干旱区生态环境知识资源中心(Arid): Applying Multi-Index Approach from Sentinel-2 Imagery to Extract Urban Areas in Dry Season (Semi-Arid Land in North East Algeria)

Arid

DOI	10.4995/raet.2020.13787
	Applying Multi-Index Approach from Sentinel-2 Imagery to Extract Urban Areas in Dry Season (Semi-Arid Land in North East Algeria)
	Rouibah, K.; Belabbas, M.
通讯作者	Rouibah, K
来源期刊	REVISTA DE TELEDETECCION
ISSN	1133-0953
EISSN	1988-8740
出版年	2020
期号	56 页码:89-101
英文摘要	The mapping of urban areas mostly presents a big difficulty, particularly, in arid and semi-arid environments. For that reason, in this research, we expect to increase built up accuracy mapping for Bordj Bou Arreridj city in semi-arid regions (North-East Algeria) by focusing on the identification of appropriate combination of the remotely sensed spectral indices. The study applies the 'k-means' classifier. In this regard, four spectral indexes were selected, namely normalized difference tillage index (NDTI) for built-up, and both bare soil index (BSI) and dry bare-soil index (DBSI), which are related to bare soil, as well as the normalized difference vegetation index (NOVI). All previous spectral indices mentioned were derived from Sentinel-2 data acquired during the dry season. Two combinations of them were generated using layer stack process, keeping both of NDTI and NDVI index constant in both combinations so that the multi-index NDTI/BSI/NDVI was the first single dataset combination, and the multi-index NDTI/DBSI/NDVI as the second component. The results show that BSI index works better with WTI index compared to the use of DBSI index. Therefore, BSI index provides improvements: bare soil classes and builtup were better discriminated, where the overall accuracy increased by 5.67% and the kappa coefficient increased by 12.05%. The use of k-means as unsupervised classifier provides an automatic and a rapid urban area detection. Therefore, the multi-index dataset NDTI/BSI/NDVI was suitable for mapping the cities in dry climate, and could provide a better urban management and future remote sensing applications in semi-arid areas particularly.
英文关键词	Sentinel-2 multi-index dataset built-up area bare soil semi-arid land
类型	Article
语种	英语
开放获取类型	Other Gold
收录类别	ESCI
WOS记录号	WOS:000594637700007
WOS关键词	COVER CLASSIFICATION ACCURACY ; BUILT-UP INDEX ; SPECTRAL INDEXES ; FEATURES
WOS类目	Remote Sensing
WOS研究方向	Remote Sensing
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/334776
作者单位	[Rouibah, K.; Belabbas, M.] USTHB Houari Boumediene Sci & Technol Univ, FSTGAT, Dept Geog & Terr Planning, POB 32, Algiers 16111, Algeria
推荐引用方式 GB/T 7714	Rouibah, K.,Belabbas, M.. Applying Multi-Index Approach from Sentinel-2 Imagery to Extract Urban Areas in Dry Season (Semi-Arid Land in North East Algeria)[J],2020(56):89-101.
APA	Rouibah, K.,&Belabbas, M..(2020).Applying Multi-Index Approach from Sentinel-2 Imagery to Extract Urban Areas in Dry Season (Semi-Arid Land in North East Algeria).REVISTA DE TELEDETECCION(56),89-101.
MLA	Rouibah, K.,et al."Applying Multi-Index Approach from Sentinel-2 Imagery to Extract Urban Areas in Dry Season (Semi-Arid Land in North East Algeria)".REVISTA DE TELEDETECCION .56(2020):89-101.