Identifying Urban Functional Areas in China’s Changchun City from Sentinel-2 Images and Social Sensing Data

The urban functional area is critical to an understanding of the complex urban system, resource allocation, and management. However, due to urban surveys’ focus on geographic objects and the mixture of urban space, it is difficult to obtain such information. The function of a place is determined by...

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Autores principales:	Shouzhi Chang, Zongming Wang, Dehua Mao, Fusheng Liu, Lina Lai, Hao Yu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	urban functional areas mobile phone signaling data social sensing random forest Changchun Science Q
Acceso en línea:	https://doaj.org/article/9b1973c82a9e43acaf0d5bff9f9aa8fc
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spelling	oai:doaj.org-article:9b1973c82a9e43acaf0d5bff9f9aa8fc2021-11-25T18:53:51ZIdentifying Urban Functional Areas in China’s Changchun City from Sentinel-2 Images and Social Sensing Data10.3390/rs132245122072-4292https://doaj.org/article/9b1973c82a9e43acaf0d5bff9f9aa8fc2021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/22/4512https://doaj.org/toc/2072-4292The urban functional area is critical to an understanding of the complex urban system, resource allocation, and management. However, due to urban surveys’ focus on geographic objects and the mixture of urban space, it is difficult to obtain such information. The function of a place is determined by the activities that take place there. This study employed mobile phone signaling data to extract temporal features of human activities through discrete Fourier transform (DFT). Combined with the features extracted from the point of interest (POI) data and Sentinel images, the urban functional areas of Changchun City were identified using a random forest (RF) model. The results indicate that integrating features derived from remote sensing and social sensing data can effectively improve the identification accuracy and that features derived from dynamic mobile phone signaling have a higher identification accuracy than those derived from POI data. The human activity characteristics on weekends are more distinguishable for different functional areas than those on weekdays. The identified urban functional layout of Changchun is consistent with the actual situation. The residential functional area has the highest proportion, accounting for 33.51%, and is mainly distributed in the central area, while the industrial functional area and green-space are distributed around.Shouzhi ChangZongming WangDehua MaoFusheng LiuLina LaiHao YuMDPI AGarticleurban functional areasmobile phone signaling datasocial sensingrandom forestChangchunScienceQENRemote Sensing, Vol 13, Iss 4512, p 4512 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	urban functional areas mobile phone signaling data social sensing random forest Changchun Science Q
spellingShingle	urban functional areas mobile phone signaling data social sensing random forest Changchun Science Q Shouzhi Chang Zongming Wang Dehua Mao Fusheng Liu Lina Lai Hao Yu Identifying Urban Functional Areas in China’s Changchun City from Sentinel-2 Images and Social Sensing Data
description	The urban functional area is critical to an understanding of the complex urban system, resource allocation, and management. However, due to urban surveys’ focus on geographic objects and the mixture of urban space, it is difficult to obtain such information. The function of a place is determined by the activities that take place there. This study employed mobile phone signaling data to extract temporal features of human activities through discrete Fourier transform (DFT). Combined with the features extracted from the point of interest (POI) data and Sentinel images, the urban functional areas of Changchun City were identified using a random forest (RF) model. The results indicate that integrating features derived from remote sensing and social sensing data can effectively improve the identification accuracy and that features derived from dynamic mobile phone signaling have a higher identification accuracy than those derived from POI data. The human activity characteristics on weekends are more distinguishable for different functional areas than those on weekdays. The identified urban functional layout of Changchun is consistent with the actual situation. The residential functional area has the highest proportion, accounting for 33.51%, and is mainly distributed in the central area, while the industrial functional area and green-space are distributed around.
format	article
author	Shouzhi Chang Zongming Wang Dehua Mao Fusheng Liu Lina Lai Hao Yu
author_facet	Shouzhi Chang Zongming Wang Dehua Mao Fusheng Liu Lina Lai Hao Yu
author_sort	Shouzhi Chang
title	Identifying Urban Functional Areas in China’s Changchun City from Sentinel-2 Images and Social Sensing Data
title_short	Identifying Urban Functional Areas in China’s Changchun City from Sentinel-2 Images and Social Sensing Data
title_full	Identifying Urban Functional Areas in China’s Changchun City from Sentinel-2 Images and Social Sensing Data
title_fullStr	Identifying Urban Functional Areas in China’s Changchun City from Sentinel-2 Images and Social Sensing Data
title_full_unstemmed	Identifying Urban Functional Areas in China’s Changchun City from Sentinel-2 Images and Social Sensing Data
title_sort	identifying urban functional areas in china’s changchun city from sentinel-2 images and social sensing data
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/9b1973c82a9e43acaf0d5bff9f9aa8fc
work_keys_str_mv	AT shouzhichang identifyingurbanfunctionalareasinchinaschangchuncityfromsentinel2imagesandsocialsensingdata AT zongmingwang identifyingurbanfunctionalareasinchinaschangchuncityfromsentinel2imagesandsocialsensingdata AT dehuamao identifyingurbanfunctionalareasinchinaschangchuncityfromsentinel2imagesandsocialsensingdata AT fushengliu identifyingurbanfunctionalareasinchinaschangchuncityfromsentinel2imagesandsocialsensingdata AT linalai identifyingurbanfunctionalareasinchinaschangchuncityfromsentinel2imagesandsocialsensingdata AT haoyu identifyingurbanfunctionalareasinchinaschangchuncityfromsentinel2imagesandsocialsensingdata
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Identifying Urban Functional Areas in China’s Changchun City from Sentinel-2 Images and Social Sensing Data

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