DOI: 10.1016/j.jag.2012.10.001
Scopus记录号: 2-s2.0-84880273407
论文题名: Mapping land cover gradients through analysis of hyper-temporal NDVI imagery
作者: Ali A ; , de Bie C ; A ; J ; M ; , Skidmore A ; K ; , Scarrott R ; G ; , Hamad A ; , Venus V ; , Lymberakis P
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2013
卷: 23, 期: 1 起始页码: 301
结束页码: 312
语种: 英语
英文关键词: Gradient
; Hyper-temporal
; Land cover
; Mapping
; MODIS
; NDVI
Scopus关键词: land cover
; MODIS
; NDVI
; satellite data
; satellite imagery
; spatiotemporal analysis
; vegetation cover
; vegetation mapping
英文摘要: The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but typically fail to express such differences as gradients. Present interpretation techniques still make insufficient use of freely available spatial-temporal Earth Observation (EO) data that allow detection of existing land cover gradients. This study explores the use of hyper-temporal NDVI imagery to detect and delineate land cover gradients analyzing the temporal behavior of NDVI values. MODIS-Terra MVC-images (250 m, 16-day) of Crete, Greece, from February 2000 to July 2009 are used. The analysis approach uses an ISODATA unsupervised classification in combination with a Hierarchical Clustering Analysis (HCA). Clustering of class-specific temporal NDVI profiles through HCA resulted in the identification of gradients in landcover vegetation growth patterns. The detected gradients were arranged in a relational diagram, and mapped. Three groups of NDVI-classes were evaluated by correlating their class-specific annual average NDVI values with the field data (tree, shrub, grass, bare soil, stone, litter fraction covers). Multiple regression analysis showed that within each NDVI group, the fraction cover data were linearly related with the NDVI data, while NDVI groups were significantly different with respect to tree cover (adj. R2 = 0.96), shrub cover (adj. R2 = 0.83), grass cover (adj. R2 = 0.71), bare soil (adj. R2 = 0.88), stone cover (adj. R2 = 0.83) and litter cover (adj. R2 = 0.69) fractions. Similarly, the mean Sorenson dissimilarity values were found high and significant at confidence interval of 95% in all pairs of three NDVI groups. The study demonstrates that hyper-temporal NDVI imagery can successfully detect and map land cover gradients. The results may improve land cover assessment and aid in agricultural and ecological studies. © 2012 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79870
Appears in Collections: 气候变化事实与影响
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作者单位: Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE Enschede, Netherlands; Pakistan Space and Upper Atmosphere Research Commission (SUPARCO), Sector 28, Gulzar-e-Hijri, Karachi 75270, Pakistan; Coastal and Marine Research Centre, Environmental Research Institute, University College Cork, County Cork, Ireland; Natural History Museum of Crete, University of Crete, P.O. Box 2208, GR-71409 Irakleio, Crete, Greece
Recommended Citation:
Ali A,, de Bie C,A,et al. Mapping land cover gradients through analysis of hyper-temporal NDVI imagery[J]. International Journal of Applied Earth Observation and Geoinformation,2013-01-01,23(1)