Composite indicator for monitoring of Norway spruce stand decline
| Autor: | Emil Cienciala, Tomas Fabianek, Petr Lukes, František Zemek, Radek Russ, Olga Brovkina |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences 0211 other engineering and technologies satellite multispectral data 02 engineering and technology Atmospheric sciences 01 natural sciences lcsh:Oceanography airborne hyperspectral Poor correlation lcsh:GC1-1581 Computers in Earth Sciences 021101 geological & geomatics engineering 0105 earth and related environmental sciences General Environmental Science Remote sensing exergy Spruce forest Multispectral data biology Picea abies Applied Mathematics fungi lcsh:QE1-996.5 Hyperspectral imaging Vegetation Composite indicator biology.organism_classification Reflectivity lcsh:Geology Geography |
| Zdroj: | European Journal of Remote Sensing, Vol 50, Iss 1, Pp 550-563 (2017) |
| ISSN: | 2279-7254 |
| Popis: | The study is aimed to explore the potential of time-series airborne hyperspectral and satellite multispectral data to track the changes in spruce forest decline expressed by a composite spruce decline indicator. Vegetation indices and exergy of solar radiation extracted from remote sensing data are used to predict the development of the composite spruce health indicator. The canopy-level spectral reflectance properties of spruce stands are investigated to identify categories of spruce stand decline: healthy, initial decline, and initial to moderate decline. The sensitivity peaks for initial decline and initial to moderate decline of spruce are shown. The highest potential for the estimation of the composite spruce health indicator is demonstrated by vegetation indices WBI and NDVIred_edge from airborne hyperspectral data, and by PSRI, NDII and exergy of solar radiation from Landsat and Sentinel-2 satellite multispectral data. MODIS data show only a poor correlation between the composite spruce stand health indicator and NDII index. The proposed methodology to obtain the distribution of the composite spruce decline indicator using remote sensing (RS) data promisingly suggests its applicability over a large forest area with potential time and economic benefits, since foliar spectral measurements, canopy chemistry, and laboratory analysis are not required. |
| Databáze: | OpenAIRE |
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