Road Condition Mapping with Hyperspectral Remote Sensing

1. Introduction The quality standards for transportation infrastructure have evolved considerably over the last three decades. The data accuracy requirements to support road management have decreased from tens of meters to a few decimeters with annual update rates. Roads are prioritized for maintenance and treatment as a result of pavement inspections. The cost of frequent, comprehensive inspection is high, and many jurisdictions limit their surveys to major roads, while minor roads are surveyed in 3-year cycles. For this purpose, a number of survey technologies have been applied to road condition mapping. The common practice today is extensive field observations by experts who characterize the Pavement Condition Index (PCI), based on established physical parameters such as cracking, rutting, raveling, etc. Other technologies are evolving such us the application of Pavement Management Systems (PMS); typically coupled with GPS/GIS technology and semi-automated in-situ pavement health surveys facilitated by vans. They capture exhaustive photographic and video logs of pavement quality (and at the same time asset inventory), while recording road geometry with GPS and Distance Measuring Instruments. This produces a detailed and georeferenced condition report, with PCI ratings for every ~10 m of road. Nevertheless, this remains an expensive and troublesome survey, while cost and safety considerations require that it be done at regular intervals.