DOI: 10.1016/j.foreco.2013.07.043
Scopus记录号: 2-s2.0-84884329878
论文题名: Forecasting potential bark beetle outbreaks based on spruce forest vitality using hyperspectral remote-sensing techniques at different scales
作者: Lausch A. ; Heurich M. ; Gordalla D. ; Dobner H.-J. ; Gwillym-Margianto S. ; Salbach C.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2013
卷: 308 起始页码: 76
结束页码: 89
语种: 英语
英文关键词: Attack
; Bark beetle
; Hyperspectral remote sensing
; Ips typographus (L.)
; Spruce forest
; Vitality
Scopus关键词: Attack
; Bark beetle
; Hyperspectral remote sensing
; Ips typographus
; Spruce forest
; Vitality
; Climate change
; Remote sensing
; Vegetation
; Forestry
; absorption
; accuracy assessment
; beetle
; chlorophyll
; climate change
; coniferous forest
; pest outbreak
; remote sensing
; vegetation index
; water content
; Forestry
; Insects
; Plants
; Remote Sensing
; Seasonal Variation
; Bavaria
; Bavarian Forest National Park
; Germany
英文摘要: The bark beetle (Ips typographus L.) is known for the detrimental impact it can have on Europe's mature spruce forests with bark beetle outbreaks already having devastated thousands of hectares of spruce forests in Germany. This study analysed the hypothesis that the vitality of spruce vegetation is already susceptible from factors such as climate change or emissions to a certain extent before infestation, so that the role of the subsequent bark beetle infestation is only secondary.Hyperspectral remote-sensing techniques were used to detect changes in biochemical-biophysical vegetation characteristics in the spruce forest of the Bavarian Forest National Park, Germany. For this study, several spectral bands, vegetation indices and specific spectral band combinations of hyperspectral HyMAP remote-sensing data with a 4. m and a 7. m ground resolution were analysed and compared in terms of their classification accuracy, generating an ID3 decision tree.The vitality classes and thus also the attack stages of the spruce vegetation could be estimated with moderate to good accuracy using hyperspectral remote-sensing data. Clear spectral differences between the class with spruce trees that were still green but with reduced vitality (possibly the first stages of green-attack) and the class with healthy spruce trees could be ascertained. The best spectral characteristics, spectral indicators and spectral derivatives related to vitality classes and thus attack stages were typically based on wavebands related to prominent chlorophyll absorption features in the VI within the spectral range of 450-890. nm. Only limited spectral information and derivatives could be found in the short-wave infrared region 1 (SWIR) within the spectral range of 1400-1800. nm, which reflects the water content of the spruce needles. The class of spruce trees that were still green but with reduced vitality (possibly the first stages of green-attack) showed a trend towards detectability and differentiation with spectral indicators and index derivatives. However, the prediction of observed effects with 64% accuracy as observed here is regarded as insufficient in forestry practises. Hyperspectral data with a ground resolution of 4. m were found to contain more information relevant to estimating the vitality class of spruce vegetation compared to hyperspectral data with a ground resolution of 7. m. © 2013 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/66357
Appears in Collections: 影响、适应和脆弱性
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作者单位: UFZ, Helmholtz Centre for Environmental Research - UFZ, Department of Computational Landscape Ecology, Permoserstraße 15, D-04318 Leipzig, Germany; Bavarian Forest National Park, D-94481 Grafenau, Germany; Leipzig University of Applied Science - HTWK Leipzig, Karl-Liebknecht-Straße 132, D-04277 Leipzig, Germany; UFZ, Helmholtz Centre for Environmental Research - UFZ, Department of Community Ecology, Theodor-Lieser-Straße 4, D-06120 Halle, Germany
Recommended Citation:
Lausch A.,Heurich M.,Gordalla D.,et al. Forecasting potential bark beetle outbreaks based on spruce forest vitality using hyperspectral remote-sensing techniques at different scales[J]. Forest Ecology and Management,2013-01-01,308