干旱区生态环境知识资源中心(Arid): The Unmanned Aerial Vehicle (UAV)-Based Hyperspectral Classification of Desert Grassland Plants in Inner Mongolia, China

Arid

DOI	10.3390/app132212245
	The Unmanned Aerial Vehicle (UAV)-Based Hyperspectral Classification of Desert Grassland Plants in Inner Mongolia, China
	Wang, Shengli; Bi, Yuge; Du, Jianmin; Zhang, Tao; Gao, Xinchao; Jin, Erdmt
通讯作者	Du, JM
来源期刊	APPLIED SCIENCES-BASEL
EISSN	2076-3417
出版年	2023
卷号	13 期号:22
英文摘要	In recent years, grassland ecosystems have faced increasingly severe desertification, which has caused continuous changes in the vegetation composition in grassland ecosystems. Therefore, effective research on grassland plant taxa is crucial to exploring the process of grassland desertification. This study proposed a solution by constructing a UAV hyperspectral remote sensing system to collect the hyperspectral data of various species in desert grasslands. This approach overcomes the limitations of traditional grassland survey methods such as a low efficiency and insufficient spatial resolution. A streamlined 2D-CNN model with different feature enhancement modules was constructed, and an improved depth-separable convolution approach was used to classify the desert grassland plants. The model was compared with existing hyperspectral classification models, such as ResNet34 and DenseNet121, under the preprocessing condition of data downscaling by combining the variance and F-norm2. The results showed that the model outperformed the other models in terms of the overall classification accuracy, kappa coefficient, and memory occupied, achieving 99.216%, 98.735%, and 16.3 MB, respectively. This model could effectively classify desert grassland species. This method provides a new approach for monitoring grassland ecosystem degradation.
英文关键词	desert grassland UAV hyperspectral remote sensing lightweight network species classification
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:001120797400001
WOS关键词	IMAGERY
WOS类目	Chemistry, Multidisciplinary ; Engineering, Multidisciplinary ; Materials Science, Multidisciplinary ; Physics, Applied
WOS研究方向	Chemistry ; Engineering ; Materials Science ; Physics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/395374
推荐引用方式 GB/T 7714	Wang, Shengli,Bi, Yuge,Du, Jianmin,et al. The Unmanned Aerial Vehicle (UAV)-Based Hyperspectral Classification of Desert Grassland Plants in Inner Mongolia, China[J],2023,13(22).
APA	Wang, Shengli,Bi, Yuge,Du, Jianmin,Zhang, Tao,Gao, Xinchao,&Jin, Erdmt.(2023).The Unmanned Aerial Vehicle (UAV)-Based Hyperspectral Classification of Desert Grassland Plants in Inner Mongolia, China.APPLIED SCIENCES-BASEL,13(22).
MLA	Wang, Shengli,et al."The Unmanned Aerial Vehicle (UAV)-Based Hyperspectral Classification of Desert Grassland Plants in Inner Mongolia, China".APPLIED SCIENCES-BASEL 13.22(2023).