气候变化领域集成服务门户(CCPortal): Mapping large-scale and fine-grained urban functional zones from VHR images using a multi-scale semantic segmentation network and object based approach

CCPortal

DOI	10.1016/j.rse.2021.112480
	Mapping large-scale and fine-grained urban functional zones from VHR images using a multi-scale semantic segmentation network and object based approach
	Du S.; Du S.; Liu B.; Zhang X.
发表日期	2021
ISSN	00344257
卷号	261
英文摘要	Urban functional zones (UFZs) are essential for characterizing both urban spatial configurations and socio-economic properties and monitoring urbanization process, thus UFZs are fundamental to urban planning, management and renewal. Although many efforts in remote sensing field have been made to map UFZs, large-scale and fine-grained UFZ maps required by a broad range of urban applications are still unavailable. Existing methods generally rely on pre-determined mapping units, such as image tiles and road blocks, which significantly limit the mapping quality and the automation degree of mapping UFZs. Given that UFZs are composed of diverse geographic objects, this study proposes a novel object-based UFZ mapping method using very-high-resolution (VHR) remote sensing images. First, a multi-scale semantic segmentation network that achieves pixel-wised predictions is proposed to predict urban-functions for geographic objects by capturing multi-scale contextual information. Afterwards, a conditional random field (CRF) framework is designed to regroup objects into UFZs to produce the final UFZ map, wherein road vectors are incorporated to restrict the procedure. The presented object-as-analysis-unit scheme conquers the drawbacks of mapping-unit pre-determination and the semantic segmentation model provides accurate function information for objects, thus they can be applied for producing large-scale and fine-grained UFZ maps. In the experiment, the proposed method is evaluated by producing UFZ maps for Beijing and Shanghai, China, and competitive results with overall accuracy of 91.6% and 89.1% are achieved, respectively. Finally, the generated UFZ maps are utilized to analyze the urban-function structures of the two cities. The proposed method can be regarded as a significant development that appears to be promising and practical for mapping UFZ maps for real-world urban applications. © 2021 Elsevier Inc.
英文关键词	CRF; Image semantic segmentation; Land use; OBIA; Urban functional zones; VHR images
语种	英语
scopus关键词	Economics; Image segmentation; Land use; Mapping; Maps; Random processes; Remote sensing; Roads and streets; Semantic Web; Fine grained; Functional zones; Image semantic segmentation; Large-scales; Multi-scales; OBIA; Random fields; Semantic segmentation; Urban functional zone; Very high resolution image; Semantics
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178814
作者单位	Institute of Remote Sensing and GIS, Peking University, Beijing, China; Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen, China
推荐引用方式 GB/T 7714	Du S.,Du S.,Liu B.,et al. Mapping large-scale and fine-grained urban functional zones from VHR images using a multi-scale semantic segmentation network and object based approach[J],2021,261.
APA	Du S.,Du S.,Liu B.,&Zhang X..(2021).Mapping large-scale and fine-grained urban functional zones from VHR images using a multi-scale semantic segmentation network and object based approach.Remote Sensing of Environment,261.
MLA	Du S.,et al."Mapping large-scale and fine-grained urban functional zones from VHR images using a multi-scale semantic segmentation network and object based approach".Remote Sensing of Environment 261(2021).