干旱区生态环境知识资源中心(Arid): Automatic Extraction of the Spatial Distribution of Picea schrenkiana in the Tianshan Mountains Based on Google Earth Engine and the Jeffries-Matusita Distance

Arid

DOI	10.3390/f14071373
	Automatic Extraction of the Spatial Distribution of Picea schrenkiana in the Tianshan Mountains Based on Google Earth Engine and the Jeffries-Matusita Distance
	Xu, Fujin; Xu, Zhonglin; Xu, Changchun; Yu, Tingting
通讯作者	Xu, CC
来源期刊	FORESTS
EISSN	1999-4907
出版年	2023
卷号	14 期号:7
英文摘要	As a distinct species in the Tianshan Mountains (TS) of Central Asia (CA), Picea schrenkiana plays a significant role in water purification, soil and water conservation, and climate regulation. In the context of climate change, rapidly and accurately obtaining its spatial distribution has critical decision-making significance for maintaining ecological security in the arid area of CA and the sustainable development of the Silk Road Economic Belt. However, conventional methods are extremely challenging to accomplish the high-resolution mapping of Picea schrenkiana in the TS, which is characterized by a wide range (9.97 x 10(5) km(2)) and complex terrain. The approach of geo-big data and cloud computing provides new opportunities to address this issue. Therefore, the purpose of this study is to propose an automatic extraction procedure for the spatial distribution of Picea schrenkiana based on Google Earth Engine and the Jeffries-Matusita (JM) distance, which considered three aspects: sample points, remote-sensing images, and classification features. The results showed that (1) after removing abnormal samples and selecting the summer image, the producer accuracy (PA) of Picea schrenkiana was improved by 2.95% and 0.24%-2.10%, respectively. (2) Both the separation obtained by the JM distance and the analysis results of eight schemes showed that spectral features and texture features played a key role in the mapping of Picea schrenkiana. (3) The JM distance can seize the classification features that are most conducive to the mapping of Picea schrenkiana, and effectively improve the classification accuracy. The PA and user accuracy of Picea schrenkiana were 96.74% and 96.96%, respectively. The overall accuracy was 91.93%, while the Kappa coefficient was 0.89. (4) The results show that Picea schrenkiana is concentrated in the middle TS and scattered in the remaining areas. In total, 85.7%, 66.4%, and 85.9% of Picea schrenkiana were distributed in the range of 1500-2700 m, 20-40 & DEG;, and on shady slope and semi-shady slope, respectively. The automatic procedure adopted in this study provides a basis for the rapid and accurate mapping of the spatial distribution of coniferous forests in the complex terrain.
英文关键词	Google Earth Engine Sentinel-1 Sentinel-2 JM distance Tianshan mountains Picea schrenkiana
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:001036205600001
WOS关键词	RANDOM FOREST ; FEATURE-SELECTION ; CLIMATE-CHANGE ; LANDSAT ; BIOMASS ; GROWTH ; CHINA
WOS类目	Forestry
WOS研究方向	Forestry
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/396430
推荐引用方式 GB/T 7714	Xu, Fujin,Xu, Zhonglin,Xu, Changchun,et al. Automatic Extraction of the Spatial Distribution of Picea schrenkiana in the Tianshan Mountains Based on Google Earth Engine and the Jeffries-Matusita Distance[J],2023,14(7).
APA	Xu, Fujin,Xu, Zhonglin,Xu, Changchun,&Yu, Tingting.(2023).Automatic Extraction of the Spatial Distribution of Picea schrenkiana in the Tianshan Mountains Based on Google Earth Engine and the Jeffries-Matusita Distance.FORESTS,14(7).
MLA	Xu, Fujin,et al."Automatic Extraction of the Spatial Distribution of Picea schrenkiana in the Tianshan Mountains Based on Google Earth Engine and the Jeffries-Matusita Distance".FORESTS 14.7(2023).