hrcak mascot   Srce   HID

Prethodno priopćenje

Artificial Neural Networks in the Assessment of Stand Parameters from an IKONOS Satellite Image

Damir Klobučar ; »Hrvatske šume« d.o.o. Zagreb Farka{a Vukotinovi}a 2 HR–10000 Zagreb CROATIA
Renata Pernar ; Forestry Faculty of Zagreb University Sveto{imunska 25 HR–10000 Zagreb CROATIA
Sven Lončarić ; University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 HR–10000 Zagreb CROATIA
Marko Subašić ; University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 HR–10000 Zagreb CROATIA

Puni tekst: engleski, pdf (413 KB) str. 201-211 preuzimanja: 826* citiraj
APA 6th Edition
Klobučar, D., Pernar, R., Lončarić, S. i Subašić, M. (2008). Artificial Neural Networks in the Assessment of Stand Parameters from an IKONOS Satellite Image. Croatian Journal of Forest Engineering, 29 (2), 201-211. Preuzeto s https://hrcak.srce.hr/32195
MLA 8th Edition
Klobučar, Damir, et al. "Artificial Neural Networks in the Assessment of Stand Parameters from an IKONOS Satellite Image." Croatian Journal of Forest Engineering, vol. 29, br. 2, 2008, str. 201-211. https://hrcak.srce.hr/32195. Citirano 28.09.2021.
Chicago 17th Edition
Klobučar, Damir, Renata Pernar, Sven Lončarić i Marko Subašić. "Artificial Neural Networks in the Assessment of Stand Parameters from an IKONOS Satellite Image." Croatian Journal of Forest Engineering 29, br. 2 (2008): 201-211. https://hrcak.srce.hr/32195
Harvard
Klobučar, D., et al. (2008). 'Artificial Neural Networks in the Assessment of Stand Parameters from an IKONOS Satellite Image', Croatian Journal of Forest Engineering, 29(2), str. 201-211. Preuzeto s: https://hrcak.srce.hr/32195 (Datum pristupa: 28.09.2021.)
Vancouver
Klobučar D, Pernar R, Lončarić S, Subašić M. Artificial Neural Networks in the Assessment of Stand Parameters from an IKONOS Satellite Image. Croatian Journal of Forest Engineering [Internet]. 2008 [pristupljeno 28.09.2021.];29(2):201-211. Dostupno na: https://hrcak.srce.hr/32195
IEEE
D. Klobučar, R. Pernar, S. Lončarić i M. Subašić, "Artificial Neural Networks in the Assessment of Stand Parameters from an IKONOS Satellite Image", Croatian Journal of Forest Engineering, vol.29, br. 2, str. 201-211, 2008. [Online]. Dostupno na: https://hrcak.srce.hr/32195. [Citirano: 28.09.2021.]

Sažetak
The paper explores the possibilities of assessing five stand parameters (tree number, volume, stocking, basal area and stand age) with the application of a multi-layer perceptron artificial neural network. An IKONOS satellite image (PAN 1 m x 1 m) was used to asses parts of stands in the sixth (121–140 yrs) and seventh (141–160 yrs) age class of pedunculate oak management class in the »Slavir« Management Unit of Otok Forest Office. Six features extracted from the first order histogram and five texture features extracted from the second order histogram were used as input data for neural network training. Data from the Management Plan were used as outputs of the neural network. An early stopping method and scaled conjugate gradient algorithm with error back propagation were used to improve generalization property of the neural network. Two neural network models were applied to assess the required stand parameters. The first model has one neuron in the output layer, where separate neuron network training was conducted for each stand parameter. The second model has five neurons in the output layer related to five assessed stand parameters. Both networks were trained and tested simultaneously. The conducted research showed that both of these neuron network models have good generalization properties. However, further analysis gave precedence to the second neural network model. Assessment of five quantitative stand parameters did not show any statistically significant differences between the Management Plan data and the neuron network model in terms of tree number, volume, stocking, basal area and stand age analysis.

Ključne riječi
artificial neuron networks; IKONOS – 2; stand parameter assessment; texture

Hrčak ID: 32195

URI
https://hrcak.srce.hr/32195

Posjeta: 1.153 *