Hyperspectral remote sensing - an effective method for large-scale monitoring of early stages of spruce damage
2001
Rock, B. N. (University of New Hampshire, Durham (USA). Complex Systems Research Center)
The massive forest decline phenomenon in the Krusne hory, Czech Republic has been described since the early 1950s and is attributed to the combination of severe atmospheric pollution and climatic conditions. These mountains trend southwest-to-northeast, along a gradient of atmospheric deposition from heavy to light related to the distance from pollution sources. Standard field evaluation methods for assigning damage classes to individual trees or forest stands are mainly based on visual assessment of macroscopic changes and needle loss occur, alterations in metabolic pathways lead to changes exhibited at the cellular level. Foliar damage related to anatomical structure and chemical composition can be assessed from plant spectral reflectance data at certain wavelength or by use of different spectral indexes. Moreover, spectral reflectance of leaves can be also used as an estimate of the concentration of photosynthetic pigments, water content and chemical composition of plants. Thus, markers of damage at the structural and metabolic levels can serve as a means of previsual damage detection. These reflectance features can also serve as the basis for efficient interpretation of hyperspectral remote sensing data
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