中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 地理科学与资源研究所
  3. 中国科学院地理科学与资源研究所
Research on the Spatio-Temporal Dynamic Evolution Characteristics and Influencing Factors of Electrical Power Consumption in Three Urban Agglomerations of Yangtze River Economic Belt, China Based on DMSP/OLS Night Light Data

文献类型：期刊论文

作者Zhong, Yang1,2; Lin, Aiwen1,2; Xiao, Chiwei3; Zhou, Zhigao1,2
刊名REMOTE SENSING
出版日期2021-03-01
卷号13期号:6页码:33
关键词YREB three urban agglomerations DMSP OLS night light data EPC spatiotemporal dynamics Geographically weighted regression (GWR) model random forest algorithm
DOI10.3390/rs13061150
通讯作者Lin, Aiwen(awlin@whu.edu.cn)
英文摘要In this paper, based on electrical power consumption (EPC) data extracted from DMSP/OLS night light data, we select three national-level urban agglomerations in China's Yangtze River Economic Belt(YREB), includes Yangtze River Delta urban agglomerations(YRDUA), urban agglomeration in the middle reaches of the Yangtze River(UAMRYR), and Chengdu-Chongqing urban agglomeration(CCUA) as the research objects. In addition, the coefficient of variation (CV), kernel density analysis, cold hot spot analysis, trend analysis, standard deviation ellipse and Moran's I Index were used to analyze the Spatio-temporal Dynamic Evolution Characteristics of EPC in the three urban agglomerations of the YREB. In addition, we also use geographically weighted regression (GWR) model and random forest algorithm to analyze the influencing factors of EPC in the three major urban agglomerations in YREB. The results of this study show that from 1992 to 2013, the CV of the EPC in the three urban agglomerations of YREB has been declining at the overall level. At the same time, the highest EPC value is in YRDUA, followed by UAMRYR and CCUA. In addition, with the increase of time, the high-value areas of EPC hot spots are basically distributed in YRDUA. The standard deviation ellipses of the EPC of the three urban agglomerations of YREB clearly show the characteristics of "east-west" spatial distribution. With the increase of time, the correlations and the agglomeration of the EPC in the three urban agglomerations of the YREB were both become more and more obvious. In terms of influencing factor analysis, by using GWR model, we found that the five influencing factors we selected basically have a positive impact on the EPC of the YREB. By using the Random forest algorithm, we found that the three main influencing factors of EPC in the three major urban agglomerations in the YREB are the proportion of secondary industry in GDP, Per capita disposable income of urban residents, and Urbanization rate.
WOS关键词PATTERNS ; EMISSIONS ; GROWTH
资助项目National Social Science Foundation of China[18ZDA040]
WOS研究方向Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000651980600001
出版者MDPI
资助机构National Social Science Foundation of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/162845]  
专题中国科学院地理科学与资源研究所
通讯作者Lin, Aiwen
作者单位1.Wuhan Univ, Sch Resources & Environm Sci, Wuhan 430079, Peoples R China
2.Wuhan Univ, Key Lab Geog Informat Syst, Wuhan 430079, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714		 Zhong, Yang,Lin, Aiwen,Xiao, Chiwei,et al. Research on the Spatio-Temporal Dynamic Evolution Characteristics and Influencing Factors of Electrical Power Consumption in Three Urban Agglomerations of Yangtze River Economic Belt, China Based on DMSP/OLS Night Light Data[J]. REMOTE SENSING,2021,13(6):33.
APA Zhong, Yang,Lin, Aiwen,Xiao, Chiwei,&Zhou, Zhigao.(2021).Research on the Spatio-Temporal Dynamic Evolution Characteristics and Influencing Factors of Electrical Power Consumption in Three Urban Agglomerations of Yangtze River Economic Belt, China Based on DMSP/OLS Night Light Data.REMOTE SENSING,13(6),33.
MLA Zhong, Yang,et al."Research on the Spatio-Temporal Dynamic Evolution Characteristics and Influencing Factors of Electrical Power Consumption in Three Urban Agglomerations of Yangtze River Economic Belt, China Based on DMSP/OLS Night Light Data".REMOTE SENSING 13.6(2021):33.

入库方式： OAI收割

来源：地理科学与资源研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。