气候变化领域集成服务门户(CCPortal): Testing Accuracy of Land Cover Classification Algorithms in the Qilian Mountains Based on GEE Cloud Platform

CCPortal

DOI	10.3390/rs13245064
	Testing Accuracy of Land Cover Classification Algorithms in the Qilian Mountains Based on GEE Cloud Platform
	Yang, Yanpeng; Yang, Dong; Wang, Xufeng; Zhang, Zhao; Nawaz, Zain
通讯作者	Yang, D (通讯作者)，Northwest Normal Univ, Coll Geog & Environm Sci, Lanzhou 730070, Peoples R China.
发表日期	2021
EISSN	2072-4292
卷号	13 期号:24
英文摘要	The Qilian Mountains (QLM) are an important ecological barrier in western China. High-precision land cover data products are the basic data for accurately detecting and evaluating the ecological service functions of the QLM. In order to study the land cover in the QLM and performance of different remote sensing classification algorithms for land cover mapping based on the Google Earth Engine (GEE) cloud platform, the higher spatial resolution remote sensing images of Sentinel-1 and Sentinel-2; digital elevation data; and three remote sensing classification algorithms, including the support vector machine (SVM), the classification regression tree (CART), and the random forest (RF) algorithms, were used to perform supervised classification of Sentinel-2 images of the QLM. Furthermore, the results obtained from the classification process were compared and analyzed by using different remote sensing classification algorithms and feature-variable combinations. The results indicated that: (1) the accuracy of the classification results acquired by using different remote sensing classification algorithms were different, and the RF had the highest classification accuracy, followed by the CART and the SVM; (2) the different feature variable combinations had different effects on the overall accuracy (OA) of the classification results and the performance of the identification and classification of the different land cover types; and (3) compared with the existing land cover products for the QLM, the land cover maps obtained in this study had a higher spatial resolution and overall accuracy.
关键词	TIME-SERIES MACHINE PERFORMANCE CHINA AREA
英文关键词	land cover; Qilian Mountains; Sentinel-2; GEE cloud platform; machine learning
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:000742423300001
来源期刊	REMOTE SENSING
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/254161
作者单位	[Yang, Yanpeng; Yang, Dong] Northwest Normal Univ, Coll Geog & Environm Sci, Lanzhou 730070, Peoples R China; [Yang, Yanpeng; Wang, Xufeng] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Heihe Remote Sensing Expt Res Stn, Key Lab Remote Sensing Gansu Prov, Lanzhou 730000, Peoples R China; [Zhang, Zhao] Shanghai Sci & Technol Exchange Ctr, Shanghai 200235, Peoples R China; [Nawaz, Zain] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Remote Sensing Gansu Prov, Lanzhou 730000, Peoples R China
推荐引用方式 GB/T 7714	Yang, Yanpeng,Yang, Dong,Wang, Xufeng,et al. Testing Accuracy of Land Cover Classification Algorithms in the Qilian Mountains Based on GEE Cloud Platform[J]. 中国科学院西北生态环境资源研究院,2021,13(24).
APA	Yang, Yanpeng,Yang, Dong,Wang, Xufeng,Zhang, Zhao,&Nawaz, Zain.(2021).Testing Accuracy of Land Cover Classification Algorithms in the Qilian Mountains Based on GEE Cloud Platform.REMOTE SENSING,13(24).
MLA	Yang, Yanpeng,et al."Testing Accuracy of Land Cover Classification Algorithms in the Qilian Mountains Based on GEE Cloud Platform".REMOTE SENSING 13.24(2021).