Detecting global urban expansion over the last three decades using a fully convolutional network

doi:10.1088/1748-9326/aaf936

GSTDTAP > 气候变化

DOI	10.1088/1748-9326/aaf936
	Detecting global urban expansion over the last three decades using a fully convolutional network
	He, Chunyang 1,2; Liu, Zhifeng 1,2; Gou, Siyuan 1,2; Zhang, Qiaofeng 3; Zhang, Jinshui 4,5,6; Xu, Linlin 7
	2019-03-01
发表期刊	ENVIRONMENTAL RESEARCH LETTERS
ISSN	1748-9326
出版年	2019
卷号	14 期号:3
文章类型	Article
语种	英语
国家	Peoples R China; USA
英文摘要	The effective detection of global urban expansion is the basis of understanding urban sustainability. We propose a fully convolutional network (FCN) and employ it to detect global urban expansion from 1992-2016. We found that the global urban land area increased from 274.7 thousand km(2)-621.1 thousand km(2), which is an increase of 346.4 thousand km(2) and a growth by 1.3 times. The results display a relatively high accuracy with an average kappa index of 0.5, which is 0.3 higher than those of existing global urban expansion datasets. Three major advantages of the proposed FCN contribute to the improved accuracy, including the integration ofmulti-source remotely sensed data, the combination of features at multiple scales, and the ability to address the lack of training samples for historical urban land. Thus, the proposed FCN has great potential to effectively detect global urban expansion.
英文关键词	fully convolutional network global urban expansion deep learning nighttime light data vegetation index land surface temperature
领域	气候变化
收录类别	SCI-E
WOS记录号	WOS:000460971000002
WOS关键词	LAND ; AREAS ; URBANIZATION ; BIODIVERSITY ; DYNAMICS ; ECOLOGY ; IMAGES ; SCALE
WOS类目	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/36485
专题	气候变化
作者单位	1.Beijing Normal Univ, Fac Geog Sci, CHESS, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China; 2.Beijing Normal Univ, Sch Nat Resources, Fac Geog Sci, Beijing 100875, Peoples R China; 3.Murray State Univ, Dept Geosci, Murray, KY 42071 USA; 4.Beijing Normal Univ, ESPRE, Beijing 100875, Peoples R China; 5.Beijing Normal Univ, Fac Geog Sci, Beijing Engn Res Ctr Global Land Remote Sensing P, Beijing 100875, Peoples R China; 6.Beijing Normal Univ, Fac Geog Sci, Inst Remote Sensing Sci & Engn, Beijing 100875, Peoples R China; 7.China Univ Geosci, Sch Land Sci & Technol, Beijing 100083, Peoples R China
推荐引用方式 GB/T 7714	He, Chunyang,Liu, Zhifeng,Gou, Siyuan,et al. Detecting global urban expansion over the last three decades using a fully convolutional network[J]. ENVIRONMENTAL RESEARCH LETTERS,2019,14(3).
APA	He, Chunyang,Liu, Zhifeng,Gou, Siyuan,Zhang, Qiaofeng,Zhang, Jinshui,&Xu, Linlin.(2019).Detecting global urban expansion over the last three decades using a fully convolutional network.ENVIRONMENTAL RESEARCH LETTERS,14(3).
MLA	He, Chunyang,et al."Detecting global urban expansion over the last three decades using a fully convolutional network".ENVIRONMENTAL RESEARCH LETTERS 14.3(2019).