CAPABILITY INVESTIGATION OF DIGITAL AERIAL ULTRA CAM-D IMAGES IN IDENTIFYING TREE SPECIES IN THE HYRCANIAN MIXED FORESTS (CASE STUDY: SHASTKALATE FOREST IN GORGAN)

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GHASEMI ROZVEH A.; SHATAEE JOIBARY SH.; MOHAMADI J.

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Journal: Journal of Wood and Forest Science and Technology Year:2017 | Volume:24 | Issue:1 Page(s): 77-89

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Title

CAPABILITY INVESTIGATION OF DIGITAL AERIAL ULTRA CAM-D IMAGES IN IDENTIFYING TREE SPECIES IN THE HYRCANIAN MIXED FORESTS (CASE STUDY: SHASTKALATE FOREST IN GORGAN)

Author(s)

GHASEMI ROZVEH A. | SHATAEE JOIBARY SH. | MOHAMADI J. | Issue Writer Certificate

Keywords

IDENTIFY TREE SPECIESQ1

DIGITAL IMAGES AERIALQ1

ULTRACAM-DQ2

MIXED HARDWOOD FORESTSQ1

MAXIMUM LIKELIHOODQ1

Abstract

IDENTIFY TREE SPECIES and tree composition mapping are playing an important role in making optimal decisions for the forest's ecosystem management of large areas. Capability investigation of different remote-sensing sources, such as aerial digital images for forest resources is considered as an alternative method for ground surveying in recent years. Remote-sensing data, especially digital aerial images with high spatial and radiometric resolution could be a useful tool to IDENTIFY TREE SPECIES. By traditional pixel-based methods, classification the pixels of images can be done the different algorithms. Traditional digital classification methods such as the MAXIMUM LIKELIHOOD algorithm are the most common methods based on pixel-based classification. The use of modern classification algorithms such as a non-parametric support vector machine algorithm is essential to compare their performances.Background and objectives: According to a few studies to examine the capability of these images in the urban forests and reforestations in the northern Iran, and lack of a research about evaluating the capability of Digital aerial images to IDENTIFY TREE SPECIES in the Hyrcanian mixed forests, The aim of this research is an investigation of capability of ULTRACAM-D aerial digital photos to IDENTIFY TREE SPECIES in the Hyrcanian mixed hardwood forest, district 1 of Shastkalate forest in Gorgan and comparing two pixel-based algorithm, i.e. the MAXIMUM LIKELIHOOD and support vector machine. There are several ways to extract information from this type of image.Materials and methods: a ground truth map of 128 trees species was provided by registration of their position with DGPS. Identification and classification of tree species were done using original and processed bands s using pixel–based method of MAXIMUM LIKELIHOOD and support vector machine algorithms Accuracy assessment of classified maps was done with use of 25% of the ground truth samples.Results: The accuracy assessment of filtered classified maps showed the classified map of the MAXIMUM LIKELIHOOD algorithm had the overall accuracy and kappa coefficient of 63.63% and 0.51, and support vector machine algorithm had 42.37% and 0.2, respectively.Conclusion: By comparing the results, it is exposed that the pixel-based classification method has not been effective relatively in identifying tree species due to the salt and peppery effect or without using of the auxiliary data (slope, elevation, etc.) in the classification process. The use of other methods such as object classification method based on identify of tree species will be recommended. In addition, the capability of images should be examined in different forest conditions.

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APA: Copy

GHASEMI ROZVEH, A., SHATAEE JOIBARY, SH., & MOHAMADI, J.. (2017). CAPABILITY INVESTIGATION OF DIGITAL AERIAL ULTRA CAM-D IMAGES IN IDENTIFYING TREE SPECIES IN THE HYRCANIAN MIXED FORESTS (CASE STUDY: SHASTKALATE FOREST IN GORGAN). JOURNAL OF WOOD AND FOREST SCIENCE AND TECHNOLOGY, 24(1), 77-89. SID. https://sid.ir/paper/156681/en

Vancouver: Copy

GHASEMI ROZVEH A., SHATAEE JOIBARY SH., MOHAMADI J.. CAPABILITY INVESTIGATION OF DIGITAL AERIAL ULTRA CAM-D IMAGES IN IDENTIFYING TREE SPECIES IN THE HYRCANIAN MIXED FORESTS (CASE STUDY: SHASTKALATE FOREST IN GORGAN). JOURNAL OF WOOD AND FOREST SCIENCE AND TECHNOLOGY[Internet]. 2017;24(1):77-89. Available from: https://sid.ir/paper/156681/en

IEEE: Copy

A. GHASEMI ROZVEH, SH. SHATAEE JOIBARY, and J. MOHAMADI, “CAPABILITY INVESTIGATION OF DIGITAL AERIAL ULTRA CAM-D IMAGES IN IDENTIFYING TREE SPECIES IN THE HYRCANIAN MIXED FORESTS (CASE STUDY: SHASTKALATE FOREST IN GORGAN),” JOURNAL OF WOOD AND FOREST SCIENCE AND TECHNOLOGY, vol. 24, no. 1, pp. 77–89, 2017, [Online]. Available: https://sid.ir/paper/156681/en

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