Evaluating Urban Community Sustainability by Integrating Housing, Ecosystem Services, and Landscape Configuration

doi:10.1155/2020/3460962

	Evaluating Urban Community Sustainability by Integrating Housing, Ecosystem Services, and Landscape Configuration
	Zhou, Liang 1,2; Mu, Haowei 1,3; Wang, Bao 4; Yuan, Bo 1,3; Dang, Xuewei 1,5
刊名	COMPLEXITY
	2020-08-27
卷号	2020 页码:14
ISSN号	1076-2787
DOI	10.1155/2020/3460962
通讯作者	Mu, Haowei(0218742@stu.lzjtu.edu.cn) ; Yuan, Bo(0219795@stu.lzjtu.edu.cn)
英文摘要	Community is the core spatial unit for evaluating sustainable development. However, single data and method seem inadequate for conducting a scientific, effective, and innovative sustainable evaluation of complex community units. In this study, we perform a sustainable-oriented land use scheme using multisource remote sensing, machine learning, and object-based postclassification refinement. Furthermore, we assess the sustainability of the traffic community by data-driven and combined housing, ecosystem services, and landscape configuration. The results indicated that (1) the relationship between housing, ecosystem services, and landscape pattern has obvious synergistic effects, although with dissimilar importance in different sustainability levels. High sustainability level is intensely coordinated with landscape configuration, medium sustainability level is more affected by ecosystem services, and low sustainability level is more related to housing. (2) Community sustainability presents a significant spatial distribution. The communities of high sustainability level are mainly located in both sides of the Pearl River and emerging urban areas, while those of medium sustainability level are distributed sporadically in the study area and those of low sustainability level are concentrated in old towns. (3) Community transformation cannot be accomplished at one step. Along with the continuous optimization of landscape configuration, the priority should be given to housing reconstruction and improvement of ecosystem services further. We provide scientific and effective data-based evidence for urban decision-makers by integrating the advantages of the Earth Observation System and multifactor analysis.
资助项目	Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19040502] ; National Natural Science Foundation of China[41701173] ; National Natural Science Foundation of China[41961027] ; Science Foundation for the Excellent Youth Scholars of Ministry of Education of China[17YJCZH268] ; LZJTU EP[201806]
WOS关键词	TRADE-OFFS ; LAND-COVER ; INDICATORS ; GREEN ; FUTURE ; CHINA ; URBANIZATION ; CHALLENGES ; GUANGZHOU ; SCIENCE
WOS研究方向	Mathematics ; Science & Technology - Other Topics
语种	英语
出版者	WILEY-HINDAWI
WOS记录号	WOS:000570884700005
资助机构	Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; Science Foundation for the Excellent Youth Scholars of Ministry of Education of China ; LZJTU EP
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/156945]
专题	中国科学院地理科学与资源研究所
通讯作者	Mu, Haowei; Yuan, Bo
作者单位	1.Lanzhou Jiaotong Univ, Fac Geomat, Lanzhou 730070, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 3.Natl Local Joint Engn Res Ctr Technol & Applicat, Lanzhou 730070, Peoples R China 4.Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Lanzhou 730000, Peoples R China 5.Gansu Prov Engn Lab Natl Geog State Monitoring, Lanzhou 730070, Peoples R China
推荐引用方式 GB/T 7714	Zhou, Liang,Mu, Haowei,Wang, Bao,et al. Evaluating Urban Community Sustainability by Integrating Housing, Ecosystem Services, and Landscape Configuration[J]. COMPLEXITY,2020,2020:14.
APA	Zhou, Liang,Mu, Haowei,Wang, Bao,Yuan, Bo,&Dang, Xuewei.(2020).Evaluating Urban Community Sustainability by Integrating Housing, Ecosystem Services, and Landscape Configuration.COMPLEXITY,2020,14.
MLA	Zhou, Liang,et al."Evaluating Urban Community Sustainability by Integrating Housing, Ecosystem Services, and Landscape Configuration".COMPLEXITY 2020(2020):14.