干旱区生态环境知识资源中心(Arid): Accurate Extraction of Mountain Grassland From Remote Sensing Image Using a Capsule Network

Arid

DOI	10.1109/LGRS.2020.2992661
	Accurate Extraction of Mountain Grassland From Remote Sensing Image Using a Capsule Network
	Guo, Zhengqiang; Liu, Hailong; Zheng, Zezhong; Chen, Xi; Liang, Yan
通讯作者	Liu, HL (corresponding author), Univ Elect Sci & Technol China, Sch Resources & Environm, Chengdu 611731, Peoples R China.
来源期刊	IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
ISSN	1545-598X
EISSN	1558-0571
出版年	2021
卷号	18 期号:6 页码:964-968
英文摘要	Due to an increasing demand of animal husbandry in arid (semiarid) area in China, grassland monitoring based on big data has become a proliferating research focus in recent years. However, the spectral of grass is interfered by topographic relief or that of forest in remote sensing image classification, leading to confusing pixels. In this letter, Tangbula grassland in the middle section of the Tianshan Mountains in Xinjiang (China) was selected as the research area. Upon analysis, we developed a novel composite multifeature deep learning method of capsule network to realize rapid and high-precision remote sensing recognition of the mountainous grassland, through combining the spectral bands with all the extracted features [normalized difference vegetation index (NDVI), topographic, and texture]. Using the new method, the accuracy of the grassland and overall classifications reached the highest values of 91.60% and 96.13%, respectively, greater than those of 85.58% and 92.18%, respectively, of normal classifications without input from texture and topographic features. Compared with the other methods, the method we applied is better than support vector machine (SVM), random forest, and artificial neural network in terms of grassland extraction and classification accuracy.
英文关键词	Feature extraction Remote sensing Deep learning Vegetation mapping Training Indexes Microsoft Windows Classification deep learning grassland remote sensing
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000652799700006
WOS关键词	NEURAL-NETWORK ; CLASSIFICATION ; VEGETATION ; TEXTURE
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构	中国科学院新疆生态与地理研究所
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/367990
作者单位	[Guo, Zhengqiang; Liu, Hailong; Zheng, Zezhong; Liang, Yan] Univ Elect Sci & Technol China, Sch Resources & Environm, Chengdu 611731, Peoples R China; [Chen, Xi] Chinese Acad Sci, Xinjiang Inst Ecol & Geog, Urumqi 830011, Peoples R China
推荐引用方式 GB/T 7714	Guo, Zhengqiang,Liu, Hailong,Zheng, Zezhong,et al. Accurate Extraction of Mountain Grassland From Remote Sensing Image Using a Capsule Network[J]. 中国科学院新疆生态与地理研究所,2021,18(6):964-968.
APA	Guo, Zhengqiang,Liu, Hailong,Zheng, Zezhong,Chen, Xi,&Liang, Yan.(2021).Accurate Extraction of Mountain Grassland From Remote Sensing Image Using a Capsule Network.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,18(6),964-968.
MLA	Guo, Zhengqiang,et al."Accurate Extraction of Mountain Grassland From Remote Sensing Image Using a Capsule Network".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 18.6(2021):964-968.