Automatic localization of backscattering events due to particulate in urban areas (Contributo in atti di convegno)

Type
Label
  • Automatic localization of backscattering events due to particulate in urban areas (Contributo in atti di convegno) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1117/12.2066670 (literal)
Alternative label
  • Gaudio, P.; Gelfusa, M.; Malizia, A.; Parracino, S.; Richetta, M.; Murari, A.; Vega, J. (2014)
    Automatic localization of backscattering events due to particulate in urban areas
    in Conference on Technologies for Optical Countermeasures XI; and High-Power Lasers - Technology and Systems, Amsterdam; Netherlands, 22-24 September 2014
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Gaudio, P.; Gelfusa, M.; Malizia, A.; Parracino, S.; Richetta, M.; Murari, A.; Vega, J. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 9244 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 9244 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 12 (literal)
Note
  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • 1-5 : Department of Industrial Engineering, University of Rome \"Tor Vergata, 00133, Rome, Italy; / 6 Consorzio RFX-Associazione EURATOM ENEA per la Fusione, I-35127 Padova, Italy; / 7 Asociación EURATOM/CIEMAT para Fusión. Avda. Complutense, 22. 28040 Madrid, Spain. (literal)
Titolo
  • Automatic localization of backscattering events due to particulate in urban areas (literal)
Abstract
  • Particulate matter (PM), emitted by vehicles in urban traffic, can greatly affect environment air quality and have direct implications on both human health and infrastructure integrity. The consequences for society are relevant and can impact also on national health. Limits and thresholds of pollutants emitted by vehicles are typically regulated by government agencies. In the last few years, the interest in PM emissions has grown substantially due to both air quality issues and global warming. Lidar-Dial techniques are widely recognized as a cost-effective alternative to monitor large regions of the atmosphere. To maximize the effectiveness of the measurements and to guarantee reliable, automatic monitoring of large areas, new data analysis techniques are required. In this paper, an original tool, the Universal Multi-Event Locator (UMEL), is applied to the problem of automatically indentifying the time location of peaks in Lidar measurements for the detection of particulate matter emitted by anthropogenic sources like vehicles. The method developed is based on Support Vector Regression and presents various advantages with respect to more traditional techniques. In particular, UMEL is based on the morphological properties of the signals and therefore the method is insensitive to the details of the noise present in the detection system. The approach is also fully general, purely software and can therefore be applied to a large variety of problems without any additional cost. The potential of the proposed technique is exemplified with the help of data acquired during an experimental campaign in the field in Rome. (literal)
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