Public Works facilities require up-to-date information on the health status of the road network they maintain. However, roadway maintenance and rehabilitation involves the greatest portion of a municipality's annual operating budget. Government officials use various technologies such as a pavement management system to assist in making better decisions about their roadways systems, pavement condition, history, and projects. Traditionally, manual surveying has served as the method of obtaining this information. To better assist in decision-making, a regionally specific spectral library for urban areas is being developed and used in conjunction with hyperspecrtal imaging, to map urban materials and pavement conditions. A Geographical Information and Positioning System (GIS/GPS) will also be implemented to overlay relative locations. This paper will examine the benefits of using hyperspectral imaging over traditional methods of roadway maintenance and rehabilitation for pavement management applications. In doing so, we will identify spatial and spectral requirements for successful large-scale road feature extraction.
This paper analyzes the feasibility and performance of HSI systems for medical diagnosis as well as for food safety. Illness prevention and early disease detection are key elements for maintaining good health. Health care practitioners worldwide rely on innovative electronic devices to accurately identify disease. Hyperspectral imaging (HSI) is an emerging technique that may provide a less invasive procedure than conventional diagnostic imaging. By analyzing reflected and fluorescent light applied to the human body, a HSI system serves as a diagnostic tool as well as a method for evaluating the effectiveness of applied therapies. The safe supply and production of food is also of paramount importance to public health illness prevention. Although this paper will focus on imaging and spectroscopy in food inspection procedures -- the detection of contaminated food sources -- to ensure food quality, HSI also shows promise in detecting pesticide levels in food production (agriculture.)