干旱区生态环境知识资源中心(Arid): Land cover classification using moderate resolution imaging spectrometer-enhanced vegetation index time-series data and self-organizing map neural network in Inner Mongolia, China

Arid

DOI	10.1117/1.2819344
	Land cover classification using moderate resolution imaging spectrometer-enhanced vegetation index time-series data and self-organizing map neural network in Inner Mongolia, China
	Bagan, Hasi 1; Wang, Qinxue 2; Yang, Yonghui 3; Yasuoka, Yoshifumi 1; Bao, Yuhai 4
通讯作者	Bagan, Hasi
来源期刊	JOURNAL OF APPLIED REMOTE SENSING
ISSN	1931-3195
出版年	2007
卷号	1
英文摘要	The Moderate Resolution Imaging Spectroradiometer (MODIS) data offers a unique combination of spectral, temporal, and spatial resolution in comparison to other global sensors. The MODIS Enhanced Vegetation Index (EVI) product has several advantages, which make it suitable for regional land cover mapping. This paper investigates the application of MODIS EVI time-series data for mapping temperate arid and semi-arid land cover at a moderate resolution (500 m), for regional land-cover/land-use monitoring purposes. A 16-day composite EVI time-series data for 2003 (22 March 2003 - 30 September 2003) was adopted for the study. A land cover map was generated for the Inner Mongolia Autonomous Region using 7 tiles of MODIS EVI time-series data and Self-Organizing Map (SOM) neural network classification. Land-use GIS data, Landsat TM/ETM, and ASTER data were employed as reference data. The results show that the overall accuracy of land cover classification is about 84% with a Kappa coefficient of 0.8170. These results demonstrate that the SOM neural network model could work well for the multi-temporal MODIS EVI data, and suggest a potential of using MODIS EVI time-series remote sensing data to monitor desertification in Inner Mongolia with limited ancillary data and little labor-input in comparison with using high-spatial resolution remote sensing data.
英文关键词	MODIS EVI neural network land cover desertification
类型	Article
语种	英语
国家	Japan ; Peoples R China
收录类别	SCI-E
WOS记录号	WOS:000260914300005
WOS关键词	MODIS ; DESERTIFICATION ; PATTERNS ; IMAGERY ; FUTURE ; USA
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/2XILL650/154712
作者单位	1.Univ Tokyo, Inst Ind Sci, Tokyo 1538505, Japan; 2.Natl Inst Environm Studies, Asian Environm Res Grp, Asia Water Environm Sect, Ibaraki 3058506, Japan; 3.Chinese Acad Sci, Inst Genet & Dev Biol, Ctr Agr Resources Res, Shijiazhuang 050021, Peoples R China; 4.Inner Mongolia Normal Univ, Coll Geog Sci, Inner Mongolia 010022, Peoples R China
推荐引用方式 GB/T 7714	Bagan, Hasi,Wang, Qinxue,Yang, Yonghui,et al. Land cover classification using moderate resolution imaging spectrometer-enhanced vegetation index time-series data and self-organizing map neural network in Inner Mongolia, China[J],2007,1.
APA	Bagan, Hasi,Wang, Qinxue,Yang, Yonghui,Yasuoka, Yoshifumi,&Bao, Yuhai.(2007).Land cover classification using moderate resolution imaging spectrometer-enhanced vegetation index time-series data and self-organizing map neural network in Inner Mongolia, China.JOURNAL OF APPLIED REMOTE SENSING,1.
MLA	Bagan, Hasi,et al."Land cover classification using moderate resolution imaging spectrometer-enhanced vegetation index time-series data and self-organizing map neural network in Inner Mongolia, China".JOURNAL OF APPLIED REMOTE SENSING 1(2007).