Field Data Acquisition Technologies for Iowa Transportation Agencies, HR-366 August 1994

This report describes the results of the research project investigating the use of advanced field data acquisition technologies for lowa transponation agencies. The objectives of the research project were to (1) research and evaluate current data acquisition technologies for field data collection, manipulation, and reporting; (2) identify the current field data collection approach and the interest level in applying current technologies within Iowa transportation agencies; and (3) summarize findings, prioritize technology needs, and provide recommendations regarding suitable applications for future development. A steering committee consisting oretate, city, and county transportation officials provided guidance during this project. Technologies considered in this study included (1) data storage (bar coding, radio frequency identification, touch buttons, magnetic stripes, and video logging); (2) data recognition (voice recognition and optical character recognition); (3) field referencing systems (global positioning systems [GPS] and geographic information systems [GIs]); (4) data transmission (radio frequency data communications and electronic data interchange); and (5) portable computers (pen-based computers). The literature review revealed that many of these technologies could have useful applications in the transponation industry. A survey was developed to explain current data collection methods and identify the interest in using advanced field data collection technologies. Surveys were sent out to county and city engineers and state representatives responsible for certain programs (e.g., maintenance management and construction management). Results showed that almost all field data are collected using manual approaches and are hand-carried to the office where they are either entered into a computer or manually stored. A lack of standardization was apparent for the type of software applications used by each agency--even the types of forms used to manually collect data differed by agency. Furthermore, interest in using advanced field data collection technologies depended upon the technology, program (e.g.. pavement or sign management), and agency type (e.g., state, city, or county). The state and larger cities and counties seemed to be interested in using several of the technologies, whereas smaller agencies appeared to have very little interest in using advanced techniques to capture data. A more thorough analysis of the survey results is provided in the report. Recommendations are made to enhance the use of advanced field data acquisition technologies in Iowa transportation agencies: (1) Appoint a statewide task group to coordinate the effort to automate field data collection and reporting within the Iowa transportation agencies. Subgroups representing the cities, counties, and state should be formed with oversight provided by the statewide task group. (2) Educate employees so that they become familiar with the various field data acquisition technologies.

Improved Employment Data for Transportation Planning, 1998

Transportation planners typically use census data or small sample surveys to help estimate work trips in metropolitan areas. Census data are cheap to use but are only collected every 10 years and may not provide the answers that a planner is seeking. On the other hand, small sample survey data are fresh but can be very expensive to collect. This project involved using database and geographic information systems (GIS) technology to relate several administrative data sources that are not usually employed by transportation planners. These data sources included data collected by state agencies for unemployment insurance purposes and for drivers licensing. Together, these data sources could allow better estimates of the following information for a metropolitan area or planning region: · Locations of employers (work sites); · Locations of employees; · Travel flows between employees’ homes and their work locations. The required new employment database was created for a large, multi-county region in central Iowa. When evaluated against the estimates of a metropolitan planning organization, the new database did allow for a one to four percent improvement in estimates over the traditional approach. While this does not sound highly significant, the approach using improved employment data to synthesize home-based work (HBW) trip tables was particularly beneficial in improving estimated traffic on high-capacity routes. These are precisely the routes that transportation planners are most interested in modeling accurately. Therefore, the concept of using improved employment data for transportation planning was considered valuable and worthy of follow-up research.

2008 Iowa Real Property Appraisal Manual, May 2008

********NOTE: There are nine sections to this manual, all in separate files.************* **********NOTE: Large files may take longer to open******** The basis of real property assessment in Iowa is market value as defined in Iowa Code §441.21. Iowa Code §§ 421.17(17) and 441.21(h) provide that assessment jurisdictions follow the guidelines and rules in this manual to help achieve uniformity in assessments. Assessors are encouraged to use the International Association of Assessing Officers’ Standard on Mass Appraisal of Real Property in their mass appraisal practices. Estimating market value in mass appraisal involves accurately listing properties, developing a sales file that includes the primary influences on market value, and developing models for subsets of properties that share common market influences using recognized mass appraisal techniques. The assessment of an individual property should not be based solely on the sale price. The Uniform Standards of Professional Appraisal Practice (USPAP) standard 6 says “In developing a mass appraisal, an appraiser must be aware of, understand, and correctly employ those recognized methods and techniques necessary to produce and communicate credible mass appraisals.” Accurate listing of property is the basis of a good mass appraisal program. On-site inspection and listing of property is essential in developing a good data base for revaluation. A physical review, including an on-site verification of property characteristics, should be conducted at least every four to six years. Land values should be reviewed every two years. Factors influencing the market of each property type should be identified and collected so that these factors can be considered in the mass appraisal model. It is equally important to maintain the data once it is collected. Accessing local government permit systems should be a part of a good data maintenance program along with an inspection program. Current cadastral maps and geographical information systems (GIS) are tools that are integral in checking accuracy of listings and maintaining a comprehensive data base.

Artificial-Intelligence-Based Optimization of the Management of Snow Removal Assets and Resources Final Report, October 2002

Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent snow removal asset management system (SRAMS). The system has been evaluated through a case study examining snow removal from the roads in Black Hawk County, Iowa, for which the Iowa Department of Transportation (Iowa DOT) is responsible. The SRAMS is comprised of an expert system that contains the logical rules and expertise of the Iowa DOT’s snow removal experts in Black Hawk County, and a geographic information system to access and manage road data. The system is implemented on a mid-range PC by integrating MapObjects 2.1 (a GIS package), Visual Rule Studio 2.2 (an AI shell), and Visual Basic 6.0 (a programming tool). The system could efficiently be used to generate prioritized snowplowing routes in visual format, to optimize the allocation of assets for plowing, and to track materials (e.g., salt and sand). A test of the system reveals an improvement in snowplowing time by 1.9 percent for moderate snowfall and 9.7 percent for snowstorm conditions over the current manual system.

Stream Stabilization in Western Iowa, HR-352, 1994

Stream channel erosion in the deep loess soils region of western Iowa causes severe damage along hundreds of miles of streams in twenty-two counties. The goal of this project was to develop information, systems, and procedures for use in making resource allocation decisions related to the protection of transportation facilities and farmland from damages caused by stream channel erosion. Section one of this report provides an introduction. Section two presents an assessment of stream channel conditions from aerial and field reconnaissance conducted in 1993 and 1994 and a classification of the streams based on a six stage model of stream channel evolution. A Geographic Information System is discussed that has been developed to store and analyze data on the stream conditions and affected infrastructure and assist in the planning of stabilization measures. Section three presents an evaluation of two methods for predicting the extent of channel degradation. Section four presents an estimate of costs associated with damages from stream channel erosion since the time of channelization until 1992. Damage to highway bridges represent the highest costs associated with channel erosion, followed by railroad bridges and right-of-way; loss of agricultural land represents the third highest cost. An estimate of costs associated with future channel erosion on western Iowa streams is also presented in section four. Section four also presents a procedure to estimate the benefits and costs of implementing stream stabilization measures. The final section of this report, section five, presents information on the development of the organizational structure and administrative procedures which are being used to plan, coordinate, and implement stream stabilization projects and programs in western Iowa.

Wireless Sensor Networks for Infrastructure Monitoring, TR-611, 2010

A good system of preventive bridge maintenance enhances the ability of engineers to manage and monitor bridge conditions, and take proper action at the right time. Traditionally infrastructure inspection is performed via infrequent periodical visual inspection in the field. Wireless sensor technology provides an alternative cost-effective approach for constant monitoring of infrastructures. Scientific data-acquisition systems make reliable structural measurements, even in inaccessible and harsh environments by using wireless sensors. With advances in sensor technology and availability of low cost integrated circuits, a wireless monitoring sensor network has been considered to be the new generation technology for structural health monitoring. The main goal of this project was to implement a wireless sensor network for monitoring the behavior and integrity of highway bridges. At the core of the system is a low-cost, low power wireless strain sensor node whose hardware design is optimized for structural monitoring applications. The key components of the systems are the control unit, sensors, software and communication capability. The extensive information developed for each of these areas has been used to design the system. The performance and reliability of the proposed wireless monitoring system is validated on a 34 feet span composite beam in slab bridge in Black Hawk County, Iowa. The micro strain data is successfully extracted from output-only response collected by the wireless monitoring system. The energy efficiency of the system was investigated to estimate the battery lifetime of the wireless sensor nodes. This report also documents system design, the method used for data acquisition, and system validation and field testing. Recommendations on further implementation of wireless sensor networks for long term monitoring are provided.

Highway Maintenance Concept Vehicle Final Report: Phase Three, 2001

This report documents Phase III of a four-phase project. The goals of the project are to study the feasibility of using advanced technology from other industries to improve he efficiency and safety of winter highway maintenance vehicle operations, and to provide travelers with the level of service defined by policy during the winter season at the least cost to the taxpayers. The results of the first phase of the research were documented in the Concept Highway Maintenance Vehicle Final Report: Phase One dated April 1997, which describes the desirable functions of a concept maintenance vehicle and evaluates its feasibility. Phase I concluded by establishing the technologies that would be assembled and tested on the prototype vehicles in Phase II. The primary goals of phase II were to install the selected technologies on the prototype winter maintenance vehicles and to conduct proof of concept in advance of field evaluations planned for Phase III. This Phase III final report documents the work completed since the end of Phase II. During this time period, the Phase III work plan was completed and the redesigned friction meter was field tested. A vendor meeting was held to discuss future private sector participation and the new design for the Iowa vehicle. In addition, weather and roadway condition data were collected from the roadway weather information systems at selected sites in Iowa and Minnesota, for comparison to the vehicles' onboard temperature sensors. Furthermore, the team received new technology, such as the mobile Frensor unit, for bench testing and later installation.

GPS to LRM: Integration of Spatial Point Features with Linear Referencing Methods, 2001

Global positioning systems (GPS) offer a cost-effective and efficient method to input and update transportation data. The spatial location of objects provided by GPS is easily integrated into geographic information systems (GIS). The storage, manipulation, and analysis of spatial data are also relatively simple in a GIS. However, many data storage and reporting methods at transportation agencies rely on linear referencing methods (LRMs); consequently, GPS data must be able to link with linear referencing. Unfortunately, the two systems are fundamentally incompatible in the way data are collected, integrated, and manipulated. In order for the spatial data collected using GPS to be integrated into a linear referencing system or shared among LRMs, a number of issues need to be addressed. This report documents and evaluates several of those issues and offers recommendations. In order to evaluate the issues associated with integrating GPS data with a LRM, a pilot study was created. To perform the pilot study, point features, a linear datum, and a spatial representation of a LRM were created for six test roadway segments that were located within the boundaries of the pilot study conducted by the Iowa Department of Transportation linear referencing system project team. Various issues in integrating point features with a LRM or between LRMs are discussed and recommendations provided. The accuracy of the GPS is discussed, including issues such as point features mapping to the wrong segment. Another topic is the loss of spatial information that occurs when a three-dimensional or two-dimensional spatial point feature is converted to a one-dimensional representation on a LRM. Recommendations such as storing point features as spatial objects if necessary or preserving information such as coordinates and elevation are suggested. The lack of spatial accuracy characteristic of most cartography, on which LRM are often based, is another topic discussed. The associated issues include linear and horizontal offset error. The final topic discussed is some of the issues in transferring point feature data between LRMs.

Multimodal Investment Analysis Methodology, Phase One: The Conceptual Model, 1998

The purpose of this project is to develop an investment analysis model that integrates the capabilities of four types of analysis for use in evaluating interurban transportation system improvements. The project will also explore the use of new data warehousing and mining techniques to design the types of databases required for supporting such a comprehensive transportation model. The project consists of four phases. The first phase, which is documented in this report, involves development of the conceptual foundation for the model. Prior research is reviewed in Chapter 1, which is composed of three major sections providing demand modeling background information for passenger transportation, transportation of freight (manufactured products and supplies), and transportation of natural resources and agricultural commodities. Material from the literature on geographic information systems makes up Chapter 2. Database models for the national and regional economies and for the transportation and logistics network are conceptualized in Chapter 3. Demand forecasting of transportation service requirements is introduced in Chapter 4, with separate sections for passenger transportation, freight transportation, and transportation of natural resources and commodities. Characteristics and capacities of the different modes, modal choices, and route assignments are discussed in Chapter 5. Chapter 6 concludes with a general discussion of the economic impacts and feedback of multimodal transportation activities and facilities.