Abstract
This study investigates the suitability of object- and pixel-based approaches for extraction of hazelnut trees from high resolution digital orthophoto maps. For object-based approach, simple linear iterative clustering (SLIC) method was employed to segment image pixels into homogeneous regions. Features spanning spectral, spatial and textural domains were extracted from each segment then classification was performed by employing support vector machine (SVM) classifier. For pixel-based approach, the spectral reflectance information from all four bands were used as features and applied maximum likelihood (ML) classifier for classification of each pixel into hazelnut and other tree species classes. An area-based approach was used to evaluate the performance of the proposed method. The experiments showed that overall classification accuracy for object-based method was superior to the pixel-based method. Using object-based approach the overall accuracy obtained was 86% while pixel-based approach scored 76%.
Original language | English |
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Pages (from-to) | 561-567 |
Number of pages | 7 |
Journal | Fresenius Environmental Bulletin |
Volume | 28 |
Issue number | 2 |
Publication status | Published - 2019 |
Bibliographical note
Publisher Copyright:© 2019 Parlar Scientific Publications. All rights reserved.
Funding
The authors would like to thank EMI Group Inc., Turkey for providing aerial imagery and reference data. This study was part of a project funded by TUBITAK under grant no. 7140512. Theprojectwas supervised by EMI Group-Turkey, and consulted by Prof.Dr.B.Bayram.
Funders | Funder number |
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EMI Group Inc. | |
TUBITAK | 7140512 |
Keywords
- Maximum likelihood
- Simple linear iterative clustering
- Support vector machine
- Tree species classification