Cerema DTer Est ERA 31
Cerema DTer Est ERA 31
Marchetti M.,Cerema DTer Est ERA 31 |
Boucher V.,Cerema DTer Ouest ERA 17 |
Dumoulin J.,LUNAM University |
Colomb M.,Cerema er Center Est
Infrared Physics and Technology | Year: 2015
Fog conditions are the cause of severe car accidents in European western countries because of the poor induced visibility. Its occurrence and intensity are still very difficult to forecast for weather services. Furthermore, visibility determination relies on expensive instruments and does not ease their dissemination. Lately, it has been demonstrated the benefit of infrared cameras to detect and to identify objects in fog while visibility is too low for eye detection. Over the past years, such cameras have become more cost effective. A research program between IFSTTAR and Cerema studied the possibility to retrieve visibility distance in a fog tunnel during its natural dissipation. The purpose of this work is to retrieve atmospheric visibility with a technique based on the combined use of infrared thermography, Principal Components Analysis (PCA) and Partial Least-Square (PLS) regression applied to infrared images. © 2015 Elsevier B.V. All rights reserved.
Marchetti M.,CEREMA DTer Est ERA 31 |
Chapman L.,University of Birmingham |
Khalifa A.,CEREMA DTer Est ERA 31 |
Bues M.,CNRS Georesources lab
Advances in Meteorology | Year: 2014
Thermal mapping uses IR thermometry to measure road pavement temperature at a high resolution to identify and to map sections of the road network prone to ice occurrence. However, measurements are time-consuming and ultimately only provide a snapshot of road conditions at the time of the survey. As such, there is a need for surveys to be restricted to a series of specific climatic conditions during winter. Typically, five to six surveys are used, but it is questionable whether the full range of atmospheric conditions is adequately covered. This work investigates the role of statistics in adding value to thermal mapping data. Principal components analysis is used to interpolate between individual thermal mapping surveys to build a thermal map (or even a road surface temperature forecast), for a wider range of climatic conditions than that permitted by traditional surveys. The results indicate that when this approach is used, fewer thermal mapping surveys are actually required. Furthermore, comparisons with numerical models indicate that this approach could yield a suitable verification method for the spatial component of road weather forecasts - a key issue currently in winter road maintenance. © 2014 Mario Marchetti et al.