Research Papers

Parameter optimization of image classification techniques to delineate crowns of coppice trees on UltraCam-D aerial imagery in woodlands

[+] Author Affiliations
Yousef Erfanifard

Shiraz University, College of Agriculture, Department of Natural Resources and Environment, 7144165186 Shiraz, Iran

Krzysztof Stereńczak

Forest Research Institute (IBL), Sękocin Stary, 3 Braci Leśnej Street, 05-090 Raszyn, Warsaw, Poland

Negin Behnia

Shiraz University, College of Agriculture, Department of Natural Resources and Environment, 7144165186 Shiraz, Iran

J. Appl. Remote Sens. 8(1), 083520 (Nov 11, 2014). doi:10.1117/1.JRS.8.083520
History: Received May 3, 2014; Accepted October 17, 2014
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Abstract.  Estimating the optimal parameters of some classification techniques becomes their negative aspect as it affects their performance for a given dataset and reduces classification accuracy. It was aimed to optimize the combination of effective parameters of support vector machine (SVM), artificial neural network (ANN), and object-based image analysis (OBIA) classification techniques by the Taguchi method. The optimized techniques were applied to delineate crowns of Persian oak coppice trees on UltraCam-D very high spatial resolution aerial imagery in Zagros semiarid woodlands, Iran. The imagery was classified and the maps were assessed by receiver operating characteristic curve and other performance metrics. The results showed that Taguchi is a robust approach to optimize the combination of effective parameters in these image classification techniques. The area under curve (AUC) showed that the optimized OBIA could well discriminate tree crowns on the imagery (AUC=0.897), while SVM and ANN yielded slightly less AUC performances of 0.819 and 0.850, respectively. The indices of accuracy (0.999) and precision (0.999) and performance metrics of specificity (0.999) and sensitivity (0.999) in the optimized OBIA were higher than with other techniques. The optimization of effective parameters of image classification techniques by the Taguchi method, thus, provided encouraging results to discriminate the crowns of Persian oak coppice trees on UltraCam-D aerial imagery in Zagros semiarid woodlands.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Yousef Erfanifard ; Krzysztof Stereńczak and Negin Behnia
"Parameter optimization of image classification techniques to delineate crowns of coppice trees on UltraCam-D aerial imagery in woodlands", J. Appl. Remote Sens. 8(1), 083520 (Nov 11, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083520


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