Successful Implementation of a GIS-Based Pavement Management System

The quality of pavement condition data is important not only in assessing the current condition of the network but also in predicting its future condition and planning future maintenance and rehabilitation (M&R) activities. This paper provides a quantitative assessment of the impact of error magnitude and type (systematic and random) in pavement condition data on the accuracy of pavement management system (PMS) outputs (i.e., forecasted needed budget and M&R activities in a multiyear planning period). The process developed to simulate the propagation of pavement condition errors to PMS output consisted of five components: condition data generation, error perturbation, condition prediction, M&R prioritization, and output generation. This process was applied to the 2011 pavement condition data set of the Bryan District of the Texas Department of Transportation. In 2011, the roadway network of the Bryan District consisted of approximately 3,200 roadbed centerline miles. The study results show that both systematic and random errors can highly distort some PMS output parameters, even in error ranges that may be considered acceptable in practice. These effects tend to persist throughout the planning period. The findings of this study can help highway agencies optimize processes for collecting pavement condition data by focusing on error levels and types that cause the greatest impact on PMS output.

The widespread application of geographic information systems (GISs) at airports is detailed through surveys of U.S. airports. A recent survey conducted through the Airport GIS Committee of the American Association of Airport Executives indicated that more than 60 percent of airports use GISs or plan to use GISs within the next 3 years. The application of GISs for infrastructure management, environmental analysis, and airport operations is becoming commonplace at larger U.S. airports. Integration of infrastructure management in general and pavement management in particular with airportwide GISs provides far greater management capabilities than traditional infrastructure management systems. The development of integrated airport GISs and the availability of affordable, differentially corrected Global Positioning System receivers have resulted in a paradigm shift in methods of infrastructure management. As the new millennium approaches, the state of the art in infrastructure and pavement management is turning away from the traditional forms toward map-based systems that have sophisticated analytical tools. In the case of pavement management, the use of map-based analysis will overcome many of the shortcomings of the traditional MicroPAVER inspection process. The capabilities of the current state of the art in pavement management are detailed.

This paper describes the development of a cracking prediction model for Portuguese conditions which is expected to integrate the Pavement Management System (PMS) of Estradas de Portugal. The World Bank's highway development and management (versions III and 4) and PARIS models are used as reference for the development of a deterministic (mechanistic-empirical) model, using pavement condition data from sections of the main road network. A two-phase distress evolution model is proposed where the initiation of cracking (1st phase) is ruled by a different equation than the progression of cracking (2nd phase). Cracking initiation is predicted on a traffic basis, from the annual traffic load and the structural capacity of the pavement. An absolute model is presented and recommended for the maintenance and rehabilitation (M&R) programming in the long-term and for the analysis of non-cracked segments. Absolute and relative type models were obtained for cracking progression. The relative model shows better agreement to data and is proposed for short- to medium-term analysis on segments with cracking history, while the absolute model is proposed for the M&R programming in the long-term and the analysis of non-cracked segments. Finally, the recommended model is evaluated based on the application to a set of pavement structures defined in the Portuguese pavement design guide.

This article will discuss how to improve the ability to protect the collection mural with Lidar and Geographic Information System (GIS) technology. Firstly, we gain three dimensional point clouds through the Lidar technology, and make high-precision Digital Orthophoto Map (DOM), which has the same scale as the real collection mural. Secondly, the spatial disease database will be built based on the DOM of collection mural with the GIS technology. Then we can get some useful dataset for protecting collection mural, such as disease map and trend map. Disease map, based on some spatial analysis and spatial statistics, will tell you where the disease is, and how serious the disease is. Lastly, but importantly, we can classify the disease grade based on the collection mural with decision tree. So protector of collection mural knows what’s the most serious disease. It is better than the traditional methods both in accuracy and efficiency. Finally, this article has confirmed the related method efficiency and the precision in the collection mural of Greatly Summons Temple.

Petrotrin, a state owned company has production operations which span the whole of south Trinidad. The company has numerous wells, the miles of gas and oil lines, and the passage of these lines through agricultural areas, towns and villages are a major environmental concern to the company. Many of these installations were inherited from predecessor companies. Geographical Information System (GIS) technology is only about twenty years, and its usefulness over the years has shown that it is a cost saving to the company. Groups monitoring GIS has concluded that it is a billion dollar industry if one were to add the value of the software, hardware and services. Other computer software packages are not as beneficial as GIS. In GIS the storage of data is independent of the mode of presentation4. GIS can provide the following information needed for management to make the right decisions: ∼identify all areas within 100 feet of the wells∼identify all watercourses within 100 feet of installations∼identify all buildings, agricultural lands that are within 100 feet of the gas and crude oil pipelines among others. Several departments within Petrotrin can look at the same data simultaneously because GIS allows that flexibility. Previously, in using paper maps only one person can look at the information since there were not several copies of these maps circulating. If these maps had to be updated it took a long time. Now with the GIS software and hardware packages more than one person can look at the same data and make faster decisions. The report presented herein conveys the benefits of using GIS in environmental decisions in Petrotrin's production operations.

Rational use and protection of soils in market conditions requires adequate application of new scientific and methodological approaches. One of such systems-analytical methods of organizing a soil cadastre is the combination of traditional ground-based methods with geographic information systems (GIS) technologies based on the widespread use of aerospace images of high resolutions. The totality of information necessary for mapping soil cover structures and their quantitative assessment is described in GIS databases. Data integration is implemented through a spatial and attributive component in the form of: the results of topographic and thematic maps. At the same time, the creation of attributive GIS databases involves the digitization of thematic maps linked in a single cartographic projection (which was a topographic map at a scale of 1:50,000). As results of the research, digital soil maps for the Chingirlau district of the West Kazakhstan region were created on the basis of GIS technologies, using the ArcGIS software products. It was established that within the limits of the Chingirlau district of the West Kazakhstan region, dark chestnut soils in combination with various soil combinations pre-dominate in the structure of the soil cover. They are formed on loess-like loams in the conditions of the dry steppe zone with a non-leaching type of water regime under fescue-grass, forb-grass-wormwood, meadowsweet-grass with wormwood plant communities. To improve the quality of generalized maps (district, regional, etc.), it is necessary to create objective automated methods for generalizing maps in a digital environment. A method for compiling a digital soil map using the ArcGIS soft-ware product, accessible to a wide range of GIS users, has been developed. To compile soil maps, it is possible to use any scanned cartographic bases, photoplans, and other raster materials. Based on the developed methodology, a large-scale soil map of the Chingirlau district of the West Kazakhstan region was created on the basis of soil maps of rural districts made using GIS technologies.

The Baltimore City Fire Department (BCFD) has been installing smoke alarms city wide for more than three decades. Though data on each visit are entered into a database, no system existed for using these data for planning or evaluation. The objective of this study is to use Geographic Information System (GIS) technology and existing databases to 1) determine the number of residences in need of a home visit; 2) determine total visits, visits per household, and number of homes entered for eligible households; and 3) demonstrate integration of various data via GIS for use in prevention planning. The tax assessment database was queried to determine the number of eligible (as determined by BCFD policy) residences in need of a visit. Each attempted BCFD home visit was coded to identify, if the BCFD personnel interacted with residents ("pass door") and installed alarms. Home visits were geocoded and compared to the tax assessment database to determine city wide pass door rates. Frequency of visits was run by individual residences to measure efficiency. A total of 206,850 residences met BCFD eligibility for a home visit. In 2007, the BCFD attempted 181,757 home visits and 177,213 were successfully geocoded to 122,118 addresses. A total of 122,118 eligible residences (59%) received a home visit. A total of 35,317 residences (29%) received a repeat visit attempt. The pass door rate was 22% (46,429) of all residences. GIS technology offers a promising means for fire departments to plan and evaluate the fire prevention services they provide.

The inherent geographic nature of displacement in refugee camps is requiring further use of Geographic Information Systems (GIS) technology for community-based information and asset management. Additionally, refugees have a fundamental need for livelihood development in host countries due to the protracted nature of displacement. This paper presents our work on the Refugee GIS or ‘RefuGIS’ project that addresses these two topics via a training and capacity building education program and community mobilization efforts. RefuGIS is currently at the prototype level of development in the Za'atari Syrian Refugee Camp in northern Jordan. RefuGIS is the one of world's first efforts at enabling GIS capacity among refugees themselves and was funded by a grant from the United Nations High Commissioner for Refugees (UNHCR) Innovation fund. Specifically, this paper will discuss (a) design of the RefuGIS educational program via utilization of a non-profit GIS software donation, hardware procurement and customized GIS educational curriculum, (b) selection of refugee participants through spatial thinking aptitude testing, (c) practical experiences and lessons learned from education, training, and capacity building of refugees on the topics of GIS and related information technology skills, (d) insights into use of GIS as a community information and asset management tool by refugees themselves as demonstrated by evaluation of project outputs such as reference mapping products and field surveys conducted by refugees. Lessons learned from the RefuGIS project, even at the prototype stage, have potential to inform other refugee community information and asset management projects. Since creation of the project, refugees in Za'atari camp have been able to obtain cash-for-work GIS jobs in Za'atari using the skills learned via the RefuGIS project. The RefuGIS project demonstrates the refugee livelihood potential that training and capacity building around GIS can build as well as the empowerment effect that technology education and livelihood development can bring to refugees.

The use of Airport Pavement Management Systems (APMS) in the United States began in the early 1980s. By the mid 1990s, the use of APMS was prevalent throughout the country, and today, more than 80 percent of one segment of the industry—state aviation agencies—use APMS tools to manage their airports’ pavements. When applied properly, an APMS provides agencies with indispensable information to make cost-effective decisions about the preservation and rehabilitation of the pavement network. Further, an APMS allows agencies to evaluate the long-term impacts of decisions made about their pavement infrastructure. Although state aviation agencies have used APMS tools for over 20 years to store and evaluate pavement inventory, condition, and performance data, no one is reporting on these data at the national level. For example, very limited documentation can be found on overall pavement inventory, condition, and performance at airports in the United States. This is unfortunate because pavement management data compiled at the national level could yield very interesting and useful information about a variety of topics, including the status of overall airport pavement conditions in the United States and the typical performance of different surface types in different climatic regions. To address this lack of information at the national level, the paper collected airport pavement management data from 22 states, representing 1,360 airports, 20,000 pavement sections, and approximately 2 billon square feet of pavement. Most of the 22 states do not tract the airport classification, such as general aviation, reliever, commercial, and so on. Therefore, it is not possible to break out the results by airport type. However, it is likely that at least 75 percent of the airports are general aviation, with most of the rest being reliever airports. The data represents six states in the Western and Northern Atlantic regions, seven states in the Central region, and three states in the Southern region. All the data were stored in a Micro PAVER database, which facilitated the analysis of the data. The collected data were analyzed to identify national and regional trends. Specifically, conditions at the national and regional level, broken out by pavement use and surface type, were evaluated. Further, pavement performance models were developed to identify typical performance trends of different pavement types, pavement uses and in different climatic regions. This paper presents the results of this analysis.

Le xington, in central Kentucky, is the second largest city in the state. Local government is by a mayor and council of elected representatives from twelve districts and three at-large representatives. The Department of Public Works headed by a Commissioner, who reports to the mayor and city-county council, administers the streets and roads system. The street and road network in Lexington consists of approximately 720 centerline miles. Approximately 100 miles are rural in nature and 620 miles are urban. Approximately 95 percent are bituminous surfaced roads; a majority of the remainder is constructed of portland cement concrete. Increasing costs for constructing and maintaining the street and road network was a stimulus to implement a systematic pavement and road surface management system. Available alternatives were reviewed, and it was decided to maximize in-house resources of the Lexington-Fayette Urban County Government. Meetings with public works officials were used to establish criteria for implementation of a management program: (a) program for visual condition survey of pavements, (b) procedure(s) to determine structural deficiencies for critical pavements identified in the visual condition survey, and (c) utilization of the above information to estimate rehabilitation strategies and their associated costs. The paper describes and documents three phases of implementation of a pavement and road surface management system. Phase I included development of a system­ wide inventory of pavements and a pavement condition rating system for both flexible and rigid pavements. Phase II dealt with the modifications to a microcomputer program to process pavement condition ratings for ranking pavements on the basis of need and also to estimate pavement maintenance and rehabilitation costs. Phase III included administrative and training activities necessary for implementation of the pavement management program. Training generally addressed three areas: (1) collection of pavement condition and distress information, (2) operation of the microcomputer program for data processing and analyses, and (3) interpretation and utilization of results of the analyses, Finally, the paper describes current research and development relating to refinements and modifications for the Lexington situation.

Pavement performance assessment and prediction are crucial for efficient infrastructure management and strategic planning of maintenance activities. Conventional techniques are insufficient and lack the efficiency and flexibility required for modern transportation networks. This study proposes a groundbreaking integrated approach that merges machine learning (ML) classification techniques with Geographical Information Systems (GIS) to evaluate road conditions using the Pavement Condition Index (PCI) and the International Roughness Index (IRI). Given that IRI data collection is more straightforward and cost-effective than gathering pavement distress data, this study aims to classify the IRI of flexible pavements to estimate PCI models using advanced ML algorithms (Artificial Neural Network (ANN), Adaptive Boosting (AdaBoost), Support Vector Machine (SVM), Decision Trees (DT), and Random Forest (RF)) and accurately determine pavement conditions. This research gathered 1042 data points using a smartphone application, TotalPave, to measure the IRI values for the (Nizwa–Muscat) and (Muscat–Nizwa) routes in the Sultanate of Oman. It meticulously applied feature selection techniques to identify the pavement parameters significantly impacting pavement performance. The research then spatially visualized and analyzed the results to determine the critical pavement sections. Among the ML models, RF demonstrated outstanding performance with an accuracy rate of 99.9% and an F1-score of 99. SVM has the lowest accuracy of 85.8% and an F1-score of 40.3. A comprehensive assessment comprising a confusion matrix, uncertainty analysis, box and whisker plot, and noise sensitivity provides in-depth insights into the reliability and consistency of predictions. The ML and GIS methods revolutionized the way transportation agencies interpret and implement their findings. The proposed framework is not merely a tool, but a transformative solution that facilitates the formulation of proactive maintenance strategies and optimizes resource utilization by providing a scalable and intelligent decision-support tool designed specifically for pavement management systems (PMS).

Use of GIS technology to analyse the health effect of exposure to heavy traffic pollution in an Italian general population sample

In this chapter, we discuss the various ways in which the emergent technology of geographic information systems (GIS) can best be utilized within the urban planning process. One of the major difficulties of developing effective integration between GIS and the functions of the planning process involves the comparative crudity of the present array of functions within GIS when compared with those functions which are required in urban planning. We first present typical GIS functions and discuss their comparative crudity, and then we illustrate the sorts of functions which are necessary to the urban planning process in the form of models and spatial analytic techniques. This serves to identify the functions which GISs require if they are to be used most effectively within planning. The rational planning process used to organize these functions is outlined and the ways in which the various phases and functions are influenced and influence the use of GIS noted. Different ways in which computer models might be embedded in GIS and into planning processes are defined and the conditions under which these different strategies can be employed are noted. We conclude the chapter with some speculations concerning the future of GIS and computer technology more generally within the planning process.

Throughout the course of human history, significant pressures have been in place to develop the coastline. Whether these pressures are a result of commercial and industrial needs or recreational preference, humans have always tended to settle at or near the waterfront. While obvious benefits can be reaped from this anthropogenic pattern, it also results in significant portions of the world's population subject to flood hazards. With the potential for these hazards to increase due to climate change, coastal zone managers and planners require tools to mitigate the risk to this population. One such tool is Geographic Information Systems (GIS). With GIS technology being at the forefront of Federal Emergency Management Agency's (FEMA) Map Modernization efforts, it has proven to be an effective tool in coastal hazard mitigation. The GIS technology is extensively used to evaluate land use and population change in the coastal areas which ultimately drives the coastal hazard mapping. The identification of risk requires analyzing large GIS data sets including topographic data (e.g. TIN {triangular irregular network} and GRID), orthophotography, land use data, and census population data. The GIS technology can effectively analyze these large data sets using the calculation algorithms built in to the GIS software such ArcGIS and present information that will guide decision makers. The 3D rendering capability of GIS software can be used to visualize various scenarios which aid in effective hazard identification and mitigation. The 3D GIS mapping and animation tools can also be applied to simulate various disaster scenarios that can ultimately aid planners in prevention of human and property loss during coastal disasters. In FEMA Region I, CDM, a FEMA study contractor and its partner OCC have been involved in numerous coastal hazard studies across New England. Together CDM and OCC have scoped total of six counties and have been involved in coastal engineering and mapping activities in more than 10 counties across New England. This paper will present methodologies to analyze various data sources and identify coastal flooding risks.

Geographic Information System (GIS) technology has many applications and plays a vital role in the majority of the daily operations by government and public administration. However, due to its technical complexity and cost, communities lacking the expertise and resources cannot benefit from this technology. The OpenCIS project, a user‐friendly free Open Source GIS‐based Web Community Information System, seeks to address this issue by bridging the gap between a simple map viewer and full GIS, representing one of the first steps towards the goal of grassroots empowerment through GIS technology.