OBJECT-BASED CLASSIFICATION OF ULTRACAMD IMAGERY FOR IDENTIFICATION OF TREE SPECIES IN THE MIXED PLANTED FOREST

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RAFIEYAN O.; DARVISHSEFAT A.A.; BABAII S.; MATAJI A.

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Paper Information

Journal: CASPIAN JOURNAL OF ENVIRONMENTAL SCIENCES (CJES) Year:2011 | Volume:9 | Issue:1 Page(s): 67-79

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Title

OBJECT-BASED CLASSIFICATION OF ULTRACAMD IMAGERY FOR IDENTIFICATION OF TREE SPECIES IN THE MIXED PLANTED FOREST

Author(s)

RAFIEYAN O. | DARVISHSEFAT A.A. | BABAII S. | MATAJI A. | Issue Writer Certificate

Keywords

TREE SPECIES IDENTIFICATIONQ3

OBJECT-BASED CLASSIFICATIONQ3

CLASS HIERARCHYQ3

IMAGE OBJECT HIERARCHYQ3

ULTRACAMDQ3

Abstract

This study is a contribution to assess the high resolution digital aerial imagery for semi-automatic analysis of TREE SPECIES IDENTIFICATION. To maximize the benefit of such data, the OBJECT-BASED CLASSIFICATION was conducted in a mixed forest plantation. Two subsets of an UltraCam D image were geometrically corrected using aero-triangulation method. Some appropriate transformations were performed and utilized. Segmentation was conducted stepwise at two levels and a hierarchical image object network was constructed. The classification hierarchy was developed and Nearest Neighbor classifier, using integration of different features was performed. Training samples and ground truth map were prepared through fieldwork. Accuracy assessment of the resulting maps in comparison with reference data showed overall accuracies and Kappa Index of Agreement of 90.2%, 0.82 (Area1) and 69.8%, 0.49 (Area2), respectively. Transformed images were advantageous to improve the results. The lower accuracy in Area2 can be attributed to high diversity and heterogeneous mixture of species. More detailed and accurate mapping of tree species would be fulfilled applying precise 3D data. The accuracy of detailed vegetation classification with very high-resolution imagery is highly dependent on the segmentation quality, sample size, sampling quality, classification framework and ground vegetation distribution and mixture.

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APA: Copy

RAFIEYAN, O., DARVISHSEFAT, A.A., BABAII, S., & MATAJI, A.. (2011). OBJECT-BASED CLASSIFICATION OF ULTRACAMD IMAGERY FOR IDENTIFICATION OF TREE SPECIES IN THE MIXED PLANTED FOREST. CASPIAN JOURNAL OF ENVIRONMENTAL SCIENCES (CJES), 9(1), 67-79. SID. https://sid.ir/paper/240737/en

Vancouver: Copy

RAFIEYAN O., DARVISHSEFAT A.A., BABAII S., MATAJI A.. OBJECT-BASED CLASSIFICATION OF ULTRACAMD IMAGERY FOR IDENTIFICATION OF TREE SPECIES IN THE MIXED PLANTED FOREST. CASPIAN JOURNAL OF ENVIRONMENTAL SCIENCES (CJES)[Internet]. 2011;9(1):67-79. Available from: https://sid.ir/paper/240737/en

IEEE: Copy

O. RAFIEYAN, A.A. DARVISHSEFAT, S. BABAII, and A. MATAJI, “OBJECT-BASED CLASSIFICATION OF ULTRACAMD IMAGERY FOR IDENTIFICATION OF TREE SPECIES IN THE MIXED PLANTED FOREST,” CASPIAN JOURNAL OF ENVIRONMENTAL SCIENCES (CJES), vol. 9, no. 1, pp. 67–79, 2011, [Online]. Available: https://sid.ir/paper/240737/en

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