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Original scientific paper

Detecting Forest Damage in Cir Aerial Photographs Using a Neural Network

Damir Klobučar ; »Hrvatske šume« d. o. o. Zagreb, Headquaters Zagreb, CROATIA
Renata Pernar ; Forestry Faculty of Zagreb University, Department of Forest Management and Remote Sensing, CROATIA
Sven Lončarić ; University of Zagreb, Faculty of Electrical Engineering and Computing, Department of Electronic Systems and Information Processing, CROATIA
Marko Subašić ; University of Zagreb, Faculty of Electrical Engineering and Computing, Department of Electronic Systems and Information Processing, CROATIA
Ante Seletković ; Forestry Faculty of Zagreb University, Department of Forest Management and Remote Sensing, CROATIA
Mario Ančić ; Forestry Faculty of Zagreb University, Department of Forest Management and Remote Sensing, CROATIA

Fulltext: english, pdf (626 KB) pages 157-163 downloads: 337* cite
APA 6th Edition
Klobučar, D., Pernar, R., Lončarić, S., Subašić, M., Seletković, A. & Ančić, M. (2010). Detecting Forest Damage in Cir Aerial Photographs Using a Neural Network. Croatian Journal of Forest Engineering, 31 (2), 157-163. Retrieved from https://hrcak.srce.hr/63726
MLA 8th Edition
Klobučar, Damir, et al. "Detecting Forest Damage in Cir Aerial Photographs Using a Neural Network." Croatian Journal of Forest Engineering, vol. 31, no. 2, 2010, pp. 157-163. https://hrcak.srce.hr/63726. Accessed 16 Jun. 2019.
Chicago 17th Edition
Klobučar, Damir, Renata Pernar, Sven Lončarić, Marko Subašić, Ante Seletković and Mario Ančić. "Detecting Forest Damage in Cir Aerial Photographs Using a Neural Network." Croatian Journal of Forest Engineering 31, no. 2 (2010): 157-163. https://hrcak.srce.hr/63726
Harvard
Klobučar, D., et al. (2010). 'Detecting Forest Damage in Cir Aerial Photographs Using a Neural Network', Croatian Journal of Forest Engineering, 31(2), pp. 157-163. Available at: https://hrcak.srce.hr/63726 (Accessed 16 June 2019)
Vancouver
Klobučar D, Pernar R, Lončarić S, Subašić M, Seletković A, Ančić M. Detecting Forest Damage in Cir Aerial Photographs Using a Neural Network. Croatian Journal of Forest Engineering [Internet]. 2010 [cited 2019 June 16];31(2):157-163. Available from: https://hrcak.srce.hr/63726
IEEE
D. Klobučar, R. Pernar, S. Lončarić, M. Subašić, A. Seletković and M. Ančić, "Detecting Forest Damage in Cir Aerial Photographs Using a Neural Network", Croatian Journal of Forest Engineering, vol.31, no. 2, pp. 157-163, 2010. [Online]. Available: https://hrcak.srce.hr/63726. [Accessed: 16 June 2019]

Abstracts
Forest dieback is taking on increasing proportions in many parts of Croatia. To improve the situation, it is of primary importance to acquire timely, accurate and inexpensive information on the scale of forest damage. Such information can be collected for large forest areas with remote sensing techniques. This paper explores the possibility of applying segmentations of color infrared aerial photographs (CIR). Self-organizing artificial neural networks are used to detect damage in beech-fir forests and determine its spatial distribution. The results of the research confirm the benefits of applying neural networks to forest damage detection, since there are no statistically significant differences between damage in the field and damage detected with a neural network.

Keywords
forest damage; color infrared aerial photographs; segmentation; neural networks; Croatia

Hrčak ID: 63726

URI
https://hrcak.srce.hr/63726

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