A Fully Automated Approach to Extract Landcover Features from Landsat Imageries

The land cover maps playa significant role in planning, managing, and monitoring our environment changes at different levels. Land cover denotes the surface cover on the ground, comprised of water, built up, bare land, vegetation, or other. This paper highlights a method to automatically extract the water, built-up, and vegetation landcover datasets using Index Extracted Water Index (IEWI), Index Extracted Built-up Index (IEBI), and Index Extracted Vegetation Index (IEVI), respectively. The results are then validated with ground truth points from the field survey. The advantages of this novel method are rapid extraction of landcover features, cost-effectiveness, reduction in misclassification, and comparable classification accuracy with superior methods of land cover classification. These findings suggest that this index -based, fully automated feature extraction approach can be quickly applied for various remote sensing applications with better accuracy.