Assessment of some forest characteristics employing IKONOS satellite data

Ľ. Scheer and R. Sitko
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Ľ. Scheer: Faculty of Forestry, Technical University in Zvolen, Zvolen, Slovak Republic
R. Sitko: Faculty of Forestry, Technical University in Zvolen, Zvolen, Slovak Republic

Journal of Forest Science, 2007, vol. 53, issue 8, 345-351

Abstract: In recent years, satellite remote sensing has become a new tool for estimation of forest condition. The paper deals with spruce timber growing stock and vegetation cover assessment employing IKONOS satellite data from a mountain forest area of Central Slovakia. Original digital data as well as enhanced digital images were used to estimate some forest variables. Image enhancement approaches employing topographic normalization, PCA analysis and different vegetation indices are a very important part of data processing. Apart from spectral characteristics, texture as an additional variable was utilized. In order to improve classification accuracy the knowledge of the vertical distribution of tree species also was incorporated into classifiers. Spectral signatures as auxiliary variables measured with the aid of training sets were utilized for the construction of spectral models for growing stock estimation. In spite of the fact that the standard error of these models is not very favourable as it varies about 30%, they offer initial information for application of different sampling designs for timber growing stock assessment, where the final precision is acceptable. Stepwise discriminant analysis was employed to choose appropriate sets for the classification of vegetation cover. Classification results show an assumed contribution of categorial knowledge for increasing the correctly classified pixel proportion and this improvement was on average about 10%. Likewise, the texture contributes to better resolution of some very near spectral classes.

Keywords: IKONOS; timber growing stock; texture; categorial knowledge; vegetation cover (search for similar items in EconPapers)
Date: 2007
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DOI: 10.17221/2181-JFS

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