Collecting and Interpreting Long-Term Pavement Performance Photographic Distress Data: Quality Control-Quality Assurance Processes
Gonzalo R. J. Rada, Amy L. Simpson, John E. Hunt
Abstract
Gonzalo R. J. Rada, Amy L. Simpson, John E. Hunt
Abstract
The Long-Term Pavement Performance (LTPP) program is making use of photographic technology to provide, first, detailed, distress-specific condition data for use in the development and validation of pavement performance models and, second, a permanent, objective, high-resolution record of pavement condition over the full length and width of the sections in the program. Because high-quality distress data are critical to the success of the LTPP program, numerous quality control-quality assurance (QC-QA) processes have been implemented over the life of the program. Those processes address data quality before the start of data collection, during data collection, during data interpretation, after data interpretation, and after the uploading of data to the LTPP database. Some of the processes are a direct result of advance planning, based on past experience, while others are the result of lessons learned in the course of the program. Some were implemented early in the program, while others were introduced well into the program. The Distress Identification Manual, distress rater accreditation workshops, time series review, database checks, data studies and analyses, and feedback reports are just a few of the elements that make up the full suite of QC-QA processes. A detailed summary of the QC-QA processes associated with the LTPP photographic distress data is presented.
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The Long-Term Pavement Performance (LTPP) program is making use of photographic technology to provide, first, detailed, distress-specific condition data for use in the development and validation of pavement performance models and, second, a permanent, objective, high-resolution record of pavement condition over the full length and width of the sections in the program. Because high-quality distress data are critical to the success of the LTPP program, numerous quality control-quality assurance (QC-QA) processes have been implemented over the life of the program. Those processes address data quality before the start of data collection, during data collection, during data interpretation, after data interpretation, and after the uploading of data to the LTPP database. Some of the processes are a direct result of advance planning, based on past experience, while others are the result of lessons learned in the course of the program. Some were implemented early in the program, while others were introduced well into the program. The Distress Identification Manual, distress rater accreditation workshops, time series review, database checks, data studies and analyses, and feedback reports are just a few of the elements that make up the full suite of QC-QA processes. A detailed summary of the QC-QA processes associated with the LTPP photographic distress data is presented.
Key concepts: Quality assurance, Data collection, Data quality, Identification (biology), Distress, Accreditation, Quality (philosophy), Documentation