This paper was prepared for the Iowa Pavement Management System, Eight AASHTO/TRB Maintenance Management Conference, Saratoga Springs, N.Y., July 1997.

Iowa's Pavement Management Program Database:
Issues and Design Considerations

Zachary N. Hans
Center for Transportation Research and Education, Iowa State University

Omar G. Smadi
Center for Transportation Research and Education, Iowa State University

Tom H. Maze
Center for Transportation Research and Education, Iowa State University

Reginald R. Souleyrette
Center for Transportation Research and Education, Iowa State University

Jon L. Resler
Center for Transportation Research and Education, Iowa State University


The state of Iowa has embarked on an effort to develop a statewide pavement management system (PMS). The project, the Iowa Pavement Management Program (IPMP), will cover 38,000 km (23,500 miles) of roads operated under three levels of government (state, county, and city). The mission of the project is to develop a geographic information system (GIS) pavement management database to support local governmental agencies and the Iowa Department of Transportation pavement management efforts. This paper discusses the technical aspects of the development of the database, including the database design, dynamic segmentation capabilities, implementation, and maintenance.


Pavement management system, GIS, dynamic segmentation, and database.


The Iowa Pavement Management Program (IPMP) is a statewide effort to develop, implement, and operate a pavement management system on all non-National Highway System (NHS) federal aid eligible highways in the state of Iowa. This effort was initiated to meet the requirements of the Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991. ISTEA mandated six (6) management systems and a traffic monitoring system (really the seventh management system). One of the management system mandates required that all federal aid eligible (FAE) highways in the state to be managed by a Pavement Management System (PMS), one of the six mandated management systems. In Iowa, part of the FAE system is operated by the state, but the majority of the system is operated by Iowa counties and cities. The IPMP is being managed by a Task Force comprised of representatives from the Iowa Department of Transportation (DOT), cities, counties, Regional Planning Affiliations (RPA), Metropolitan Planning Organizations (MPO), and the Federal Highway Administration (FHWA) Iowa Division Office.

The FAE highway network in Iowa covers about 43,500 km (27,000 miles) under the three different jurisdictions: state; counties; and cities. Out of the entire FAE highway network, about 5,600 km (3,500 miles) are on the NHS and are not covered under the IPMP. Iowa's approach to the development of the IPMP is to centrally develop the non-NHS FAE pavement management database for all participants from local and regional governmental agencies along with the Iowa DOT. Local and regional governments and the Iowa DOT will use the information generated from the IPMP as a tool to assist them in managing highway networks under each governmental entity's jurisdiction.

The IPMP started in 1994 and is still in the implementation phase. Full system operation will start in early 1998. Once the system is in it operating phase, training will be provided for local and regional governmental agencies to help them utilize all of the system's capabilities. The principle function of the IPMP is a statewide pavement management database. The statewide database will serve the data requirements of Iowa DOT and local and regional agencies wishing to perform pavement management on the portions of the FAE within their jurisdiction. By collecting and storing pavement management data statewide, tremendous economies-to-scale are achieved in comparison to each agency individually developing their own database. In addition, by having a common database statewide, with data collected using the same procedures throughout the state, all jurisdictions will have consistent data of consistent quality. Another important feature is providing common pavement management tools to all jurisdictions with common default parameters. Pavement management tools allow all jurisdictions to perform pavement management within their jurisdiction. Training and assistance is provided to local and regional governmental agencies to support their use of pavement management.

The IPMP Task Force believed that there were significant advantages to perform common functions centrally, while actual pavement management decisions (maintenance, rehabilitation, or reconstruction project selection) would be conducted by individual highway operating agencies. Database design and development, distress data collection, and pavement management software selection and calibration are the common activities conducted under the IPMP, while the actual application of pavement management would continue to be the domain of the operating agency.

The focus of this paper is on the development of the IPMP database. The database is designed to support access to the pavement management data, provide for data analysis, update, and storage. The IPMP Task Force recommended that the database should provide for geographic referencing of linear and/or segmental data, use of an integrated database platform which has the capability of supporting dynamic segmentation, and be compatible with other management systems databases to allow for easy data integration. The paper provides guidance for agencies in other states which are attempting to develop a geographic information system (GIS) relational database for pavements or any other transportation system involving multiple jurisdictions. The paper describes the basic procedure used to develop the database and covers the basic database functions. This paper, however, only provides guidance on the mechanics of development of database and not overcoming the institutional issues associated with the development of multi-jurisdictional database. A significant level of effort was developed to overcome institutional issues, but a discussion of the institutional issues is reported elsewhere in the literature.(1)


A primary consideration in design of the IPMP database is data integration. The database should readily accommodate data sets from multiple sources, referenced using various location referencing methods, while limiting data redundancy and facilitating data maintenance and analysis.

Given these basic objectives, use of available computer-based tools in database design was investigated. This investigation centered on geographic information systems (GIS) and relational databases with dynamic segmentation capabilities. GIS was a logical choice because of its ability to capture, store, manage, retrieve, query, analyze, and present spatial data. Furthermore, all data maintained within the IPMP database possess a spatial component (they describe attributes at point locations or over linear segments of the highway system). The potential variability of segment locations or extents among data sets suggests the use of dynamic segmentation techniques, specifically GIS and database tools which possess these capabilities.

Dynamic Segmentation

Data sets which are linear in nature, such as those describing attributes along a highway system, may be stored using either fixed-length or variable-length static segmentation. Fixed-length static segments are broken into pre-defined lengths and are insensitive to changes in attributes, which can result in significant data redundancy. Variable-length static segments, on-the-other-hand, can be any length and broken for any reason, such as an attribute change (e.g. pavement type, pavement width, traffic, etc...). This segmentation allows for more flexible data collection and storage but may be too sensitive to attribute changes which may result in a large number of fine segments describing the highway network.

A relational database management system possessing dynamic segmentation capabilities, however, can accommodate integration of both fixed and variable length statically segmented data sets (see Figure 1). Such a database maintains highway attribute data in several database tables.

Figure 1. Dynamic Segmentation

For example, one table may contain traffic data, another may contain pavement distress data, and yet another may contain pavement history data. New segments can be generated interactively , or existing segments updated, by performing dynamic segmentation with the appropriate attribute tables. For example, a new segment may be generated based on attribute queries from two data sets, where the average annual daily traffic (AADT) is greater that 10,000 and the international roughness index (IRI) is greater than four, and pavement history data maybe updated with pavement distress data contained in another attribute table. These attribute tables need not possess common linear extents. Additionally, dynamic segmentation facilitates the collection of data in the most logical manner, whether fixed-length or variable-length, and simplifies redefinition of segment limits (e.g. changing the beginning and ending locations of a segment). Dynamic segmentation provides for more flexible data management without requiring the duplication of network geometry or data.(2) This flexibility is further enhanced with the application of GIS and its ability to accommodate multiple location referencing methods (which is described in the next section).

Location Referencing Methods

A location referencing method is a technique used to identify points or segments of a highway. There are two primary types of location referencing methods, linear and spatial. Components of a linear referencing method include identification of a route organization scheme, identification of a known point on a highway network, and measurement of a distance and direction from the known point. A typical database supporting dynamic segmentation is designed to accommodate either one or several linear referencing methods. If a single method is specified, any variation from this method will result in system incompatibility, limiting flexibility in data collection and maintenance. Comparatively, a database supporting multiple linear referencing methods is more flexible but more difficult to maintain. For example, a correspondence table outlining the relationship among the multiple linear referencing methods is required in order to cross-reference data sets.

A GIS database with dynamic segmentation capabilities simplifies management of highway attribute data linearly referenced using different methods (e.g. base point and control point). This is accomplished through the GIS's ability to interpret the complex spatial relationships among physical entities. Furthermore, the spatial nature of GIS enables the use of spatial referencing methods to identify the location of attribute data. In other words, coordinates identify the location of a point or linear extent along a highway. These coordinates may be either geographic (i.e. longitude, latitude) or projected (e.g. state plane). Given the increasing application of global positioning systems (GPS) in highway operations, such as inventory and survey, inclusion of these spatial referencing capabilities in database design seemed crucial.

By accommodating multiple location referencing methods, users are not constrained to collect or provide attribute data in a single manner. The potential impacts of technology changes, specifically in data collection techniques and achievable accuracy, should not be as significant, also making it easier to conform to changing system needs.


Four primary data sources are included in the Iowa Pavement Management Program database: Iowa Department of Transportation (DOT) Base Record Inventory System data (base records), Iowa DOT cartography, pavement history data provided by the Iowa DOT and local agencies, and pavement distress data collected centrally utilizing automated distress collection equipment. Each of these data sources are described in the following sections.

Base Record Inventory System

The Iowa comprehensive inventory of the roadway system is called the Base Record Inventory System. This system contains information about all roads and structures within the State. In fact, other highway databases are derived from the Base Record Inventory System. The Base Record Inventory System is maintained on an IDMS database software and is presently being redesigned to reside on a relational database and be more GIS compatible.

Highway system attribute data are stored using variable-length static segments, and new segments are created where changes in attribute values occur. Three methods are currently used to define the location of each segment along the non-NHS, Federal Aid Eligible system. For county owned roads, segments are defined using a public land survey referencing method, which consists of county, township, range, section, and road number attributes. City owned segments are identified by county, city, street number, and street sequence. The non-NHS portion of the primary system (under state jurisdiction) segments are identified by county, county sequence, and segment sequence

Only a portion of the total attributes stored in the Base Record Inventory System are germane to the pavement management database. These attributes include

As changes occur in the Base Record Inventory System, these changes must also be reflected in the Iowa Pavement Management Program database. Conversely, attribute data from the IPMP database will be integrated into the Base Record Inventory System as well.


The Iowa DOT Office of Cartography uses Bentley's MicroStation to create its highway and transportation maps. County cartography are maintained at a 1:100,000 scale (50 m accuracy), while city cartography are maintained at 1:24,000 scale (12 m accuracy). The Iowa DOT is currently investigating procedures to update the existing cartography, but more importantly, it is in the process of modifying these maps and attributing the graphic elements (in MicroStation) with the corresponding control attributes from the Base Record Inventory System. Each graphic element represents a single base record section, uniquely identified by control data attributes.

Pavement History

Pavement history information is provided by local highway operating agencies and the Iowa DOT. Data provided for each pavement management section includes:

Pavement management sections limits are determined by identifying the location of changes in pavement surface type, project history, traffic volumes and composition, functional classification, or the occurrence of jurisdictional boundaries. Boundaries for existing data collection activities and other databases of the highway operating jurisdictions are also taken into consideration. Sections are indicated on a paper map and accompanied by a written literal description. The sections average in length from approximately 0.5 kilometers in urban areas to 3.5 to 10 kilometers in rural areas.

Pavement Distress

Pavement condition (distress) data are collected through an automated mechanism, specifically, an ARAN van from Roadware Corporation. The ARAN van collects and stores video images of the pavement surface that are digitized and processed using pattern recognition software to identify, quantify and classify each distress. Rutting and roughness (IRI) are collected real time (speeds of up to 90 kmph) while collecting the rest of the surface distresses. Pavement distress data, which include cracking, potholes, patches, rutting, and ride, are collected and aggregated to linear segments of one hundred meters in length in both urban and rural areas. A global positioning system (GPS) receiver collects the geographic coordinates of the vehicle's position at each reading. These coordinates are differentially corrected (accurate within three to ten meters ) and used to denote the endpoints of each linear segment.


The IPMP database consists of two parts, a relational database with dynamic segmentation capabilities and GIS to integrate individual data elements into maps for display, interpretation, and integration with other spatial databases. However, it would be impractical to begin formulating a database design solution and implementation plan before fully understanding the software tools available and identifying those most practical for application. After identifying these specific tools, one can proceed with the subsequent implementation steps: creating and populating the database, data analysis, database maintenance, and data delivery and exchange.

Software Tools Selection

A major concern in the software selection process is how these two tools interface and whether these tools are used and supported by the Iowa DOT. The next two subsections briefly describe the selection process for these two tools.

Relational Database Management System

As noted in the "Dynamic Segmentation" section, linear referencing through dynamic segmentation requires relational database management system (RDBMS) technology. Relational database selection issues include dynamic segmentation capabilities, GIS interface, functionality (e.g. capacity, speed, SQL), compatibility, hardware platform (mainframe, workstation, or PC), and Iowa DOT support. Capacity and speed are major issues because of the potential enormity of the IPMP database.

Relational database options were identified and separated into two groups, those supported by the Iowa DOT and those currently not supported. Of the databases supported by the Iowa DOT, only Oracle and DB2 are relational databases. DB2 is primarily used by the Division of Motor Vehicles as an engine for storing document image data, while Oracle is in very limited use by the Iowa DOT as a GIS database. Other relational databases not supported by the Iowa DOT, but compatible with GIS, include Informix, Ingres, and SYBASE. Ultimately, Oracle was selected as the relational database development platform, primarily based on a general knowledge of its performance and its use within the Iowa DOT.

Geographic Information System (GIS)

The GIS utilized for the IPMP database must interface with a relational database and support dynamic segmentation capabilities. Two such GIS software platforms are ESRI's ArcInfo and Intergraph's MGE. ArcInfo is a full function GIS which uses an internal database, Info. ArcInfo can also access a third party relational database, such as Oracle but ArcInfo is still used as the link. MGE is also a full function GIS, but exclusively uses a third party relational database as well as a third party CAD engine, Bentley's MicroStation.

The dynamic segmentation requirements and capabilities of each GIS platform were investigated to determine which would serve as the best development platform. As a whole, there appeared to be no significant differences in the dynamic segmentation components of these two software platforms, suggesting that, once the GIS database is developed, it may be feasible to migrate to another system (GIS), if deemed appropriate.

MicroStation and MGE are used at the Iowa DOT. For this reason, MGE was selected as the GIS development platform. Further, we believe that if it is necessary, it is quite possible to migrate to another GIS platform without losing any of the effort required to develop the relational database.

Creating the Database

To limit the overall size of the databases, data are stored and managed (tiled) by Regional Planning Affiliation (RPA). An RPA covers a region consisting of multiple counties (3 to 9 counties) and the cities within each county. The state of Iowa is comprised of 18 RPAs. Data sets within each RPA are aggregated by county or city jurisdiction. In-other-words, data for all cities within an RPA are maintained together, and data for all counties are maintained together. Although this may decrease the data processing overhead, statewide analysis requires multiple queries, and city and county data must be analyzed separately. The following sections describe how the IPMP database is populated with the data sources discussed earlier.

Base Linear Network

A linearly referenced base GIS network must be adopted to enable the geographic overlay and dynamic segmentation of the highway attribute data (e.g. base record, pavement distress, and pavement history data). This network is developed using the attributed Iowa DOT cartographic data and Base Record Information System data.

The attributed cartographic data are provided in two files: a MicroStation file containing graphical representations of the roadways and a text file describing information about each graphic element, including the base record control attributes. The text files are loaded into the appropriate database table, and graphic elements associated with the corresponding records in these tables. Each record contains distance and length attributes in addition to the base record control attributes. The route, distance, and length attributes are updated with data from the base records attribute table (described in the next section), yielding a base point referenced base network.

The MicroStation graphics and associated attribute data used to create the base linear network is a by-product of the cartography attribution procedure. This procedure was established prior to IPMP database development. Therefore, the objectives of this process differ somewhat from the IPMP database needs. For example, a graphic element may be attributed as a single base record section but may actually represent multiple sections. Additionally, base record sections may be missing from cartography. Both of these occurrences result in an incomplete, or incorrectly represented, transportation network. These difficulties will be corrected over time.

Base Record Inventory System

The appropriate base record data, for the non-NHS, federal aid eligible roadways only, are exported from the Iowa DOT's IDMS mainframe database. These data are imported into a spreadsheet, and a kilometer point ( attribute is appended to each segment. The location of each segment along a route, with respect to the beginning of the route, is determined. The new attribute is updated with the cumulative length of the preceding segments along a route (street), providing a base point reference for the segment. The location of each base record segment within the highway system is now uniquely identifiable using a combination of the route (street) name, jurisdiction, and and length attributes. These updated base record data are then loaded into the appropriate relational database table.

Pavement History Data

Upon receiving pavement history data from the local highway operating agencies, the data are entered into a spreadsheet. Given the literal description of the location of each pavement management section, GIS capabilities are used to identify the geographic coordinates (longitude, latitude) of the endpoints of each section, yielding spatially referenced sections. The endpoint data are compiled in a text file and associated with the corresponding pavement management section in the spreadsheet. These updated history data are then loaded into the appropriate relational database table.

Pavement Distress Data

As pavement condition (distress) data are collected, the route (street) name and jurisdiction of the roadway are noted by the test vehicle operator(s). As testing begins on a new route or a new jurisdiction, this information is entered and the attributes are updated. Distress data are provided for 100 meter segments in a text file and referenced using both linear and differential GPS (DGPS) coordinates (longitude/latitude). The linear referencing method provided is only required by the distress data collection crew, helping them to track their progress. The DGPS coordinates are used with the IPMP database but must be converted to a coordinate system compatible with the Iowa DOT's existing cartography. Coordinate data are extracted from the original distress data files and input into a GIS coordinate conversion program. The converted coordinates are appended to the original distress data file (the original coordinates are also maintained), and the entire file is loaded into the appropriate relational database table.

Data Analysis

In its simple form, data analysis allows for the transformation of data between the different data sources (base record, pavement history information, and distress data) using dynamic segmentation. The data can be aggregated or disaggregated depending on which data source is used (see Figure 1).

Data transformation rules must be established for each data item to allow for consistent analysis of the data. For example, distress data (100 m test sections) will be aggregated to pavement management section data. Each distress element will have its data transformation rule. If we consider rutting (a safety related item), the aggregation rule might be to calculate the maximum rut depth from all test sections within each pavement management section. The value calculated will be assigned to the pavement management section rut depth and it will represent the worst rut depth along that section. When aggregating the pavement management sections data, the average will be used in most cases.

An additional consideration in data analysis is the differences in accuracy among the spatially-based, attribute data sets. For example, the base GIS network, on which all data integration depends, is accurate to 12 m (40 ft) in the cities and 50 m (167 ft) in the counties. Pavement distress data, on-the-other-hand, is accurate to 10 m (33 ft) or better in all areas. Therefore, a tolerance zone around the distress data points must be defined to ensure that the distress data will project correctly onto the base network.

Data Maintenance

Data maintenance is a very crucial operation for both integrating the IPMP database with other databases and the functionality of the database itself. Data maintenance include updating the database for roadway alignment changes, changes in route (street) designations, and annual date updates. Annual data updates include history information, distress data, and base record information.

Roadway Alignment Changes

The attribute data associated with the base GIS network must be updated when highway alignment or route (street) name change. For alignment changes, this may entail recalibrating all distance attributes along routes that have changed (see Figure 2). The cartographic data must also be modified to represent any changes in highway alignment. The primary data maintenance issue, however, is not how these changes can be performed, but how these changes can be identified. Since it is not necessary to maintain the relationship between the base network and the base record data (after the initial development of the base network), determining the location of roadway alignment changes and route name changes may be somewhat difficult.

Route Designations

Dynamic segmentation requires that each route be uniquely identified. The route (street) name and jurisdiction attributes uniquely identify each route. Unfortunately, not all base record sections possess a unique route name. While the base network is being developed, an attempt is made to assign unique names to these routes based on history data from the local highway agencies.

Differences in route designations may be as seemingly insignificant as "1 St" versus "1 Street". Many discrepancies exist among the base record, pavement history, and distress data, which must be identified and corrected. Some of these discrepancies are identified by actually plotting the endpoints of pavement history and distress sections and comparing their route designations to those of the most proximate base network graphics. Upon identifying what appears to be a correct route designation, all appropriate database table(s) are updated. All changes must also be provided to the Iowa DOT and reflected in the Base Record Inventory System. If this is not done, the Base Record Inventory System will contain the old route names, and Iowa DOT's yearly updates of base record data (for these routes) will not project onto the base GIS network.

Figure 2. Roadway Alignment Changes

Annual Updates

Annual pavement history updates will be provided by the local highway operating agencies, annual base record updates will be provided by the Iowa DOT, and bi-annual updates will be provided for pavement condition. Populating the IPMP database with these data sets will be nearly the same as the methods discussed previously, with the possible exception of identification of pavement management section limits.

At present, it is somewhat difficult to estimate the amount of time it will take to update the database annually. It is reasonable to assume that it may take as long to update the database, initially, as to create the database. However, as the process progresses, and procedures are established, the time requirements should decrease significantly.

Data Access, Delivery, and Exchange

The IPMP database, with its use of a relational database and GIS, is quite complex. An inexperienced user may find it difficult to perform a simple analysis of the data. Access to the system is also somewhat limited. A more user-friendly, accessible system is desirable.

Users of the IPMP database can be separated into two main groups: the Iowa DOT and local highway operating agencies (cities and counties). Each of these groups will have different needs, with respect to access and analysis. Questions that remain to be addressed include: who should have access to the data, how should users access the data, how much experience should they have, and what types of analyses are necessary? These questions will serve to identify the access and analysis needs of both groups and dictate the approaches taken to meet these needs. For example, data access may be provided through an intranet or internet and analysis performed using a desktop GIS or web application. On-the-other-hand, access issues may be limited to the format in which the data will be provided.

Initially, pavement distress data is summarized by pavement management section, exported from the database, organized by jurisdiction, and distributed to the local agencies on paper and electronically (spreadsheet format). Raw pavement distress data are also available in these formats.


This paper covered the development of a large and complex database to support pavement management by Iowa agencies at the local, regional, and state level. In addition, the project will provide these agencies with pavement management decision making tool to allow them to conduct pavement management within their own jurisdiction. The paper discusses the technical details of constructing the database but does not discuss the many institutional issues which were addressed in the process of creating a multi-jurisdiction system.

Development of the database centrally, as opposed to allowing each agency to develop their own database, creates significant economies to scale and provides a database with the functionality that most Iowa agencies could not afford. At the same time, these agencies have access to high quality data, which is consistent from one jurisdiction to the next, to conduct pavement management within their own jurisdiction. Decisions on the allocation of resources are best left to the highway manager, planner, or engineer within each jurisdiction who is knowledgeable of local needs and conditions. On the other hand, creating such a database, provides significant challenges. The database development and initiating the population of the database will have taken three year, when we reach completion at the end of 1997.


1. T.H. Maze and Omar G. Smadi, "Taxonomy of Institutional Barriers to the Implementation of Pavement Management Systems," Proceedings of the Seventh Maintenance Management Conference, National Academy Press, Washington, D.C., 1995.

2. Lewis, Simon and Roger Petzold. "Transportation Location Referencing Systems: Problem Definition and Current Topics." Pre-Conference Workshop, AASHTO GIS-T Symposium, Sparks, Nevada, 1995.

CTRE is an Iowa State University center, administered by the Institute for Transportation.

Address: 2711 S. Loop Drive, Suite 4700, Ames, IA 50010-8664

Phone: 515-294-8103
FAX: 515-294-0467


Iowa State University--Becoming the Best