Time-Series Landsat Data for 3D Reconstruction of Urban History

Accurate quantification of vertical structure (or 3D structure) and its change of a city is essential for understanding the evolution of urban form, and its social and ecological consequences. Previous studies have largely focused on the horizontal structure (or 2D structure), but few on 3D structur...

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Autores principales:	Wenjuan Yu, Chuanbao Jing, Weiqi Zhou, Weimin Wang, Zhong Zheng
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	urban form vertical structure building height change detection building age spatiotemporal pattern Science Q
Acceso en línea:	https://doaj.org/article/9648784b81a74932a908f55128a26726
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id	oai:doaj.org-article:9648784b81a74932a908f55128a26726
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spelling	oai:doaj.org-article:9648784b81a74932a908f55128a267262021-11-11T18:54:19ZTime-Series Landsat Data for 3D Reconstruction of Urban History10.3390/rs132143392072-4292https://doaj.org/article/9648784b81a74932a908f55128a267262021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4339https://doaj.org/toc/2072-4292Accurate quantification of vertical structure (or 3D structure) and its change of a city is essential for understanding the evolution of urban form, and its social and ecological consequences. Previous studies have largely focused on the horizontal structure (or 2D structure), but few on 3D structure, especially for long time changes, due to the absence of such historical data. Here, we present a new approach for 3D reconstruction of urban history, which was applied to characterize the urban 3D structure and its change from 1986 to 2017 in Shenzhen, a megacity in southern China. This approach integrates the contemporary building height obtained from the increasingly available data of building footprint with building age estimated based on the long-term observations from time-series Landsat imagery. We found: (1) the overall accuracy for building change detection was 87.80%, and for the year of change was 77.40%, suggesting that the integrated approach provided an effective method to cooperate horizontal (i.e., building footprint), vertical (i.e., building height), and temporal information (i.e., building age) to generate the historical data for urban 3D reconstruction. (2) The number of buildings increased dramatically from 1986 to 2017, by eight times, with an increased proportion of high-rise buildings. (3) The old urban areas continued to have the highest density of buildings, with increased average height of buildings, but there were two emerging new centers clustered with high-rise buildings. The long-term urban 3D maps allowed characterizing the spatiotemporal patterns of the vertical dimension at the city level, which can enhance our understanding on urban morphology.Wenjuan YuChuanbao JingWeiqi ZhouWeimin WangZhong ZhengMDPI AGarticleurban formvertical structurebuilding heightchange detectionbuilding agespatiotemporal patternScienceQENRemote Sensing, Vol 13, Iss 4339, p 4339 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	urban form vertical structure building height change detection building age spatiotemporal pattern Science Q
spellingShingle	urban form vertical structure building height change detection building age spatiotemporal pattern Science Q Wenjuan Yu Chuanbao Jing Weiqi Zhou Weimin Wang Zhong Zheng Time-Series Landsat Data for 3D Reconstruction of Urban History
description	Accurate quantification of vertical structure (or 3D structure) and its change of a city is essential for understanding the evolution of urban form, and its social and ecological consequences. Previous studies have largely focused on the horizontal structure (or 2D structure), but few on 3D structure, especially for long time changes, due to the absence of such historical data. Here, we present a new approach for 3D reconstruction of urban history, which was applied to characterize the urban 3D structure and its change from 1986 to 2017 in Shenzhen, a megacity in southern China. This approach integrates the contemporary building height obtained from the increasingly available data of building footprint with building age estimated based on the long-term observations from time-series Landsat imagery. We found: (1) the overall accuracy for building change detection was 87.80%, and for the year of change was 77.40%, suggesting that the integrated approach provided an effective method to cooperate horizontal (i.e., building footprint), vertical (i.e., building height), and temporal information (i.e., building age) to generate the historical data for urban 3D reconstruction. (2) The number of buildings increased dramatically from 1986 to 2017, by eight times, with an increased proportion of high-rise buildings. (3) The old urban areas continued to have the highest density of buildings, with increased average height of buildings, but there were two emerging new centers clustered with high-rise buildings. The long-term urban 3D maps allowed characterizing the spatiotemporal patterns of the vertical dimension at the city level, which can enhance our understanding on urban morphology.
format	article
author	Wenjuan Yu Chuanbao Jing Weiqi Zhou Weimin Wang Zhong Zheng
author_facet	Wenjuan Yu Chuanbao Jing Weiqi Zhou Weimin Wang Zhong Zheng
author_sort	Wenjuan Yu
title	Time-Series Landsat Data for 3D Reconstruction of Urban History
title_short	Time-Series Landsat Data for 3D Reconstruction of Urban History
title_full	Time-Series Landsat Data for 3D Reconstruction of Urban History
title_fullStr	Time-Series Landsat Data for 3D Reconstruction of Urban History
title_full_unstemmed	Time-Series Landsat Data for 3D Reconstruction of Urban History
title_sort	time-series landsat data for 3d reconstruction of urban history
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/9648784b81a74932a908f55128a26726
work_keys_str_mv	AT wenjuanyu timeserieslandsatdatafor3dreconstructionofurbanhistory AT chuanbaojing timeserieslandsatdatafor3dreconstructionofurbanhistory AT weiqizhou timeserieslandsatdatafor3dreconstructionofurbanhistory AT weiminwang timeserieslandsatdatafor3dreconstructionofurbanhistory AT zhongzheng timeserieslandsatdatafor3dreconstructionofurbanhistory
_version_	1718431660167397376

Time-Series Landsat Data for 3D Reconstruction of Urban History

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