Land Use/Land Cover Mapping Based on GEE for the Monitoring of Changes in Ecosystem Types in the Upper Yellow River Basin over the Tibetan Plateau

doi:10.3390/rs14215361

LZUFE-KMS

	Land Use/Land Cover Mapping Based on GEE for the Monitoring of Changes in Ecosystem Types in the Upper Yellow River Basin over the Tibetan Plateau
	Feng, Senyao 1; Li, Wenlong 1; Xu, Jing 2; Liang, Tiangang 1; Ma, Xuanlong 3,4; Wang, Wenying 5; Yu, Hongyan 6
	2022-11-01
发表期刊	Remote Sensing
卷号	14 期号:21
摘要	The upper Yellow River basin over the Tibetan Plateau (TP) is an important ecological barrier in northwestern China. Effective LULC products that enable the monitoring of changes in regional ecosystem types are of great importance for their environmental protection and macro-control. Here, we combined an 18-class LULC classification scheme based on ecosystem types with Sentinel-2 imagery, the Google Earth Engine (GEE) platform, and the random forest method to present new LULC products with a spatial resolution of 10 m in 2018 and 2020 for the upper Yellow River Basin over the TP and conducted monitoring of changes in ecosystem types. The results indicated that: (1) In 2018 and 2020, the overall accuracy (OA) of LULC maps ranged between 87.45% and 93.02%. (2) Grassland was the main LULC first-degree class in the research area, followed by wetland and water bodies and barren land. For the LULC second-degree class, the main LULC was grassland, followed by broadleaf shrub and marsh. (3) In the first-degree class of changes in ecosystem types, the largest area of progressive succession (positive) was grassland–shrubland (451.13 km2), whereas the largest area of retrogressive succession (negative) was grassland–barren (395.91 km2). In the second-degree class, the largest areas of progressive succession (positive) were grassland–broadleaf shrub (344.68 km2) and desert land–grassland (302.02 km2), whereas the largest areas of retrogressive succession (negative) were broadleaf shrubland–grassland (309.08 km2) and grassland–bare rock (193.89 km2). The northern and southwestern parts of the study area showed a trend towards positive succession, whereas the south-central Huangnan, northeastern Gannan, and central Aba Prefectures showed signs of retrogressive succession in their changes in ecosystem types. The purpose of this study was to provide basis data for basin-scale ecosystem monitoring and analysis with more detailed categories and reliable accuracy. © 2022 by the authors.
关键词	Decision trees Engines Forestry Land use Machine learning Mapping Rivers Watersheds Wetlands Ecosystem type Google earth engine Google earths Land cover mapping Land use/land cover Land use/land cover mapping Machine-learning Sentinel-2 Upper yellow river basin Upper yellow rivers Yellow River basin
DOI	10.3390/rs14215361
收录类别	EI ; SCIE
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:000881450900001
出版者	MDPI
EI入藏号	20224613127119
EI主题词	Ecosystems
EI分类号	403 Urban and Regional Planning and Development ; 405.3 Surveying ; 444.1 Surface Water ; 454.3 Ecology and Ecosystems ; 723.4 Artificial Intelligence ; 821 Agricultural Equipment and Methods ; Vegetation and Pest Control ; 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory ; 961 Systems Science
原始文献类型	Journal article (JA)
EISSN	2072-4292
引用统计	被引频次：16[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/33101
专题	兰州财经大学
作者单位	1.State Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou; 730000, China; 2.School of Agriculture and Forestry Economic and Management, Lanzhou University of Finance and Economics, Lanzhou; 730020, China; 3.College of Earth and Environmental Sciences, Lanzhou University, Lanzhou; 730020, China; 4.Institute of Yellow River Basin Green Development, Lanzhou University, Lanzhou; 730020, China; 5.Department of Life Sciences, Qinghai Normal University, Xining; 810008, China; 6.Service Guarantee Center of Qilian Mountain National Park in Qinghai, Xining; 810008, China
推荐引用方式 GB/T 7714	Feng, Senyao,Li, Wenlong,Xu, Jing,et al. Land Use/Land Cover Mapping Based on GEE for the Monitoring of Changes in Ecosystem Types in the Upper Yellow River Basin over the Tibetan Plateau[J]. Remote Sensing,2022,14(21).
APA	Feng, Senyao.,Li, Wenlong.,Xu, Jing.,Liang, Tiangang.,Ma, Xuanlong.,...&Yu, Hongyan.(2022).Land Use/Land Cover Mapping Based on GEE for the Monitoring of Changes in Ecosystem Types in the Upper Yellow River Basin over the Tibetan Plateau.Remote Sensing,14(21).
MLA	Feng, Senyao,et al."Land Use/Land Cover Mapping Based on GEE for the Monitoring of Changes in Ecosystem Types in the Upper Yellow River Basin over the Tibetan Plateau".Remote Sensing 14.21(2022).