干旱区生态环境知识资源中心(Arid): Deep Insight on Land Use/Land Cover Geospatial Assessment through Internet-Based Validation Tool in Upper Karkheh River Basin (KRB), South-West Iran

Arid

DOI	10.3390/land12050979
	Deep Insight on Land Use/Land Cover Geospatial Assessment through Internet-Based Validation Tool in Upper Karkheh River Basin (KRB), South-West Iran
	Mallah, Sina; Gorji, Manouchehr; Balali, Mohammad Reza; Asadi, Hossein; Davatgar, Naser; Varmazyari, Hojjat; Stellacci, Anna Maria; Castellini, Mirko
通讯作者	Gorji, M
来源期刊	LAND
EISSN	2073-445X
出版年	2023
卷号	12 期号:5
英文摘要	Recently, the demand for high-quality land use/land cover (LULC) information for near-real-time crop type mapping, in particular for multi-relief landscapes, has increased. While the LULC classes are inherently imbalanced, the statistics generally overestimate the majority classes and underestimate the minority ones. Therefore, the aim of this study was to assess the classes of the 10 m European Satellite Agency (ESA) WorldCover 2020 land use/land cover product with the support of the Google Earth Engine (GEE) in the Honam sub-basin, south-west Iran, using the LACOVAL (validation tool for regional-scale land cover and land cover change) online platform. The effect of imbalanced ground truth has also been explored. Four sampling schemes were employed on a total of 720 collected ground truth points over approximately 14,100 ha. The grassland and cropland totally canopied 94% of the study area, while barren land, shrubland, trees and built-up covered the rest. The results of the validation accuracy showed that the equalized sampling scheme was more realistically successful than the others in terms of roughly the same overall accuracy (91.6%), mean user's accuracy (91.6%), mean producers' accuracy (91.9%), mean partial portmanteau (91.9%) and kappa (0.9). The product was statistically improved to 93.5% +/- 0.04 by the assembling approach and segmented with the help of supplementary datasets and visual interpretation. The findings confirmed that, in mapping LULC, data of classes should be balanced before accuracy assessment. It is concluded that the product is a reliable dataset for environmental modeling at the regional scale but needs some modifications for barren land and grassland classes in mountainous semi-arid regions of the globe.
英文关键词	quality assessment imbalanced dataset classification accuracy cropland area map accuracy image processing
类型	Article
语种	英语
开放获取类型	gold, Green Published
收录类别	SSCI
WOS记录号	WOS:000997233800001
WOS关键词	THEMATIC ACCURACY ; USE/COVER CHANGE ; CLASSIFICATION ; DIFFERENCE ; LANDSCAPE ; QUANTITY
WOS类目	Environmental Studies
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/397654
推荐引用方式 GB/T 7714	Mallah, Sina,Gorji, Manouchehr,Balali, Mohammad Reza,et al. Deep Insight on Land Use/Land Cover Geospatial Assessment through Internet-Based Validation Tool in Upper Karkheh River Basin (KRB), South-West Iran[J],2023,12(5).
APA	Mallah, Sina.,Gorji, Manouchehr.,Balali, Mohammad Reza.,Asadi, Hossein.,Davatgar, Naser.,...&Castellini, Mirko.(2023).Deep Insight on Land Use/Land Cover Geospatial Assessment through Internet-Based Validation Tool in Upper Karkheh River Basin (KRB), South-West Iran.LAND,12(5).
MLA	Mallah, Sina,et al."Deep Insight on Land Use/Land Cover Geospatial Assessment through Internet-Based Validation Tool in Upper Karkheh River Basin (KRB), South-West Iran".LAND 12.5(2023).