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Evaluation of Pavement Condition Using Hyperspectral Images
Pavement Condition Index (PCI) is an important index to establish a proper maintenance and rehabilitation strategy of a road network. The index is calculated based on the present state of surface defects, deformation and cracking. The information is normally obtained by visual inspection and observation of road networks. Nowadays, various sensor-based visual inspection techniques are applied to obtain detailed information of a road network, and to automate the entire process of calculating PCI. Hyperspectral analysis is a technique to identify the spectral signature of a material in the electromagnetic spectrum. The technique is being applied to pavement condition evaluation. Some researchers have reported that Exposed Aggregate Index (EAI) has a relationship with the reflectance of a hyperspectral image of a road network. In this study, the possibility of using hyperspectral images for pavement condition evaluation is experimentally investigated and the relationship between EAI and PCI is addressed.
