Characterising invasive non-native Rhododendron ponticum spectra signatures with spectroradiometry in the laboratory and field: Potential for remote mapping

被引:11
|
作者
Taylor, Sarah L. [1 ]
Hill, Ross A. [2 ]
Edwards, Colin [3 ]
机构
[1] Keele Univ, Sch Life Sci, Keele ST5 5BG, Staffs, England
[2] Bournemouth Univ, Sch Appl Sci, Poole BH12 5BB, Dorset, England
[3] Forest Res, No Res Stn, Roslin, Midlothian, Scotland
关键词
Hyperspectral remote sensing; Invasive species; Logistic regression; Species discrimination; Leaf plasticity; LEAF WATER-CONTENT; REFLECTANCE; PLANTS;
D O I
10.1016/j.isprsjprs.2013.04.003
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Compared with traditional ground surveys, remote sensing has the potential to map the spatial extent of non-native invasive species rapidly and reliably. This paper assesses the potential of spectroradiometry to distinguish and characterise the status of invasive non-native rhododendron (Rhododendron ponticum). Absolute reflectance of target plant material was measured with an ASD Fieldspec Pro System under standardised laboratory conditions and in the field to characterise spectral signatures in the winter, during leaf-off conditions for woodland overstory, and in the summer when mature rhododendrons are flowering. A logistic regression model of absolute reflectance at key wavelengths (490, 550, 610, 1040 and 1490 nm) was used to determine the success of discriminating rhododendron from three other shrubby species likely to be encountered in woodlands during the winter. The logistic regression model was highly significant (p < 0.001), with 93.5% of 246 leaf sets correctly identified as rhododendron or non-rhododendron (i.e. cherry laurel (Prunus laurocerasus), holly (Ilex aquifolium), and beech (Fagus sylvatica)). Rescaling the data to emulate the spectral resolution of airborne and satellite acquired data decreased the total success rate of correctly identifying rhododendron by only 0.4%; although this error rate will likely increase for airborne or satellite data as a result of atmospheric attenuation and reduced spatial resolution. This demonstrates the potential to map bush presence using hyperspectral data and indicates the optimum spectral wavelengths required. Such information is critical to the development of successful strategic management plans to eradicate rhododendron (and the associated Phytophthora ramorum pathogen) effectively from a site. (C) 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.
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页码:70 / 81
页数:12
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