干旱区生态环境知识资源中心(Arid): Barchan Sand Dunes Collisions Detection in High Resolution Satellite Images based on Image Clustering and Transfer Learning

Arid

	Barchan Sand Dunes Collisions Detection in High Resolution Satellite Images based on Image Clustering and Transfer Learning
	Azzaoui, M. A.; Masmoudi, L.; El Belrhiti, H.; Chaouki, I. E.
通讯作者	Azzaoui, MA
来源期刊	INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
ISSN	2158-107X
EISSN	2156-5570
出版年	2020
卷号	11 期号:1 页码:376-383
英文摘要	Desertification is a core concern for populations living in arid and semi-arid areas. Specifically, barchans dunes which are the fastest moving sand dunes put constant pressure over human settlements and infrastructure. Remote sensing was used to analyze sand dunes around Tarfaya city located in the south of Morocco in the Sahara Desert. In this area, dunes form long corridors made of thousands crescent shaped dunes moving simultaneously, thus, making data gathering in the field very difficult. A computer vision approach based on machine learning was proposed to automate the detection of barchans sand dunes and monitor their complex interactions. An IKONOS high resolution satellite image was used with the combination of a clustering algorithm for image segmentation of the dunes corridor, and a Transfer Learning model which was trained to detect three classes of objects: Barchan dunes, bare fields and a new introduced class consisting of dunes collisions. Indeed, collisions were very difficult to model using classical digital image processing methods due to the large variability of their shapes. The model was trained on 1000 image patches which were annotated then augmented to generate a larger dataset. The obtained detection results showed an accuracy of 84,01%. The interest of this research was to provide with a relatively affordable approach for tracking sand dunes locations in order to better understand their dynamics.
英文关键词	High resolution satellite images remote sensing transfer learning image segmentation sand dunes desertification
类型	Article
语种	英语
收录类别	ESCI
WOS记录号	WOS:000518467600047
WOS关键词	FIELD SELF-ORGANIZATION
WOS类目	Computer Science, Theory & Methods
WOS研究方向	Computer Science
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/334248
作者单位	[Azzaoui, M. A.; Masmoudi, L.] Univ Mohammed V Rabat, Lab Concept & Syst Elect Signaux & Informat, Rabat, Morocco; [El Belrhiti, H.] Inst Agron & Vet Hassan II, Dept Sci Fondamentales & Appl, Rabat, Morocco; [Chaouki, I. E.] Ecole Natl Sci Appl Agadir, Dept Informat, Agadir, Morocco
推荐引用方式 GB/T 7714	Azzaoui, M. A.,Masmoudi, L.,El Belrhiti, H.,et al. Barchan Sand Dunes Collisions Detection in High Resolution Satellite Images based on Image Clustering and Transfer Learning[J],2020,11(1):376-383.
APA	Azzaoui, M. A.,Masmoudi, L.,El Belrhiti, H.,&Chaouki, I. E..(2020).Barchan Sand Dunes Collisions Detection in High Resolution Satellite Images based on Image Clustering and Transfer Learning.INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS,11(1),376-383.
MLA	Azzaoui, M. A.,et al."Barchan Sand Dunes Collisions Detection in High Resolution Satellite Images based on Image Clustering and Transfer Learning".INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 11.1(2020):376-383.