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Extraction of Urban Targets Using Fusion of Spectral and Shape Features in AVIRIS-NG Hyperspectral Data: Use of Hyperspectral Data for Detecting Roads and Roofs
Abstract
Hyperspectral imagery holds the essence of spectral and spatial attributes, making it a rich source of information for applications like target detection in the field of agriculture, urban areas, etc. The chapter provides an insight of extraction of shape-based features fused with the spectral characteristics for detection of urban targets particularly roads and roofs. Roads are considered as linear structures whereas roofs occur in clusters. Therefore, to detect them, spectral information is not sufficient. The work proposes integration of both spectral and shape aspects of a target, which has given better results using SVM. The experimentation involves results in the form of spectral analysis, shape analysis, fusion of spectral and shape-based features along with the detection rate and supporting results. Delineating the roads and roofs of urban topography is an essential fragment for city planning, urban sprawl estimation, population studies, sustainable development, etc. The work done here may help numerous governmental and non-governmental organizations for conducting related studies.
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