Abstracts – Browse Results
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Cunningham Emord, P (2009) Building evaluation capacity with appreciative inquiry: An exploratory case study, Unpublished PhD Thesis, , The University of New Mexico.
Garrido Martins, C (2019) Assessment of project risks in fast-track construction projects, Unpublished PhD Thesis, , University of New Mexico.
Gatti, U C (2012) Measuring and evaluating physical strain to improve construction workforce productivity, Unpublished PhD Thesis, , University of New Mexico.
Han, F (2021) Measurement of resilience performance for infrastructure construction project delivery, Unpublished PhD Thesis, , The University of New Mexico.
Jafari, A (2018) A decision-making framework for the selection of sustainable alternatives for energy-retrofits, Unpublished PhD Thesis, , University of New Mexico.
Jaramillo, L V (2019) Implementations of resilience engineering for natural system disturbances: A panarchical perspective, Unpublished PhD Thesis, , University of New Mexico.
Martens, R (2018) An analysis of the relationship between leadership style and lean expressed through respect, proactivity, and innovative work behavior, Unpublished PhD Thesis, , University of New Mexico.
Nauman, R A (1999) The United States air force academy: A case study of rhetoric and reality in the making of modernism, Unpublished PhD Thesis, , University of New Mexico.
Phillips, H C (2009) A proposed method to determine confidence in a construction schedule, Unpublished PhD Thesis, , University of New Mexico.
Santamaria Carrera, J L (2017) Quantifying the effect of construction site factors on concrete quality, costs and production rates, Unpublished PhD Thesis, , University of New Mexico.
Severn, B W (1980) A simplified methodology for evaluating rural road proposals for less developed countries, Unpublished PhD Thesis, , University of New Mexico.
Zhang, S (2017) Pavement surface distress detection, assessment, and modeling using geospatial techniques, Unpublished PhD Thesis, , University of New Mexico.
- Type: Thesis
- Keywords: pavement; traffic; asset management
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/1947584393
- Abstract:
Roadway pavement surface distress information is essential for effective pavement asset management, and subsequently, transportation agencies at all levels dedicate a large amount of time and money to routinely collect data on pavement surface distress conditions as the core of their asset management programs. These data are used by these agencies to make maintenance and repair decisions. Current methods for pavement surface distress evaluation are time-consuming and expensive. Geospatial technologies provide new methods for evaluating pavement surface distress condition that can supplement or substitute for currently-adopted evaluation methods. However, few previous studies have explored the utility of geospatial technologies for pavement surface distress evaluation. The primary scope of this research is to evaluate the potential of three geospatial techniques to improve the efficiency of pavement surface distress evaluation, including empirical analysis of high-spatial resolution natural color digital aerial photography (HiSR-DAP), empirical analysis of hyper-spatial resolution natural color digital aerial photography (HySR-DAP), and inferential geospatial modeling based on traffic volume, environmental conditions, and topographic factors. Pavement surface distress rates estimated from the aforementioned geospatial technologies are validated against distress data manually collected using standard protocols. Research results reveal that straightforward analysis of the spectral response extracted from HiSR-DAP can permit assessment of overall pavement surface conditions. In addition, HySR-DAP acquired from S-UAS can provide accurate and reliable information to characterize detailed pavement surface distress conditions. Research results also show that overall pavement surface distress condition can be effectively estimated based on the extent of geospatial data and inferential modeling techniques. In the near term, these proposed methods could be used to rapidly and cost-effectively evaluate pavement surface distress condition for roadway sections where field inspectors or survey vehicles cannot gain access. In the long term, these proposed methods are capable of being automated to routinely evaluate pavement surface distress condition and, ultimately, to provide a cost-effective, rapid, and safer alternative to currently-adopted evaluation methods with substantially reduced sampling density.