Investigation of hyperspectral remote sensing for mapping asphalt road conditions

Andreou, C; Karathanassi, V; Kolokoussis, P

dc.contributor.author	Andreou, C	en
dc.contributor.author	Karathanassi, V	en
dc.contributor.author	Kolokoussis, P	en
dc.date.accessioned	2014-03-01T02:02:20Z
dc.date.available	2014-03-01T02:02:20Z
dc.date.issued	2011	en
dc.identifier.issn	01431161	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/29310
dc.subject.other	Asphalt roads	en
dc.subject.other	Compact airborne spectrographic imager	en
dc.subject.other	Grey-level co-occurrence matrixes	en
dc.subject.other	High quality	en
dc.subject.other	HyperSpectral	en
dc.subject.other	Hyperspectral Data	en
dc.subject.other	Hyperspectral remote sensing	en
dc.subject.other	ISODATA	en
dc.subject.other	Material quality	en
dc.subject.other	Processing method	en
dc.subject.other	Radiometer data	en
dc.subject.other	Self organizing	en
dc.subject.other	Spectral angle mappers	en
dc.subject.other	Spectral libraries	en
dc.subject.other	Spectral measurement	en
dc.subject.other	Spectral signature	en
dc.subject.other	Supervised classification	en
dc.subject.other	Texture measurement	en
dc.subject.other	Thresholding	en
dc.subject.other	Unsupervised classification	en
dc.subject.other	Asphalt	en
dc.subject.other	Linear transformations	en
dc.subject.other	Mapping	en
dc.subject.other	Metadata	en
dc.subject.other	Quality control	en
dc.subject.other	Radiometers	en
dc.subject.other	Radiometry	en
dc.subject.other	Remote sensing	en
dc.subject.other	Roads and streets	en
dc.subject.other	Space optics	en
dc.subject.other	Principal component analysis	en
dc.subject.other	asphalt	en
dc.subject.other	image analysis	en
dc.subject.other	mapping	en
dc.subject.other	principal component analysis	en
dc.subject.other	radiometer	en
dc.subject.other	remote sensing	en
dc.subject.other	road	en
dc.subject.other	spectral analysis	en
dc.title	Investigation of hyperspectral remote sensing for mapping asphalt road conditions	en
heal.type	journalArticle	en
heal.identifier.primary	10.1080/01431161.2010.508799	en
heal.identifier.secondary	http://dx.doi.org/10.1080/01431161.2010.508799	en
heal.publicationDate	2011	en
heal.abstract	An investigation of hyperspectral remote sensing for mapping asphalt road conditions is undertaken in this study. Hyperspectral data acquired by the GER1500 radiometer and the Compact Airborne Spectrographic Imager (CASI) 550 sensor have been analysed, processed and interpreted. Field radiometer data were used to provide high-quality spectral measurements for developing a spectral library for asphalt, defining potential categories of the asphalt condition and minimizing the dimension of the hyperspectral space. Analysis of spectral signatures indicated that asphalt condition is affected by asphalt age, material quality and road circulation, and that it led to the definition of five potential categories. Two of them indicate asphalt in high distress and surfaces that need rehabilitation. Among several others, the following processing methods were revealed as the most suitable for detecting asphalt condition: Principal Component Analysis (PCA), thresholding of colour transformation images, unsupervised classification Iterative Self-organizing Data Analysis (IsoData), supervised classification Spectral Angle Mapper (SAM) and texture measurements using the Grey-level Co-occurrence Matrix operator. The results indicated that hyperspectral remote sensing is capable of mapping asphalt road conditions with respect to the categorization proposed within this study. © 2011 Taylor & Francis.	en
heal.journalName	International Journal of Remote Sensing	en
dc.identifier.doi	10.1080/01431161.2010.508799	en
dc.identifier.volume	32	en
dc.identifier.issue	21	en
dc.identifier.spage	6315	en
dc.identifier.epage	6333	en