干旱区生态环境知识资源中心(Arid): Aeolian Desertification Dynamics from 1995 to 2020 in Northern China: Classification Using a Random Forest Machine Learning Algorithm Based on Google Earth Engine

Arid

DOI	10.3390/rs16163100
	Aeolian Desertification Dynamics from 1995 to 2020 in Northern China: Classification Using a Random Forest Machine Learning Algorithm Based on Google Earth Engine
	Zhang, Caixia; Tan, Ningjing; Li, Jinchang
通讯作者	Zhang, CX
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2024
卷号	16 期号:16
英文摘要	Machine learning methods have improved in recent years and provide increasingly powerful tools for understanding landscape evolution. In this study, we used the random forest method based on Google Earth Engine to evaluate the desertification dynamics in northern China from 1995 to 2020. We selected Landsat series image bands, remote sensing inversion data, climate baseline data, land use data, and soil type data as variables for majority voting in the random forest method. The method's average classification accuracy was 91.6% +/- 5.8 [mean +/- SD], and the average kappa coefficient was 0.68 +/- 0.09, suggesting good classification results. The random forest classifier results were consistent with the results of visual interpretation for the spatial distribution of different levels of desertification. From 1995 to 2000, the area of aeolian desertification increased at an average rate of 9977 km2 yr-1, and from 2000 to 2005, from 2005 to 2010, from 2010 to 2015, and from 2015 to 2020, the aeolian desertification decreased at an average rate of 2535, 3462, 1487, and 4537 km2 yr-1, respectively.
英文关键词	aeolian desertification random forest classification northern China
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:001305694500001
WOS关键词	SANDY LAND
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/405322
推荐引用方式 GB/T 7714	Zhang, Caixia,Tan, Ningjing,Li, Jinchang. Aeolian Desertification Dynamics from 1995 to 2020 in Northern China: Classification Using a Random Forest Machine Learning Algorithm Based on Google Earth Engine[J],2024,16(16).
APA	Zhang, Caixia,Tan, Ningjing,&Li, Jinchang.(2024).Aeolian Desertification Dynamics from 1995 to 2020 in Northern China: Classification Using a Random Forest Machine Learning Algorithm Based on Google Earth Engine.REMOTE SENSING,16(16).
MLA	Zhang, Caixia,et al."Aeolian Desertification Dynamics from 1995 to 2020 in Northern China: Classification Using a Random Forest Machine Learning Algorithm Based on Google Earth Engine".REMOTE SENSING 16.16(2024).