Study on spatio-temporal modelling between NPP-VIIRS night-time light intensity and GDP for major urban agglomerations in China
文献类型：期刊论文
| 作者 | Li, Chang2; Huo, Zehua1,2; Wang, Xueyu2; Wu, Yijin2 |
| 刊名 | INTERNATIONAL JOURNAL OF REMOTE SENSING
 |
| 出版日期 | 2022-11-03 |
| 页码 | 24 |
| ISSN号 | 0143-1161 |
| 关键词 | Spatio-temporal modelling geographically and temporally weighted regression model (GTWR) night-time light intensity (NTLI) gross domestic product (GDP) NPP-VIIRS imagery |
| DOI | 10.1080/01431161.2022.2133580 |
| 通讯作者 | Li, Chang(lcshaka@126.com) |
| 英文摘要 | Currently, most of the studies establish the relationship between night-time light intensity (NTLI) and gross domestic product (GDP) only in the temporal dimension or spatial dimension, without combining both of them or considering real spatio-temporal modelling. Moreover, few studies verify the spatio-temporal heterogeneity of the model. To solve the aforementioned problems, this paper is the first to propose using the geographically and temporally weighted regression model (GTWR) for coupling NTLI and GDP. The NTLI derived from NPP-VIIRS satellites and GDP statistics for 14 urban agglomerations in China from 2013 to 2020 were systematically studied by comparing four methods, including OLS (ordinary least squares), GWR (geographically weighted regression model), TWR (time-weighted regression model), and GTWR. It is found that the GTWR model has the highest coefficient of determination. This finding proves that 'the spatio-temporal nature of material movement is inseparable from each other' and verifies the superiority, correctness, and scientific validity of the GTWR model. The implications of this paper include 1) demonstrating the superiority of the GTWR model (i.e. three-dimensional spatio-temporal model) in fitting the relationship between NTLI and GDP of urban agglomerations; 2) solving the problem of insufficient sample size of the single dimension of NPP-VIIRS through the spatio-temporal model; 3) quantitatively detecting the spatio-temporal heterogeneity of urban agglomerations and analysing the high non-stationarity urban agglomerations by GTWR and spatio-temporal cube with spatio-temporal hot spot analysis. |
| WOS关键词 | ELECTRIC-POWER CONSUMPTION ; WEIGHTED REGRESSION ; URBANIZATION ; DYNAMICS ; POPULATION ; IMAGERY ; SCALES ; GROWTH |
| 资助项目 | National Natural Science Foundation of China (NSFC)[41771493] ; National Natural Science Foundation of China (NSFC)[41101407] ; Fundamental Research Funds for the Central Universities[CCNU22QN019] |
| WOS研究方向 | Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | TAYLOR & FRANCIS LTD |
| WOS记录号 | WOS:000878555700001 |
| 资助机构 | National Natural Science Foundation of China (NSFC) ; Fundamental Research Funds for the Central Universities |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/186626]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Li, Chang |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 2.Cent China Normal Univ, Coll Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat, Wuhan, Hubei, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Chang,Huo, Zehua,Wang, Xueyu,et al. Study on spatio-temporal modelling between NPP-VIIRS night-time light intensity and GDP for major urban agglomerations in China[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2022:24. |
| APA | Li, Chang,Huo, Zehua,Wang, Xueyu,&Wu, Yijin.(2022).Study on spatio-temporal modelling between NPP-VIIRS night-time light intensity and GDP for major urban agglomerations in China.INTERNATIONAL JOURNAL OF REMOTE SENSING,24. |
| MLA | Li, Chang,et al."Study on spatio-temporal modelling between NPP-VIIRS night-time light intensity and GDP for major urban agglomerations in China".INTERNATIONAL JOURNAL OF REMOTE SENSING (2022):24. |
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。