Studying the Applicability of X-Band SAR Data to the Network-Scale Mapping of Pavement Roughness on US Roads
The traveling public judges the quality of a road mostly by its roughness and/or ride quality. Hence, mapping, monitoring, and maintaining adequate pavement smoothness is of high importance to State Departments of Transportation in the US. Current methods rely mostly on in situ measurements and are,...
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doaj-0b11d68079a1479384e1f6c5eb04256b2020-11-25T02:04:33ZengMDPI AGRemote Sensing2072-42922020-05-01121507150710.3390/rs12091507Studying the Applicability of X-Band SAR Data to the Network-Scale Mapping of Pavement Roughness on US RoadsFranz J. Meyer0Olaniyi A. Ajadi1Edward J. Hoppe2Geophysical Institute, University of Alaska Fairbanks, 2156 Koyukuk Drive, Fairbanks, AK 99775, USAGeophysical Institute, University of Alaska Fairbanks, 2156 Koyukuk Drive, Fairbanks, AK 99775, USAVirginia Transportation Research Council, 530 Edgemont Rd, Charlottesville, VA 22903, USAThe traveling public judges the quality of a road mostly by its roughness and/or ride quality. Hence, mapping, monitoring, and maintaining adequate pavement smoothness is of high importance to State Departments of Transportation in the US. Current methods rely mostly on in situ measurements and are, therefore, time consuming and costly when applied at the network scale. This paper studies the applicability of satellite radar remote sensing data, specifically, high-resolution Synthetic Aperture Radar (SAR) data acquired at X-band, to the network-wide mapping of pavement roughness of roads in the US. Based on a comparison of high-resolution X-band Cosmo-SkyMed images with road roughness data in the form of International Roughness Index (IRI) measurements, we found that X-band radar brightness generally increases when pavement roughness worsens. Based on these findings, we developed and inverted a model to distinguish well maintained road segments from segments in need of repair. Over test sites in Augusta County, VA, we found that our classification scheme reaches an overall accuracy of 92.6%. This study illustrates the capacity of X-band SAR for pavement roughness mapping and suggests that incorporating SAR into DOT operations could be beneficial.https://www.mdpi.com/2072-4292/12/9/1507X-bandsynthetic aperture radarpavement roughnessroad surface qualityinternational roughness indexIRI |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Franz J. Meyer Olaniyi A. Ajadi Edward J. Hoppe |
spellingShingle |
Franz J. Meyer Olaniyi A. Ajadi Edward J. Hoppe Studying the Applicability of X-Band SAR Data to the Network-Scale Mapping of Pavement Roughness on US Roads Remote Sensing X-band synthetic aperture radar pavement roughness road surface quality international roughness index IRI |
author_facet |
Franz J. Meyer Olaniyi A. Ajadi Edward J. Hoppe |
author_sort |
Franz J. Meyer |
title |
Studying the Applicability of X-Band SAR Data to the Network-Scale Mapping of Pavement Roughness on US Roads |
title_short |
Studying the Applicability of X-Band SAR Data to the Network-Scale Mapping of Pavement Roughness on US Roads |
title_full |
Studying the Applicability of X-Band SAR Data to the Network-Scale Mapping of Pavement Roughness on US Roads |
title_fullStr |
Studying the Applicability of X-Band SAR Data to the Network-Scale Mapping of Pavement Roughness on US Roads |
title_full_unstemmed |
Studying the Applicability of X-Band SAR Data to the Network-Scale Mapping of Pavement Roughness on US Roads |
title_sort |
studying the applicability of x-band sar data to the network-scale mapping of pavement roughness on us roads |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2020-05-01 |
description |
The traveling public judges the quality of a road mostly by its roughness and/or ride quality. Hence, mapping, monitoring, and maintaining adequate pavement smoothness is of high importance to State Departments of Transportation in the US. Current methods rely mostly on in situ measurements and are, therefore, time consuming and costly when applied at the network scale. This paper studies the applicability of satellite radar remote sensing data, specifically, high-resolution Synthetic Aperture Radar (SAR) data acquired at X-band, to the network-wide mapping of pavement roughness of roads in the US. Based on a comparison of high-resolution X-band Cosmo-SkyMed images with road roughness data in the form of International Roughness Index (IRI) measurements, we found that X-band radar brightness generally increases when pavement roughness worsens. Based on these findings, we developed and inverted a model to distinguish well maintained road segments from segments in need of repair. Over test sites in Augusta County, VA, we found that our classification scheme reaches an overall accuracy of 92.6%. This study illustrates the capacity of X-band SAR for pavement roughness mapping and suggests that incorporating SAR into DOT operations could be beneficial. |
topic |
X-band synthetic aperture radar pavement roughness road surface quality international roughness index IRI |
url |
https://www.mdpi.com/2072-4292/12/9/1507 |
work_keys_str_mv |
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