干旱区生态环境知识资源中心(Arid): Sentinel-2 Data for Land Use Mapping: Comparing Different Supervised Classifications in Semi-Arid Areas

Arid

DOI	10.3390/agriculture12091429
	Sentinel-2 Data for Land Use Mapping: Comparing Different Supervised Classifications in Semi-Arid Areas
	Abida, Khouloud; Barbouchi, Meriem; Boudabbous, Khaoula; Toukabri, Wael; Saad, Karem; Bousnina, Habib; Chahed, Thouraya Sahli
通讯作者	Abida, K
来源期刊	AGRICULTURE-BASEL
EISSN	2077-0472
出版年	2022
卷号	12 期号:9
英文摘要	Mapping and monitoring land use (LU) changes is one of the most effective ways to understand and manage land transformation. The main objectives of this study were to classify LU using supervised classification methods and to assess the effectiveness of various machine learning methods. The current investigation was conducted in the Nord-Est area of Tunisia, and an optical satellite image covering the study area was acquired from Sentinel-2. For LU mapping, we tested three machine learning models algorithms: Random Forest (RF), K-Dimensional Trees K-Nearest Neighbors (KDTree-KNN) and Minimum Distance Classification (MDC). According to our research, the RF classification provided a better result than other classification models. RF classification exhibited the best values of overall accuracy, kappa, recall, precision and RMSE, with 99.54%, 0.98%, 0.98%, 0.98% and 0.23%, respectively. However, low precision was observed for the MDC method (RMSE = 1.15). The results were more intriguing since they highlighted the value of the bare soil index as a covariate for LU mapping. Our results suggest that Sentinel-2 combined with RF classification is efficient for creating a LU map.
英文关键词	sentinel-2 land use mapping supervised classification spectral index machine learning
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000856163800001
WOS关键词	SPECTRAL REFLECTANCE ; RANDOM FORESTS ; SOIL INDEXES ; BUILT-UP ; COVER ; GROUNDWATER ; ALGORITHMS ; NORTHEAST ; ZAGHOUAN ; AQUIFER
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/2XILL650/391695
推荐引用方式 GB/T 7714	Abida, Khouloud,Barbouchi, Meriem,Boudabbous, Khaoula,et al. Sentinel-2 Data for Land Use Mapping: Comparing Different Supervised Classifications in Semi-Arid Areas[J],2022,12(9).
APA	Abida, Khouloud.,Barbouchi, Meriem.,Boudabbous, Khaoula.,Toukabri, Wael.,Saad, Karem.,...&Chahed, Thouraya Sahli.(2022).Sentinel-2 Data for Land Use Mapping: Comparing Different Supervised Classifications in Semi-Arid Areas.AGRICULTURE-BASEL,12(9).
MLA	Abida, Khouloud,et al."Sentinel-2 Data for Land Use Mapping: Comparing Different Supervised Classifications in Semi-Arid Areas".AGRICULTURE-BASEL 12.9(2022).