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Social functional mapping of urban green space using remote sensing and social sensing data
Chen, Wei1,2; Huang, Huiping1; Dong, Jinwei3; Zhang, Yuan1; Tian, Yichen1; Yang, Zhiqi2,3
2018-12-01
Source PublicationISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
ISSN0924-2716
Volume146Pages:436-452
Corresponding AuthorHuang, Huiping(huanghp@radi.ac.cn)
AbstractUrban 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.
KeywordRemote sensing Social sensing Urban green space Social functional mapping
DOI10.1016/j.isprsjprs.2018.10.010
WOS KeywordLAND-USE ; SEMANTIC CLASSIFICATION ; ENVIRONMENTAL IMPACTS ; SPATIAL-DISTRIBUTION ; LIDAR DATA ; COVER ; VEGETATION ; LANDSCAPE ; AREAS ; CHINA
Indexed BySCI
Language英语
Funding ProjectNational Key R&D Program of China[2017YFB0503800]
Funding OrganizationNational Key R&D Program of China
WOS Research AreaPhysical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000453499400033
PublisherELSEVIER SCIENCE BV
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/51304
Collection中国科学院地理科学与资源研究所
Corresponding AuthorHuang, Huiping
Affiliation1.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
Recommended Citation
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.
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