Manne Suneetha
ABSTRACT
Multispectral Image classification is one of the Important and complex tasks in remote sensing image analysis. Many approaches have been studied to improve classification performance. Most of these methods use pixel based Classification. Unlike, this paper proposed object based Classification which uses Vector data by make use of geometrical shapes like lines and polygons. Series of steps are designed and implemented for remote sensing satellite images like Deimos-2 and Cartosat-1. The Overall Accuracy (OA) and Kappa coefficient values have shown the effectiveness of the proposed method. These values are 93.6% and 87% respectively for Deimos-2 Data. But for Cartosat-1 Data accuracy values are less and observed as 87.33% and 81%. Besides, the proposed method can be useful in tree parameters estimation along with supported elevation data.
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Index Terms
- Object based Classification of Multispectral Remote Sensing Images for Forestry Applications
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