干旱区生态环境知识资源中心(Arid): Deep Learning for Vegetation Health Forecasting: A Case Study in Kenya

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DOI	10.3390/rs14030698
	Deep Learning for Vegetation Health Forecasting: A Case Study in Kenya
	Lees, Thomas; Tseng, Gabriel; Atzberger, Clement; Reece, Steven; Dadson, Simon
通讯作者	Lees, T
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2022
卷号	14 期号:3
英文摘要	East Africa has experienced a number of devastating droughts in recent decades, including the 2010/2011 drought. The National Drought Management Authority in Kenya relies on real-time information from MODIS satellites to monitor and respond to emerging drought conditions in the arid and semi-arid lands of Kenya. Providing accurate and timely information on vegetation conditions and health-and its probable near-term future evolution-is essential for minimising the risk of drought conditions evolving into disasters as the country's herders directly rely on the conditions of grasslands. Methods from the field of machine learning are increasingly being used in hydrology, meteorology, and climatology. One particular method that has shown promise for rainfall-runoff modelling is the Long Short Term Memory (LSTM) network. In this study, we seek to test two LSTM architectures for vegetation health forecasting. We find that these models provide sufficiently accurate forecasts to be useful for drought monitoring and forecasting purposes, showing competitive performances with lower resolution ensemble methods and improved performances over a shallow neural network and a persistence baseline.
英文关键词	machine learning deep learning drought vegetation health
类型	Article
语种	英语
开放获取类型	gold, Green Accepted, Green Published
收录类别	SCI-E
WOS记录号	WOS:000759872100001
WOS关键词	DROUGHT ; MODEL ; TEMPERATURE ; LESSONS ; SYSTEM
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/376399
推荐引用方式 GB/T 7714	Lees, Thomas,Tseng, Gabriel,Atzberger, Clement,et al. Deep Learning for Vegetation Health Forecasting: A Case Study in Kenya[J],2022,14(3).
APA	Lees, Thomas,Tseng, Gabriel,Atzberger, Clement,Reece, Steven,&Dadson, Simon.(2022).Deep Learning for Vegetation Health Forecasting: A Case Study in Kenya.REMOTE SENSING,14(3).
MLA	Lees, Thomas,et al."Deep Learning for Vegetation Health Forecasting: A Case Study in Kenya".REMOTE SENSING 14.3(2022).