Urban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China.

Uncontrolled urban growth detracts from healthy urban development. Understanding urban development trends and predicting future urban spatial states is of great practical significance. In order to comprehensively analyze urbanization and its effect on vegetation cover, we extracted urban development...

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Autores principales:	Yanghua Zhang, Liang Zhao, Hu Zhao, Xiaofeng Gao
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b3ad20bfa4db4a6ebe3090b89a5b6fc2
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spelling	oai:doaj.org-article:b3ad20bfa4db4a6ebe3090b89a5b6fc22021-12-02T20:17:14ZUrban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China.1932-620310.1371/journal.pone.0257776https://doaj.org/article/b3ad20bfa4db4a6ebe3090b89a5b6fc22021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0257776https://doaj.org/toc/1932-6203Uncontrolled urban growth detracts from healthy urban development. Understanding urban development trends and predicting future urban spatial states is of great practical significance. In order to comprehensively analyze urbanization and its effect on vegetation cover, we extracted urban development trends from time series DMSP/OLS NTL and NDVI data from 2000 to 2015, using a linear model fitting method. Six urban development trend types were identified by clustering the linear model parameters. The identified trend types were found to accurately reflect the on-ground conditions and changes in the Jinan area. For example, a high-density, stable urban type was found in the city center while a stable dense vegetation type was found in the mountains to the south. The SLEUTH model was used for urban growth simulation under three scenarios built on the urban development analysis results. The simulation results project a gentle urban growth trend from 2015 to 2030, demonstrating the prospects for urban growth from the perspective of environmental protection and conservative urban development.Yanghua ZhangLiang ZhaoHu ZhaoXiaofeng GaoPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 10, p e0257776 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yanghua Zhang Liang Zhao Hu Zhao Xiaofeng Gao Urban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China.
description	Uncontrolled urban growth detracts from healthy urban development. Understanding urban development trends and predicting future urban spatial states is of great practical significance. In order to comprehensively analyze urbanization and its effect on vegetation cover, we extracted urban development trends from time series DMSP/OLS NTL and NDVI data from 2000 to 2015, using a linear model fitting method. Six urban development trend types were identified by clustering the linear model parameters. The identified trend types were found to accurately reflect the on-ground conditions and changes in the Jinan area. For example, a high-density, stable urban type was found in the city center while a stable dense vegetation type was found in the mountains to the south. The SLEUTH model was used for urban growth simulation under three scenarios built on the urban development analysis results. The simulation results project a gentle urban growth trend from 2015 to 2030, demonstrating the prospects for urban growth from the perspective of environmental protection and conservative urban development.
format	article
author	Yanghua Zhang Liang Zhao Hu Zhao Xiaofeng Gao
author_facet	Yanghua Zhang Liang Zhao Hu Zhao Xiaofeng Gao
author_sort	Yanghua Zhang
title	Urban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China.
title_short	Urban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China.
title_full	Urban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China.
title_fullStr	Urban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China.
title_full_unstemmed	Urban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China.
title_sort	urban development trend analysis and spatial simulation based on time series remote sensing data: a case study of jinan, china.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/b3ad20bfa4db4a6ebe3090b89a5b6fc2
work_keys_str_mv	AT yanghuazhang urbandevelopmenttrendanalysisandspatialsimulationbasedontimeseriesremotesensingdataacasestudyofjinanchina AT liangzhao urbandevelopmenttrendanalysisandspatialsimulationbasedontimeseriesremotesensingdataacasestudyofjinanchina AT huzhao urbandevelopmenttrendanalysisandspatialsimulationbasedontimeseriesremotesensingdataacasestudyofjinanchina AT xiaofenggao urbandevelopmenttrendanalysisandspatialsimulationbasedontimeseriesremotesensingdataacasestudyofjinanchina
_version_	1718374425804406784

Urban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China.

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