TRB's Airport Cooperative Research Program (ACRP) Report 39: Recommended Guidelines for the Collection and Use of Geospatially Referenced Data for Airfield Pavement Management offers recommended guidelines for the collection and use of geospatially referenced data for airfield pavement management. The guidelines provide a data schema, data collection methods, data quality requirements, and other relevant information required for developing specifications and standards for integrating geospatial data into pavement management systems. Appendixes A through C to ACRP Report 39 are available online. Titles of the appendixes are as follows: Appendix A: Survey Questionnaire; Appendix B: Questionnaire Responses; Appendix C: Pavement Management Systems Software Data Elements.

TRB's Airport Cooperative Research Program (ACRP) Report 39: Recommended Guidelines for the Collection and Use of Geospatially Referenced Data for Airfield Pavement Management offers recommended guidelines for the collection and use of geospatially referenced data for airfield pavement management. The guidelines provide a data schema, data collection methods, data quality requirements, and other relevant information required for developing specifications and standards for integrating geospatial data into pavement management systems. Appendixes A through C to ACRP Report 39 are available online. Titles of the appendixes are as follows: Appendix A: Survey Questionnaire; Appendix B: Questionnaire Responses; Appendix C: Pavement Management Systems Software Data Elements.

TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 335: Pavement Management Applications Using Geographic Information Systems examines the state of the practice and knowledge of pavement management systems (PMS) using geographic information systems (GIS) and other spatial technologies, and discusses how the technologies have been combined to enhance the highway management process. The synthesis reviews the principal issues related to PMS data collection, integration, management, and dissemination; applications of spatial technologies for map generation and PMS spatial analysis; and implementation-related issues, including approaches used for integrating PMS and GIS and the different tools used to support pavement management decisions.

“Pavement condition data” are essential inputs to the process of managing airport pavements and ensuring safe operations. The technology available today to collect pavement condition data is considerably different from that available even 20 years ago, and new technologies are being developed and introduced into practice at a rapid pace. ACRP Research Report 203: Guidelines for Collecting, Applying, and Maintaining Pavement Condition Data at Airports provides guidance on the collection, use, maintenance, and application of pavement condition data at airports. Such data include conditions that are visually observed as well as those that are obtained by mechanical measurement or other means. Visually observed distresses on a pavement surface (such as cracking, rutting, patching, and spalling) are widely used and accepted as indicators of pavement performance. A key part of the background study leading to this report was the development of case studies of seven airports or airport agencies on their experiences with pavement data collection, use, and management. They include: Houston Airport System (Houston, Texas), Salt Lake City Department of Airports (Salt Lake City, Utah), Dublin International (Dublin, Ireland), Columbus Regional Port Authority (Columbus, Ohio), Gerald R. Ford International Airport Authority (Grand Rapids, Michigan), North Dakota (statewide), and Missouri (statewide).

A Pavement Management System (PMS) is a tool that aids in determining the most effective application of maintenance and reconstruction (M & R) work for a given pavement network. The purpose of this research is the development and implementation of an Airfield Pavement Management System for the Winnipeg International Airport (WIA) that expands on the capabilities and usefulness of conventional systems. The system developed in this research utilizes geo-referenced pavement distress data collected using a GPS receiver. Time required to complete Pavement Condition Index surveys has been reduced, minimizing the impact on airport operations of conducting an airfield inspection. Using geo-referenced distress data leads to a multitude of new analysis techniques that allow for optimum management of the pavement network. Several pavement deterioration models have been created using the collected pavement condition data. These models aim to predict pavement condition at points in the future to aid in M & R planning. Models were created using the least-squares regression technique as well as neural network modelling. The use of neural networks appears promising as they are not constrained to a single regression parameter and can account for the interaction b etween parameters and nonlinear relationships. The WIA PMS represents a significant improvement to the functionality of current PMSs by expanding the analysis and modelling capabilities while reducing the effort associated with data collection.