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ŠUMARSKI LIST 9-10/2008 str. 18     <-- 18 -->        PDF

A. Seletković, R. Pernar, A. Jazbec, M. Ančić: TOČNOST KLASIFIKACIJE SATELITSKE SNIMKE VISOKE ... Šumarski list br. 9–10, CXXXII (2008), 393-404
and IKONOS joint characterization approach. Gj Otočke šume
Remote Sensing of Environment, 88, 17–22. Gj Slavir

**** Osnove gospodarenja: Gj Vrbanjske šume

Gj Kragujna

SUMMARY: Satellite images as a source of information are becoming more
significant and more often used in Croatian forestry. Data in satellite images
can be obtained in two ways – by visual and digital interpretation. Choice
of adequate interpretation is dependant on set goals or, more precisely, on
getting enough quality information needed for certain task. Main objective of
this paper was to examine, compare and find the best way to interpret IKONOS
high spatial resolution satellite images, that would be simple and acceptable
for operational purposes. Research was conducted in Spačva forest basin
area, where largest integral pedunculate oak (Quercus robur L) forest is
situated. Interest array was defined with 1 IKONOS satellite image scene

(11.3 x 11.3 km) and it covers the central part of Spačva forest complex, with
four forest management units: Kragujna, Otočke šume, Slavir, Vrbanjske
šume. The above mentioned shooting produced IKONOS satellite image of
the Spačva basin area, 132 km2 large surface, in 5 spectral channels: PA N
(1 x 1 m) and 4 MS Bundle (4 x 4 m).
Visual interpretation was conducted on the created colorcomposit with
three chosen spectral channels (4, 3, 2), while digital interpretation was conducted
through six different algorithms, on the IKONOS satellite image. For
each algorithm of the supervised classification, as well as the visual interpretation,
Kappa statistics and accuracy parameters of the classification were
calculated. Reference data from field research was compared to results from
different satellite image classification methods to determine the level of accuracy
for each classification. From these comparisons, the error matrix, which
represents the base for accuracy verification, was created. Three accuracy indexes
were derived from the error matrix: total, producers and users index.
Last two refer to each class individually. Apart from the mentioned indexes,
error matrix was also used for calculating the parameters of Kappa statistics,
which enabled data generalization.

Of all the conducted interpretations (classifications), visual interpretation
produced best results – results obtained this way were the closest to the actual
situation in the field (field research, data from forest management plans). Conducted
methods of the IKONOS satellite image supervised classification determined
that the most accurate method for operational application was the feature
extraction classification with natural features recognition module, in
which the unclassified areas are assigned to the most similar class. This research
also confirmed the facts stated by Mas and Ramirez (1996) in their studies,
concerning the claims that, besides being the most used, visual interpretation
method also produced the most accurate results, primarily due to the human
ability to identify objects/events of interest. On the other hand, process itself
lasts relatively long, because each part of the image is analysed separately,
which can significantly increase the time and the costs of the analysis.

K e y w o rd s : IKONOS satellite image, visual and digital interpretation,
classification accuracy, Kappa statistics, accuracy index, Spačva.