The proposed urban extent dataset is available for download and can provide reference data and support for future studies of urbanization and urban planning. Public Library of Science 2018-05-24 /pmc/articles/PMC5993125/ /pubmed/29795685 http://dx.doi.org/10.1371/journal.pone.0198189 Text en © 2018 Yao et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yao, Yao
Chen, Dongsheng
Chen, Le
Wang, Huan
Guan, Qingfeng
A time series of urban extent in China using DSMP/OLS nighttime light data
title A time series of urban extent in China using DSMP/OLS nighttime light data
title_full A time series of urban extent in China using DSMP/OLS nighttime light data
title_fullStr A time series of urban extent in China using DSMP/OLS nighttime light data
title_full_unstemmed A time series of urban extent in China using DSMP/OLS nighttime light data
title_short A time series of urban extent in China using DSMP/OLS nighttime light data
title_sort time series of urban extent in china using dsmp/ols nighttime light data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993125/
https://www.ncbi.nlm.nih.gov/pubmed/29795685
http://dx.doi.org/10.1371/journal.pone.0198189
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