Classification of tree species using high-resolution QuickBird-2 satellite images in the valley of Ui-dong in Bukhansan National Park
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참고문헌
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초록
This study was performed in order to suggest the possibility of tree species classification using high-resolution Quick-Bird-2 images spectral characteristics comparison(digital numbers [DNs]) of tree species, tree species classification, and accuracy verification. In October 2010, the tree species of three conifers and eight broad-leaved trees were examined in the areas studied. The spectral characteristics of each species were observed, and the study area was classified by image classification. The results were as follows: Panchromatic and multi-spectral band 4 was found to be useful for tree species classification. DNs values of conifers were lower than broad-leaved trees. Vegetation indices such as normalized difference vegetation index (NDVI), soil brightness index (SBI), green vegetation index (GVI) and Biband showed similar patterns to band 4 and panchromatic (PAN); Tukey’s multiple comparison test was significant among tree species. However,tree species within the same genus, such as Pinus densiflora-P. rigida and Quercus mongolica-Q. serrata, showed similar DNs patterns and, therefore, supervised classification results were difficult to distinguish within the same genus; Random selection of validation pixels showed an overall classification accuracy of 74.1% and Kappa coefficient was 70.6%. The classification accuracy of Pterocarya stenoptera, 89.5%, was found to be the highest. The classification accuracy of broadleaved trees was lower than expected, ranging from 47.9% to 88.9%. P. densiflora-P. rigida and Q. mongolica-Q. serrata were classified as the same species because they did not show significant differences in terms of spectral patterns.
Abstract
This study was performed in order to suggest the possibility of tree species classification using high-resolution Quick-Bird-2 images spectral characteristics comparison(digital numbers [DNs]) of tree species, tree species classification, and accuracy verification. In October 2010, the tree species of three conifers and eight broad-leaved trees were examined in the areas studied. The spectral characteristics of each species were observed, and the study area was classified by image classification. The results were as follows: Panchromatic and multi-spectral band 4 was found to be useful for tree species classification. DNs values of conifers were lower than broad-leaved trees. Vegetation indices such as normalized difference vegetation index (NDVI), soil brightness index (SBI), green vegetation index (GVI) and Biband showed similar patterns to band 4 and panchromatic (PAN); Tukey’s multiple comparison test was significant among tree species. However,tree species within the same genus, such as Pinus densiflora-P. rigida and Quercus mongolica-Q. serrata, showed similar DNs patterns and, therefore, supervised classification results were difficult to distinguish within the same genus; Random selection of validation pixels showed an overall classification accuracy of 74.1% and Kappa coefficient was 70.6%. The classification accuracy of Pterocarya stenoptera, 89.5%, was found to be the highest. The classification accuracy of broadleaved trees was lower than expected, ranging from 47.9% to 88.9%. P. densiflora-P. rigida and Q. mongolica-Q. serrata were classified as the same species because they did not show significant differences in terms of spectral patterns.
참고문헌 (15)
- Chung KH, "Classification of forest type using resolution imagery of satellite IKONOS", Korean J Remote Sens, 17, pp.275~284 (2001)
- ERDAS, "ERDAS Field Guide. 4th ed" (1997), ERDAS
- Franklin SE, "Using spatial co-occurrence texture to increase forest structure and species composition classification accuracy", Photogramm Eng Remote Sens, 67, pp.849~855 (2001)
- Ham BY, "Estimation of spatial distribution and occurrence probability of oak species using IKONOS satellite imagery and GIS", Korean J For Meas, 7, pp.74~84 (2004)
- S. Jayakumar, "Object-oriented Classification and QuickBird Multi-spectral Imagery in Forest Density Mapping", 대한원격탐사학회지, 23(3), pp.153~160 (2007), 대한원격탐사학회
- Jordan CF, "Derivation of leaf-area index from quality of light on the forest floor", Ecology, 50, pp.663~666 (1969)
- Katoh M, "Estimation of rates of the crown area in yezo spruce plantations with Landsat thematic mapper data", Proceedings of the 16th ISPRS, 1988, 23~29
- Katoh M, "The estimation of crown densities in todomatsu plantations using Landsat thematic mapper data", Proceedings and IUFRO on sustainable forest management, pp.246~253 (1995)
- Katoh M, "Classifying tree species in a northern mixed forest using high-resolution IKONOS data", J For Res, 9, pp.7~14 (2004)
- 김천, "Use of Crown Feature Analysis to Separate the Two Pine Species in QuickBird Imagery", 대한원격탐사학회지, 24(3), pp.267~272 (2008), 대한원격탐사학회
- Kriegler FJ, "Preprocessing transformations and their effects on multispectral recognition", Proceedings of the 6th International Symposium on Remote Sensing of Environment, pp.97~131 (1969)
- Lee JH, "A study on classification and spatial distribution of forest types using IKONOS satellite imagery and GIS", 석사, pp.2001
- Martin ME, "Determining forest species composition using high spectral resolution remote sensing data", Remote Sens Environ, 65, pp.249~254 (1998)
- Mapping of the Detailed-class Land Cover Map Using Satellite Images. Report, "Ministry of Environment", Ministry of Environment, ~ (2010)
- Construction of GIS-DB for National Ecosystem Information. Report, "National Institute of Environmental Research", National Institute of Environmental Research, ~ (2010)