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Šumarski list, Vol. 141 No. 1-2, 2017.

Izvorni znanstveni članak
https://doi.org/10.31298/sl.141.1-2.3

Positional accuracy assessment of forest area boundaries obtained by object – oriented classification of multispectral imagery

Nedim Tuno   ORCID icon orcid.org/0000-0002-1358-8435 ; Univerzitet u Sarajevu, Građevinski fakultet, Odsjek za geodeziju, BiH
Admir Mulahusić   ORCID icon orcid.org/0000-0002-9727-8708 ; Univerzitet u Sarajevu, Građevinski fakultet, Odsjek za geodeziju, BiH
Jusuf Topoljak ; Univerzitet u Sarajevu, Građevinski fakultet, Odsjek za geodeziju, BiH
Alma Elezović ; Općina Visoko, Visoko, BiH

Puni tekst: hrvatski, pdf (3 MB) str. 29-38 preuzimanja: 103* citiraj
APA 6th Edition
Tuno, N., Mulahusić, A., Topoljak, J. i Elezović, A. (2017). Ispitivanje položajne točnosti granica šumskih područja dobivenih objektno – orijentiranom klasifikacijom multispektralnih snimaka. Šumarski list, 141 (1-2), 29-38. https://doi.org/10.31298/sl.141.1-2.3
MLA 8th Edition
Tuno, Nedim, et al. "Ispitivanje položajne točnosti granica šumskih područja dobivenih objektno – orijentiranom klasifikacijom multispektralnih snimaka." Šumarski list, vol. 141, br. 1-2, 2017, str. 29-38. https://doi.org/10.31298/sl.141.1-2.3. Citirano 17.02.2019.
Chicago 17th Edition
Tuno, Nedim, Admir Mulahusić, Jusuf Topoljak i Alma Elezović. "Ispitivanje položajne točnosti granica šumskih područja dobivenih objektno – orijentiranom klasifikacijom multispektralnih snimaka." Šumarski list 141, br. 1-2 (2017): 29-38. https://doi.org/10.31298/sl.141.1-2.3
Harvard
Tuno, N., et al. (2017). 'Ispitivanje položajne točnosti granica šumskih područja dobivenih objektno – orijentiranom klasifikacijom multispektralnih snimaka', Šumarski list, 141(1-2), str. 29-38. doi: https://doi.org/10.31298/sl.141.1-2.3
Vancouver
Tuno N, Mulahusić A, Topoljak J, Elezović A. Ispitivanje položajne točnosti granica šumskih područja dobivenih objektno – orijentiranom klasifikacijom multispektralnih snimaka. Šumarski list [Internet]. 2017 [pristupljeno 17.02.2019.];141(1-2):29-38. doi: https://doi.org/10.31298/sl.141.1-2.3
IEEE
N. Tuno, A. Mulahusić, J. Topoljak i A. Elezović, "Ispitivanje položajne točnosti granica šumskih područja dobivenih objektno – orijentiranom klasifikacijom multispektralnih snimaka", Šumarski list, vol.141, br. 1-2, str. 29-38, 2017. [Online]. doi: https://doi.org/10.31298/sl.141.1-2.3

Sažetak
Knowledge about positional accuracy of forest geospatial information, obtained by interpretation of satellite imagery, is of great significance. The consequences of the decisions that are based on data with insufficient or unknown quality could be very negative. This paper investigates the accuracy of closed linear shapes that represented boundaries of forest cover. Forest areas are effectively extracted from Landsat image by implementing the process of multiresolution image segmentation (figure 4), using all bands. Multispectral classification of defined segments was performed by special rules. The results of object-oriented classification showed that an overall accuracy from 99 reference points was better than 90 % (table 1), which can be considered as a very good result. The number of forest polygons, obtained by satellite imagery classification, was reduced by 37 times by cartographic aggregation (figure 5). The Polynomial Approximation with Exponential Kernel (PAEK) method was used for cartographic smoothing of the forest polygons, which smoothes lines in relation to a softening tolerance (tolerances from 30 m to 180 m were used in this research) (figure 6). The positional accuracy assessment of the boundary of forest areas, based on procedure of comparing a tested lines to a reference lines, showed that the best results were obtained by PAEK smoothing with 150 m and 180 m tolerances (CMAS = 49 m, according to STANAG 2215) (tables 2 and 3, figure 8).
The findings of this empirical research showed that cartographic generalization contributes to improvement of the forest boundaries accuracy, as well as the appropriate processing of the medium spatial resolution remotely sensed data can result in satisfactory quality of vector data.

Ključne riječi
Landsat; object-oriented forest classification; cartographic generalization; positional accuracy

Hrčak ID: 175787

URI
https://hrcak.srce.hr/175787

[hrvatski]

Posjeta: 243 *