干旱区生态环境知识资源中心(Arid): High-resolution rural poverty mapping in Pakistan with ensemble deep learning

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DOI	10.1371/journal.pone.0283938
	High-resolution rural poverty mapping in Pakistan with ensemble deep learning
	Agyemang, Felix S. K.; Memon, Rashid; Wolf, Levi John; Fox, Sean
通讯作者	Agyemang, FSK
来源期刊	PLOS ONE
ISSN	1932-6203
出版年	2023
卷号	18 期号:4
英文摘要	High resolution poverty mapping supports evidence-based policy and research, yet about half of all countries lack the survey data needed to generate useful poverty maps. To overcome this challenge, new non-traditional data sources and deep learning techniques are increasingly used to create small-area estimates of poverty in low- and middle-income countries (LMICs). Convolutional Neural Networks (CNN) trained on satellite imagery are emerging as one of the most popular and effective approaches. However, the spatial resolution of poverty estimates has remained relatively coarse, particularly in rural areas. To address this problem, we use a transfer learning approach to train three CNN models and use them in an ensemble to predict chronic poverty at 1 km(2) scale in rural Sindh, Pakistan. The models are trained with spatially noisy georeferenced household survey containing poverty scores for 1.67 million anonymized households in Sindh Province and publicly available inputs, including daytime and nighttime satellite imagery and accessibility data. Results from both hold-out and k-fold validation exercises show that the ensemble provides the most reliable spatial predictions in both arid and non-arid regions, outperforming previous studies in key accuracy metrics. A third validation exercise, which involved ground-truthing of predictions from the ensemble model with original survey data of 7000 households further confirms the relative accuracy of the ensemble model predictions. This inexpensive and scalable approach could be used to improve poverty targeting in Pakistan and other low- and middle-income countries.
类型	Article
语种	英语
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000968026400039
WOS关键词	SETTLEMENTS ; IMAGERY
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/398118
推荐引用方式 GB/T 7714	Agyemang, Felix S. K.,Memon, Rashid,Wolf, Levi John,et al. High-resolution rural poverty mapping in Pakistan with ensemble deep learning[J],2023,18(4).
APA	Agyemang, Felix S. K.,Memon, Rashid,Wolf, Levi John,&Fox, Sean.(2023).High-resolution rural poverty mapping in Pakistan with ensemble deep learning.PLOS ONE,18(4).
MLA	Agyemang, Felix S. K.,et al."High-resolution rural poverty mapping in Pakistan with ensemble deep learning".PLOS ONE 18.4(2023).