干旱区生态环境知识资源中心(Arid): Analysis of Landsat-derived multitemporal vegetation cover to understand drivers of oasis agroecosystems change

Arid

DOI	10.1117/1.JRS.13.014517
	Analysis of Landsat-derived multitemporal vegetation cover to understand drivers of oasis agroecosystems change
	Lamqadem, Atman Ait 1; Afrasinei, Gabriela Mihaela 2; Saber, Hafid 1
通讯作者	Lamqadem, Atman Ait
来源期刊	JOURNAL OF APPLIED REMOTE SENSING
ISSN	1931-3195
出版年	2019
卷号	13 期号:1
英文摘要	Oasis agroecosystems monitoring plays a significant role in the economic development, sustainable management, and policy-making of arid and Saharan regions. The aims of this study are to analyze the spatiotemporal changes of oasis vegetation and discuss possible driving forces of changes. This analysis employed field and ancillary data, geographic information system, Landsat imagery, and remote-sensing techniques. Minimum noise fraction is used for endmembers extraction, and spectral mixture analysis is applied to each image to extract vegetation fraction, which is used as an indicator of change. Change detection is performed in six oases in south-eastern Morocco over eight separate periods from 1984 to 2017 using Landsat data. The pattern of the spatiotemporal changes in vegetation cover is analyzed using time-and space-oriented change detection algorithms. Results indicate that the Mezguita, Tinzouline, and Ternata oases had an evenly distributed and constant expansion during the last three decades (of similar to 41.35%), whereas the oases of Fezouata and Ktaoua presented low expansion and randomly distributed change (similar to 29%). However, the vegetation cover of M'Hamid oasis decreased by 23% over the studied period. The results show that spectral mixture analysis yields high accuracies for oasis vegetation extraction in arid areas and accounts for mixed pixel issues. The results are discussed considering also climate and socioeconomic factors, showing that the driving forces of these dynamics are primarily anthropogenic. (C) 2019 Society of Photo-Optical Instrumentation Engineers (SPIE)
英文关键词	oasis agroecosystems spectral mixture analysis Landsat imagery change detection land degradation vegetation cover
类型	Article
语种	英语
国家	Morocco ; Ireland
收录类别	SCI-E
WOS记录号	WOS:000461217900001
WOS关键词	RADIOMETRIC CORRECTION ; RIVER-BASIN ; DESERTIFICATION ; REGION
WOS类目	Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; 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/2XILL650/216696
作者单位	1.Chouaib Doukkali Univ, Fac Sci, Dept Geol, Lab Geodynam & Geomat, El Jadida, Morocco; 2.Teagasc Food Res Ctr, Dept Agrifood Business & Spatial Anal, Dublin, Ireland
推荐引用方式 GB/T 7714	Lamqadem, Atman Ait,Afrasinei, Gabriela Mihaela,Saber, Hafid. Analysis of Landsat-derived multitemporal vegetation cover to understand drivers of oasis agroecosystems change[J],2019,13(1).
APA	Lamqadem, Atman Ait,Afrasinei, Gabriela Mihaela,&Saber, Hafid.(2019).Analysis of Landsat-derived multitemporal vegetation cover to understand drivers of oasis agroecosystems change.JOURNAL OF APPLIED REMOTE SENSING,13(1).
MLA	Lamqadem, Atman Ait,et al."Analysis of Landsat-derived multitemporal vegetation cover to understand drivers of oasis agroecosystems change".JOURNAL OF APPLIED REMOTE SENSING 13.1(2019).