干旱区生态环境知识资源中心(Arid): Multi-Scale LBP Texture Feature Learning Network for Remote Sensing Interpretation of Land Desertification

Arid

DOI	10.3390/rs14143486
	Multi-Scale LBP Texture Feature Learning Network for Remote Sensing Interpretation of Land Desertification
	Wang, Wuli; Jiang, Yumeng; Wang, Ge; Guo, Fangming; Li, Zhongwei; Liu, Baodi
通讯作者	Wang, WL
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2022
卷号	14 期号:14
英文摘要	Land desertification is a major challenge to global sustainable development. Therefore, the timely and accurate monitoring of the land desertification status can provide scientific decision support for desertification control. The existing automatic interpretation methods are affected by factors such as same spectrum different matter, different spectrum same object, staggered distribution of desertification areas, and wide ranges of ground objects. We propose an automatic interpretation method for the remote sensing of land desertification that incorporates multi-scale local binary pattern (MSLBP) and spectral features based on the above issues. First, a multi-scale convolutional LBP feature extraction network is designed to obtain the spatial texture features of remote sensing images and fuse them with spectral features to enhance the feature representation capability of the model. Then, considering the continuity of the distribution of the same kind of ground objects in local space, we designed an adaptive median filtering method to process the probability map of the extreme learning machine (ELM) classifier output to improve the classification accuracy. Four typical datasets were developed using GF-1 multispectral imagery with the Horqin Left Wing Rear Banner as the study area. Experimental results on four datasets show that the proposed method solves the problem of ill classification and omission in classifying the remote sensing images of desertification, effectively suppresses the effects of homospectrum and heterospectrum, and significantly improves the accuracy of the remote sensing interpretation of land desertification.
英文关键词	desertification land cover classification extreme learning machine local binary patterns Horqin Left Wing Rear Banner
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:000833937800001
WOS关键词	TIME-SERIES ; CLASSIFICATION ; AREA ; DYNAMICS ; MACHINE ; DROUGHT ; CLIMATE ; IMAGERY ; COVER ; MODIS
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/2XILL650/394175
推荐引用方式 GB/T 7714	Wang, Wuli,Jiang, Yumeng,Wang, Ge,et al. Multi-Scale LBP Texture Feature Learning Network for Remote Sensing Interpretation of Land Desertification[J],2022,14(14).
APA	Wang, Wuli,Jiang, Yumeng,Wang, Ge,Guo, Fangming,Li, Zhongwei,&Liu, Baodi.(2022).Multi-Scale LBP Texture Feature Learning Network for Remote Sensing Interpretation of Land Desertification.REMOTE SENSING,14(14).
MLA	Wang, Wuli,et al."Multi-Scale LBP Texture Feature Learning Network for Remote Sensing Interpretation of Land Desertification".REMOTE SENSING 14.14(2022).