干旱区生态环境知识资源中心(Arid): Combining night time lights in prediction of poverty incidence at the county level

Arid

DOI	10.1016/j.apgeog.2021.102552
	Combining night time lights in prediction of poverty incidence at the county level
	Xu, Jianbin; Song, Jie; Li, Baochao; Liu, Dan; Cao, Xiaoshu
通讯作者	Cao, XS (corresponding author), Shaanxi Normal Univ, Yunnan Guizhou Plateau Observat Stn Coupled Human, Xian 710119, Peoples R China.
来源期刊	APPLIED GEOGRAPHY
ISSN	0143-6228
EISSN	1873-7730
出版年	2021
卷号	135
英文摘要	Long-term poverty data can support accurate decision-making. This study demonstrates an accurate and reliable method for identifying poverty areas and predicting poverty incidence based on night time light remote-sensing data and machine learning methods. Using data of poverty counties and poverty incidence in Guizhou Province of China as the training dataset, we show how to use machine learning to identify poverty counties and predict poverty incidence in the Yunnan-Guangxi-Guizhou Rocky desertification area. The identification accuracy of poverty-stricken counties was 76.5%. The root mean squared error, mean absolute error, and R2 values of the poverty incidence rates were 5.01, 4.04, and 0.60, respectively. Using data from 2015 to verify the trained model, the R2 value of the predicted and actual values of poverty incidence reached 0.95. With the progress in machine learning and night light remote sensing, poverty mapping combined with night time lights and machine learning can compensate for the data gap in deprived areas and provide a decision-making basis for sustainable development in poverty-stricken areas.
英文关键词	Night time lights Machine learning Poverty estimate Long sequence Accuracy YGGRD
类型	Article
语种	英语
收录类别	SSCI
WOS记录号	WOS:000701946700006
WOS关键词	ELECTRIC-POWER CONSUMPTION ; DYNAMICS ; CHINA ; INTERCALIBRATION ; PATTERNS ; DMSP/OLS ; IMAGERY
WOS类目	Geography
WOS研究方向	Geography
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/362488
作者单位	[Xu, Jianbin] Shanxi Univ Finance & Econ, Coll Resources & Environm, Taiyuan 030006, Peoples R China; [Song, Jie; Li, Baochao; Liu, Dan] Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510275, Peoples R China; [Cao, Xiaoshu] Shaanxi Normal Univ, Shaanxi Normal Univ Acad Nat Resources & Territor, Xian 710119, Peoples R China; [Cao, Xiaoshu] Shaanxi Normal Univ, Yunnan Guizhou Plateau Observat Stn Coupled Human, Xian 710119, Peoples R China
推荐引用方式 GB/T 7714	Xu, Jianbin,Song, Jie,Li, Baochao,et al. Combining night time lights in prediction of poverty incidence at the county level[J],2021,135.
APA	Xu, Jianbin,Song, Jie,Li, Baochao,Liu, Dan,&Cao, Xiaoshu.(2021).Combining night time lights in prediction of poverty incidence at the county level.APPLIED GEOGRAPHY,135.
MLA	Xu, Jianbin,et al."Combining night time lights in prediction of poverty incidence at the county level".APPLIED GEOGRAPHY 135(2021).