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DOI	10.1016/j.ejrs.2015.09.005
	Improved Land-use/Land-cover classification of semi-arid deciduous forest landscape using thermal remote sensing
	Sinha, Suman; Sharma, Laxmi Kant; Nathawat, Mahendra Singh
通讯作者	Sinha, S
来源期刊	EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES
ISSN	1110-9823
EISSN	2090-2476
出版年	2015
卷号	18 期号:2 页码:217-233
英文摘要	Land Use Land Cover (LULC) change detection helps the policy makers to understand the environmental change dynamics to ensure sustainable development. Hence, LULC feature identification has emerged as an important research aspect and thus, a proper and accurate methodology for LULC classification is the need of time. In this study, Landsat-7 satellite data captured by Enhanced Thematic Mapper (ETM+) were used for LULC classification employing the maximum likelihood supervised classification (MLC) algorithm. The study targets the improvement of classification accuracy with the combined use of thermal and spectral information from satellite imagery. Land surface temperature (LST) is sensitive to land surface features and hence can be used to extract information on LULC features. The classification accuracy was found to improve on integrating the thermal information from the thermal band of Landsat ETM+ with spectral information. Two thermal vegetation indices, namely Thermal Integrated Vegetation Index (TLIVI) and Advanced Thermal Integrated Vegetation Index (ATLIVI), proposed in this study showed fairly good correlations (R-2 = 0.65 and 0.7, respectively) with the derived surface temperature. These indices based on empirical parameterization of the relationship between surface temperature (T-s) and vegetation indices showed an increase of nearly 6% in the overall accuracy for land-use/ land-cover (LULC) classification in comparison to MLC algorithm using Standard False Colour Composite (FCC) satellite image of Landsat ETM+ as reference. (C) 2015 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.
英文关键词	Land Use Land Cover (LULC) Classification Landsat ETM+ Land surface temperature (LST) Thermal Vegetation Index (TVI) Land surface features
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:000216589700008
WOS关键词	LEAF-AREA INDEX ; ENHANCED VEGETATION INDEX ; SURFACE-TEMPERATURE ; ENERGY-BALANCE ; SOIL-MOISTURE ; MODIS ; DISTRICT ; CLIMATE ; NDVI ; UTTARAKHAND
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/2XILL650/331062
作者单位	[Sinha, Suman] Birla Inst Technol, Dept Remote Sensing, Ranchi 835215, Jharkhand, India; [Sharma, Laxmi Kant] Cent Univ Jharkhand, Ctr Land Resource Management, Ranchi 835205, Bihar, India; [Nathawat, Mahendra Singh] Indira Gandhi Natl Open Univ IGNOU, Sch Sci, New Delhi 110068, India
推荐引用方式 GB/T 7714	Sinha, Suman,Sharma, Laxmi Kant,Nathawat, Mahendra Singh. Improved Land-use/Land-cover classification of semi-arid deciduous forest landscape using thermal remote sensing[J],2015,18(2):217-233.
APA	Sinha, Suman,Sharma, Laxmi Kant,&Nathawat, Mahendra Singh.(2015).Improved Land-use/Land-cover classification of semi-arid deciduous forest landscape using thermal remote sensing.EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES,18(2),217-233.
MLA	Sinha, Suman,et al."Improved Land-use/Land-cover classification of semi-arid deciduous forest landscape using thermal remote sensing".EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES 18.2(2015):217-233.