干旱区生态环境知识资源中心(Arid): Multi-Year Cereal Crop Classification Model in a Semi-Arid Region Using Sentinel-2 and Landsat 7-8 Data

Arid

DOI	10.3390/agriculture13081633
	Multi-Year Cereal Crop Classification Model in a Semi-Arid Region Using Sentinel-2 and Landsat 7-8 Data
	Khlif, Manel; Escorihuela, Maria Jose; Bellakanji, Aicha Chahbi; Paolini, Giovanni; Kassouk, Zeineb; Chabaane, Zohra Lili
通讯作者	Khlif, M
来源期刊	AGRICULTURE-BASEL
EISSN	2077-0472
出版年	2023
卷号	13 期号:8
英文摘要	This study developed a multi-year classification model for winter cereal in a semi-arid region, the Kairouan area (Tunisia). A random forest classification model was constructed using Sentinel 2 (S2) vegetation indices for a reference agricultural season, 2020/2021. This model was then applied using S2 and Landsat (7 and 8) data for previous seasons from 2011 to 2022 and validated using field observation data. The reference classification model achieved an overall accuracy (OA) of 89.3%. Using S2 data resulted in higher overall classification accuracy. Cereal classification exhibited excellent precision ranging from 85.8% to 95.1% when utilizing S2 data, while lower accuracy (41% to 91.8%) was obtained when using only Landsat data. A slight confusion between cereals and cereals growing with olive trees was observed. A second objective was to map cereals as early as possible in the agricultural season. An early cereal classification model demonstrated accurate results in February (four months before harvest), with a precision of 95.2% and an OA of 87.7%. When applied to the entire period, February cereal classification exhibited a precision ranging from 85.1% to 94.2% when utilizing S2 data, while lower accuracy (42.6% to 95.4%) was observed in general with Landsat data. This methodology could be adopted in other cereal regions with similar climates to produce very useful information for the planner, leading to a reduction in fieldwork.
英文关键词	land cover classification early cereal classification sentinel 2 Landsat random forest
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:001056775000001
WOS关键词	SUPPORT VECTOR MACHINES ; VEGETATION INDEX ; EARTH ; IMAGERY ; EXTENT ; RED
WOS类目	Agronomy
WOS研究方向	Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/395156
推荐引用方式 GB/T 7714	Khlif, Manel,Escorihuela, Maria Jose,Bellakanji, Aicha Chahbi,et al. Multi-Year Cereal Crop Classification Model in a Semi-Arid Region Using Sentinel-2 and Landsat 7-8 Data[J],2023,13(8).
APA	Khlif, Manel,Escorihuela, Maria Jose,Bellakanji, Aicha Chahbi,Paolini, Giovanni,Kassouk, Zeineb,&Chabaane, Zohra Lili.(2023).Multi-Year Cereal Crop Classification Model in a Semi-Arid Region Using Sentinel-2 and Landsat 7-8 Data.AGRICULTURE-BASEL,13(8).
MLA	Khlif, Manel,et al."Multi-Year Cereal Crop Classification Model in a Semi-Arid Region Using Sentinel-2 and Landsat 7-8 Data".AGRICULTURE-BASEL 13.8(2023).