气候变化领域集成服务门户(CCPortal): An Integrated Land Cover Mapping Method Suitable for Low-Accuracy Areas in Global Land Cover Maps

CCPortal

DOI	10.3390/rs11151777
	An Integrated Land Cover Mapping Method Suitable for Low-Accuracy Areas in Global Land Cover Maps
	Zeng, Tian; Wang, Lei; Zhang, Zengxiang; Wen, Qingke; Wang, Xiao; Yu, Le
通讯作者	Wang, L (通讯作者)
发表日期	2019
EISSN	2072-4292
卷号	11 期号:15
英文摘要	In land cover mapping, an area with complex topography or heterogeneous land covers is usually poorly classified and therefore defined as a low-accuracy area. The low-accuracy areas are important because they restrict the overall accuracy (OA) of global land cover classification (LCC) data generated. In this paper, low-accuracy areas in China (extracted from the MODIS global LCC maps) were taken as examples, identified as the regions having lower accuracy than the average OA of China. An integrated land cover mapping method targeting low-accuracy regions was developed and tested in eight representative low-accuracy regions of China. The method optimized procedures of image choosing and sample selection based on an existent visually-interpreted regional LCC dataset with high accuracies. Five algorithms and 16 groups of classification features were compared to achieve the highest OA. The support vector machine (SVM) achieved the highest mean OA (81.5%) when only spectral bands were classified. Aspect tended to attenuate OA as a classification feature. The optimal classification features for different regions largely depends on the topographic feature of vegetation. The mean OA for eight low-accuracy regions was 84.4% by the proposed method in this study, which exceeded the mean OA of most precedent global land cover datasets. The new method can be applied worldwide to improve land cover mapping of low-accuracy areas in global land cover maps.
关键词	CLASSIFICATION SATELLITE VARIABILITY ALGORITHMS CONTINUITY DATABASE FUSION
英文关键词	land cover classification; low-accuracy area; classification algorithms; support vector machine; topographical data; classification accuracy
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000482442800041
来源期刊	REMOTE SENSING
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/259450
推荐引用方式 GB/T 7714	Zeng, Tian,Wang, Lei,Zhang, Zengxiang,et al. An Integrated Land Cover Mapping Method Suitable for Low-Accuracy Areas in Global Land Cover Maps[J]. 中国科学院青藏高原研究所,2019,11(15).
APA	Zeng, Tian,Wang, Lei,Zhang, Zengxiang,Wen, Qingke,Wang, Xiao,&Yu, Le.(2019).An Integrated Land Cover Mapping Method Suitable for Low-Accuracy Areas in Global Land Cover Maps.REMOTE SENSING,11(15).
MLA	Zeng, Tian,et al."An Integrated Land Cover Mapping Method Suitable for Low-Accuracy Areas in Global Land Cover Maps".REMOTE SENSING 11.15(2019).