干旱区生态环境知识资源中心(Arid): Spectral mixture analysis (SMA) and change vector analysis (CVA) methods for monitoring and mapping land degradation/desertification in arid and semiarid areas (Sudan), using Landsat imagery

Arid

DOI	10.1016/j.ejrs.2016.12.008
	Spectral mixture analysis (SMA) and change vector analysis (CVA) methods for monitoring and mapping land degradation/desertification in arid and semiarid areas (Sudan), using Landsat imagery
	Salih, Abdelrahim A. M.; Ganawa, El-Tyeb; Elmahl, Anwer Alsadat
通讯作者	Salih, AAM
来源期刊	EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES
ISSN	1110-9823
EISSN	2090-2476
出版年	2017
卷号	20 页码:S21-S29
英文摘要	The severe Sahel catastrophe in 1968-1974 as well as repeated famines and food shortage that have hit many African countries during the 1970s have highlighted the need for further research concerning land degradation and environmental monitoring in arid and semi-arid areas. Land degradation, and desertification processes in arid and semi-arid environment were increased in the last four decades, especially in the developing countries like Sudan. To test to what extent remote sensing and geographical information science (GIS) methodologies and techniques could be used for monitoring changes in arid and semi-arid regions and environment, these methodologies have long been suggested as a time and cost-efficient method. In this frame, spectral Mixture Analysis (SMA), Object-based oriented classification (Segmentation), and Change Vector Analysis are recently much recommended as a most suitable method for monitoring and mapping land cover changes in arid and semi-arid environment. Therefor the aim of this study is to use these methods and techniques for environmental monitoring with emphasis on desertification and to find model that can describe and map the status and rate of desertification processes and land cover changes in semi-arid areas in White Nile State (Sudan) by using multi-temporal imagery of the Landsat satellite TM (1987), TM (2000), and ETM+ (2014) respectively. The paper also discusses and evaluates the efficiency of the adapted methodologies in monitoring the land degradation processes and changes in the arid and semi-arid regions. (C) 2017 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-ncnd/4.0/).
英文关键词	Land degradation Spectral mixture analysis Segmentation Landsat Classification and semiarid
类型	Article
语种	英语
开放获取类型	DOAJ Gold
收录类别	ESCI
WOS记录号	WOS:000396610600004
WOS关键词	VEGETATION
WOS类目	Environmental Sciences ; Remote Sensing
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/332082
作者单位	[Salih, Abdelrahim A. M.; Ganawa, El-Tyeb] Univ Khartoum, Fac Geog & Environm Sci, Dept GIS, Khartoum, Sudan; [Elmahl, Anwer Alsadat] UN Childrens Emergency Fund Unicef, Khartoum, Sudan
推荐引用方式 GB/T 7714	Salih, Abdelrahim A. M.,Ganawa, El-Tyeb,Elmahl, Anwer Alsadat. Spectral mixture analysis (SMA) and change vector analysis (CVA) methods for monitoring and mapping land degradation/desertification in arid and semiarid areas (Sudan), using Landsat imagery[J],2017,20:S21-S29.
APA	Salih, Abdelrahim A. M.,Ganawa, El-Tyeb,&Elmahl, Anwer Alsadat.(2017).Spectral mixture analysis (SMA) and change vector analysis (CVA) methods for monitoring and mapping land degradation/desertification in arid and semiarid areas (Sudan), using Landsat imagery.EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES,20,S21-S29.
MLA	Salih, Abdelrahim A. M.,et al."Spectral mixture analysis (SMA) and change vector analysis (CVA) methods for monitoring and mapping land degradation/desertification in arid and semiarid areas (Sudan), using Landsat imagery".EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES 20(2017):S21-S29.