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ŠUMARSKI LIST 9-10/2014 str. 49     <-- 49 -->        PDF

situation in a natural mixed forest. The number of studies where WV2 data was used for forest tree species mapping in heterogeneous temperate European forests is very limited. Immitzer et al. (2012) tested the suitability of WV2 data for mapping of 10 tree species in a mid-European mixed forest in Austria. With the use of a non-parametric Random Forests (Breiman, 2001) analyses, the overall accuracy of 82% was reached, which demonstrates the high use potential of WV2 data for forest tree species recognition. Moreover, the new WV2 bands improved classification when a larger number of tree species were analysed. However, they selected training samples by selecting pixels on the sun-lit parts of crowns to read spectral information and not whole crowns to add more complex texture information. Heumann (2011) demonstrated the use of the WV2 sensor, Object-based image analysis (OBIA), and support vector machine (SVM) classification for the classification of mangrove in the Galapagos Archipelago, Ecuador. The overall accuracy achieved for discriminating true mangroves from other vegetation was more than 90%. Similarly, Seletković et al. (2008) used a form of object-based image analyses – features extraction, in a supervised process analysing IKONOS imagery covering an area where a large pedunculate oak forest was situated. They concluded, however, that using IKONOS imagery visual interpretation gains favourable results in comparison to digital interpretation. Moreover, authors warned the time required for visual interpretation and concluded that that specific imagery did not guarantee significant reduction of time and cost needed for the analyses.
Because the satellite multispectral imagery has not yet provided enough spatial detail, for example, to distinguish the texture details of crowns of different tree species, a fusion with airborne laser scanning (LiDAR) data was applied to improve the segmentation and classification process (Ali et al., 2008; Zhang et al., 2012). It has been shown that combining LiDAR with multispectral imagery is a very useful method for monitoring of forest stands and even for individual tree crown mapping (Leckie et al., 2003; Blaschke et al., 2011; Jakubowski et al., 2013).
The review of previous research published in peer-reviewed literature revealed that more research was needed on the application of WV2 imagery for mapping individual tree species in heterogeneous, mixed urban forests of temperate climate, where trees of different species and of different ages often grow very close to each other with their crowns intertwining. Furthermore, a fusion of WV2 and laser scanning data has not been applied for individual tree classification in natural urban forests.
Therefore, this study was aimed toward closing this gap by exploring whether a straightforward method of object-based