Social functional mapping of urban green space using remote sensing and social sensing data

doi:10.1016/j.isprsjprs.2018.10.010

	Social functional mapping of urban green space using remote sensing and social sensing data
	Chen, Wei 1,2; Huang, Huiping 1; Dong, Jinwei 3; Zhang, Yuan 1; Tian, Yichen 1; Yang, Zhiqi 2,3
刊名	ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
	2018-12-01
卷号	146 页码:436-452
关键词	Remote sensing Social sensing Urban green space Social functional mapping
ISSN号	0924-2716
DOI	10.1016/j.isprsjprs.2018.10.010
通讯作者	Huang, Huiping(huanghp@radi.ac.cn)
英文摘要	Urban green space (UGS) is an indispensable component of urban environmental systems and is important to urban residents. Both physical features (e.g., shrubs, trees) and social functions (e.g., public parks, green buffers) are important in UGS mapping. Most UGS studies rely solely on remote sensing data to conduct UGS mapping of physical features, and few studies have focused on UGS mapping from a social function perspective. Due to the limitations of remote sensing in identifying social features; social sensing, which can reflect socioeconomic characteristics, is needed. As a result, a novel methodological framework for integrating these two different data sources to conduct the social functional mapping of UGS has been required. Consequently, we first extracted vegetation patches from an area in Beijing, via the Hyperplanes for Plant Extraction Methodology (HPEM) and considered the parcels segmented by the OpenStreetMap (OSM) road networks as the basic analytical units. Then, near-convex-hull analysis (NCHA) and text-concave-hull analysis (TCHA) were performed to integrate the multi-source data. The results show that the Level I and Level II (refer to Table 3) social function types of UGS had overall accuracies of 92.48% and 88.76%, respectively. Our study provides an improved understanding of UGS and can assist government departments in urban planning. It can also help researchers broaden their research scope by acting as a freely available data source for their work.
资助项目	National Key R&D Program of China[2017YFB0503800]
WOS关键词	LAND-USE ; SEMANTIC CLASSIFICATION ; ENVIRONMENTAL IMPACTS ; SPATIAL-DISTRIBUTION ; LIDAR DATA ; COVER ; VEGETATION ; LANDSCAPE ; AREAS ; CHINA
WOS研究方向	Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000453499400033
资助机构	National Key R&D Program of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/51303]
专题	中国科学院地理科学与资源研究所
通讯作者	Huang, Huiping
作者单位	1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Chen, Wei,Huang, Huiping,Dong, Jinwei,et al. Social functional mapping of urban green space using remote sensing and social sensing data[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2018,146:436-452.
APA	Chen, Wei,Huang, Huiping,Dong, Jinwei,Zhang, Yuan,Tian, Yichen,&Yang, Zhiqi.(2018).Social functional mapping of urban green space using remote sensing and social sensing data.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,146,436-452.
MLA	Chen, Wei,et al."Social functional mapping of urban green space using remote sensing and social sensing data".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 146(2018):436-452.