Investigation of Spectral Assignments from Airborne HRS Sensor to Model Friction Deterioration in Asphaltic Roads

Nimrod Carmon, Eyal Ben-Dor, Csaba Lenart

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work, we propose a spectral assignment analysis (SAA) oriented partial least squares regression (PLS-R) modeling approach, designed to provide descriptive spectral assignments of proxy models. We applied this method on airborne HSR data of asphalt roads combined with the dynamic friction coefficient (m) that were measured independently. Accordingly, the method automatically subgroups the data into high and low values clusters under an iterative segmentation process. A PLS-R model is fitted to each group, followed by the extraction of the B Coefficient spectrum. A spectral angle (SA) value is calculated in each iteration between the two spectra to find the most pronounced difference between the two segments, pointing on a significant group separation. Hyperspectral data was acquired using the AisaFenix 1k hyperspectral imaging system over several asphalt roads in central Israel. This method provided insights regarding the physical and chemical processes occurring to asphalt pavement due to aging effects, and the different assignments for different friction levels.

Original languageEnglish
Title of host publication2018 9th Workshop on Hyperspectral Image and Signal Processing
Subtitle of host publicationEvolution in Remote Sensing, WHISPERS 2018
PublisherIEEE Computer Society
ISBN (Electronic)9781728115818
DOIs
StatePublished - Sep 2018
Event9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2018 - Amsterdam, Netherlands
Duration: 23 Sep 201826 Sep 2018

Publication series

NameWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Volume2018-September
ISSN (Print)2158-6276

Conference

Conference9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2018
Country/TerritoryNetherlands
CityAmsterdam
Period23/09/1826/09/18

Keywords

  • Data-mining
  • chemometrics
  • partial least squares
  • skid resistance
  • spectral assignment

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