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Estimation of tree size diversity using object oriented texture analysis and aster imagery

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dc.creator Ozkan, Ulas Yunus
dc.creator Ozdemir, Ibrahim
dc.creator Norton, David A.
dc.creator SENTURK, Ozdemir
dc.creator Mert, AHMET
dc.date 2008-07-31T21:00:00Z
dc.date.accessioned 2020-10-06T10:48:11Z
dc.date.available 2020-10-06T10:48:11Z
dc.identifier 8d2ff90a-72b6-437b-adeb-edc8942fe02f
dc.identifier 10.3390/s8084709
dc.identifier https://avesis.sdu.edu.tr/publication/details/8d2ff90a-72b6-437b-adeb-edc8942fe02f/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/65997
dc.description This study investigates the potential of object-based texture parameters extracted from 15m spatial resolution ASTER imagery for estimating tree size diversity in a Mediterranean forested landscape in Turkey. Tree size diversity based on tree basal area was determined using the Shannon index and Gini Coefficient at the sampling plot level. Image texture parameters were calculated based on the grey level co-occurrence matrix (GLCM) for various image segmentation levels. Analyses of relationships between tree size diversity and texture parameters found that relationships between the Gini Coefficient and the GLCM values were the most statistically significant, with the highest correlation (r=0.69) being with GLCM Homogeneity values. In contrast, Shannon Index values were weakly correlated with image derived texture parameters. The results suggest that 15m resolution Aster imagery has considerable potential in estimating tree size diversity based on the Gini Coefficient for heterogeneous Mediterranean forests.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title Estimation of tree size diversity using object oriented texture analysis and aster imagery
dc.type info:eu-repo/semantics/article


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