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http://dx.doi.org/10.7848/ksgpc.2015.33.5.363

A Study on the Feature Extraction Using Spectral Indices from WorldView-2 Satellite Image  

Hyejin, Kim (Dept. of Civil and Environmental Engineering, Seoul National University)
Yongil, Kim (Dept. of Civil and Environmental Engineering, Seoul National University)
Byungkil, Lee (Dept. of Civil Engineering, Kyonggi University)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.33, no.5, 2015 , pp. 363-371 More about this Journal
Abstract
Feature extraction is one of the main goals in many remote sensing analyses. After high-resolution imagery became more available, it became possible to extract more detailed and specific features. Thus, considerable image segmentation algorithms have been developed, because traditional pixel-based analysis proved insufficient for high-resolution imagery due to its inability to handle the internal variability of complex scenes. However, the individual segmentation method, which simply uses color layers, is limited in its ability to extract various target features with different spectral and shape characteristics. Spectral indices can be used to support effective feature extraction by helping to identify abundant surface materials. This study aims to evaluate a feature extraction method based on a segmentation technique with spectral indices. We tested the extraction of diverse target features-such as buildings, vegetation, water, and shadows from eight band WorldView-2 satellite image using decision tree classification and used the result to draw the appropriate spectral indices for each specific feature extraction. From the results, We identified that spectral band ratios can be applied to distinguish feature classes simply and effectively.
Keywords
Feature Extraction; Spectral Index; Segmentation; Decision Tree Classification;
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