DOI: 10.1016/j.jag.2012.10.006
Scopus记录号: 2-s2.0-84880315804
论文题名: Field hyperspectral data analysis for discriminating spectral behavior of tea plantations under various management practices
作者: Kumar A ; , Manjunath K ; R ; , Meenakshi, Bala R ; , Suda R ; K ; , Singh R ; D ; , Panigrahy S
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2013
卷: 23, 期: 1 起始页码: 352
结束页码: 359
语种: 英语
英文关键词: Camellia sinensis
; Discriminant analysis
; Hyperspectral
; Kangra
; Principal components
; Spectroradiometer
; Wilks' Lambda
Scopus关键词: crop production
; crop yield
; discriminant analysis
; management practice
; plantation
; principal component analysis
; satellite data
; satellite imagery
; spectral resolution
; tea
; Camellia sinensis
英文摘要: The quality and yield of tea depends upon management of tea plantations, which takes into account the factors like type, age of plantation, growth stage, pruning status, light conditions, and disease incidence. Recognizing the importance of hyperspectral data in detecting minute spectral variations in vegetation, the present study was conducted to explore applicability of such data in evaluating these factors. Also stepwise discriminant analysis and principal component analysis were conducted to identify the appropriate bands for accessing the above mentioned factors. The Green region followed by NIR region was found as most appropriate best band for discriminating different types of tea plants, and the tea in sunlit and shade condition. For discriminating age of plantation, growth stage of tea, and diseased and healthy bush, Blue region was most appropriate. The Red and NIR regions were best bands to discriminate pruned and unpruned tea. The study concluded that field hyperspectral data can be efficiently used to know the plantation that need special care and may be an indicator of tea productivity. The spectral signature of these characteristics of tea plantations may also be used to classify the hyperspectral satellite data to derive these parameters at regional scale. © 2012 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79815
Appears in Collections: 气候变化事实与影响
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作者单位: CSIR - Institute of Himalayan Bioresource Technology, Council of Scientific and Industrial Research (CSIR), Palampur, Himachal Pradesh, India; Space Applications Centre, Indian Space Research Organisation (ISRO), Ahmedabad, Gujarat, India
Recommended Citation:
Kumar A,, Manjunath K,R,et al. Field hyperspectral data analysis for discriminating spectral behavior of tea plantations under various management practices[J]. International Journal of Applied Earth Observation and Geoinformation,2013-01-01,23(1)