Next Article in Journal
Changes in Aerosol Optical and Micro-Physical Properties over Northeast Asia from a Severe Dust Storm in April 2014
Previous Article in Journal
InSAR-Based Mapping of Tidal Inundation Extent and Amplitude in Louisiana Coastal Wetlands
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2016, 8(5), 392; doi:10.3390/rs8050392

Characterizing Pavement Surface Distress Conditions with Hyper-Spatial Resolution Natural Color Aerial Photography

1
Department of Civil Engineering, University of New Mexico, Albuquerque, NM 87131, USA
2
Department of Geography and Environmental Studies, University of New Mexico, Albuquerque, NM 87131, USA
3
Earth Data Analysis Center, University of New Mexico, Albuquerque, NM 87131, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Gonzalo Pajares Martinsanz, Guoqing Zhou and Prasad S. Thenkabail
Received: 16 February 2016 / Revised: 16 April 2016 / Accepted: 3 May 2016 / Published: 9 May 2016
View Full-Text   |   Download PDF [9636 KB, uploaded 9 May 2016]   |  

Abstract

Roadway pavement surface distress information is critical for effective pavement asset management, and subsequently, transportation management agencies at all levels (i.e., federal, state, and local) dedicate a large amount of time and money to routinely evaluate pavement surface distress conditions as the core of their asset management programs. However, currently adopted ground-based evaluation methods for pavement surface conditions have many disadvantages, like being time-consuming and expensive. Aircraft-based evaluation methods, although getting more attention, have not been used for any operational evaluation programs yet because the acquired images lack the spatial resolution to resolve finer scale pavement surface distresses. Hyper-spatial resolution natural color aerial photography (HSR-AP) provides a potential method for collecting pavement surface distress information that can supplement or substitute for currently adopted evaluation methods. Using roadway pavement sections located in the State of New Mexico as an example, this research explored the utility of aerial triangulation (AT) technique and HSR-AP acquired from a low-altitude and low-cost small-unmanned aircraft system (S-UAS), in this case a tethered helium weather balloon, to permit characterization of detailed pavement surface distress conditions. The Wilcoxon Signed Rank test, Mann-Whitney U test, and visual comparison were used to compare detailed pavement surface distress rates measured from HSR-AP derived products (orthophotos and digital surface models generated from AT) with reference distress rates manually collected on the ground using standard protocols. The results reveal that S-UAS based hyper-spatial resolution imaging and AT techniques can provide detailed and reliable primary observations suitable for characterizing detailed pavement surface distress conditions comparable to the ground-based manual measurement, which lays the foundation for the future application of HSR-AP for automated detection and assessment of detailed pavement surface distress conditions. View Full-Text
Keywords: pavement surface distress evaluation; hyper-spatial resolution; natural color aerial photography; small-unmanned aircraft systems (S-UAS); aerial triangulation pavement surface distress evaluation; hyper-spatial resolution; natural color aerial photography; small-unmanned aircraft systems (S-UAS); aerial triangulation
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Zhang, S.; Lippitt, C.D.; Bogus, S.M.; Neville, P.R.H. Characterizing Pavement Surface Distress Conditions with Hyper-Spatial Resolution Natural Color Aerial Photography. Remote Sens. 2016, 8, 392.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top