Geographic information systems (GIS)

Asset management is critical for local and state governments to track assets and plan for maintenance of assets that will provide the greatest return on investment (ROI) for the agency. The use of geographic information system (GIS) applications, tools and geospatial data can provide agencies with the most accurate inventory of assets, a basis to determine and maintain condition, cost-effective mobile tracking and maintenance of assets such as signs, culverts, roads and bridges, and reporting tools to justify asset expenditures. However, challenges such as agency size and location, access to accurate and timely geospatial data, and lack of information about the best data processes, applications and tools to use limits local agency use of GIS for asset management. A Minnesota Local Road Research Board project examined current local agency practices and reviewed existing mobile technologies to recommend best practices for the efficient, cost-effective use of GIS mobile technology for better managing agency assets. This Quick Start Guide offers brief synopses of the three case studies appearing in the project’s final report and highlights five software options used by Minnesota local agencies.

Asset management is critical for local and state governments to not only track assets but to also plan for maintenance of assets that will provide the greatest return on investment for the agency. The use of geographic information system (GIS) applications, tools and geospatial data can provide agencies with the most accurate inventory of assets, a basis to determine and maintain condition, cost-effective mobile tracking and maintenance of assets such as signs, culverts, roads and bridges, and reporting tools to justify asset expenditures. The research team’s two-part survey effort gathered information about the use of GIS mobile technology by Minnesota local agencies. A review of selected mobile technologies highlighted the specific tasks and functionality the technology provided to assist with an agency’s asset-management program. Using this information and the results of extensive interviews with selected local agencies, the research team developed three case studies that offer recommendations for agencies at different stages in the use of GIS for asset management: Case Study 1: Getting Started Case Study 2: Utilizing Mobile Technology for Asset Management Case Study 3: Moving Beyond "What and Where" to Analysis and Forecasting

This Implementation Summary pertains to report 2020-04, Development of Pavement Condition Forecasting for Web-Based Asset Management for County Governments.

MnDOT Office of Transportation System Management (OTSM) desires to reduce the cycle time for collecting road data updates from county sources and, opportunistically, capture additional data about road and ancillary uses, e.g. bicycle access. Specifically, this project researched free or low-cost aerial or spatial data from government and other sources to determine if the imagery and spatial data would provide a source of sufficient resolution, accuracy and low cost to maintain MnDOTs various mapping needs.

Phase 4 Slope Vulnerability Assessments is a continuation of Phases 1-3 previously conducted by WSB and MnDOT to determine the risk of slope failure along state highways. This phase includes 16 counties located in districts 1 and 3 and the Metro. The three main components of the model are 1) identify past slope failures, 2) model the causative factors of past failures and how they vary locally, and 3) model the risk of new slope failures. The vulnerability factors and expected failure types reflect the diverse geomorphology of Northeast Minnesota. Vulnerability factors for the new study area include slope angle, curvature, relief, slope orientation (aspect), and water table depth. The preliminary model developed prior to the field visit was underestimating slope vulnerability and was not effectively capturing all historical failure types. WSB determined the solution was to re-design the historical failures model. The model was refined and led to an improved vulnerability output. Model results were ranked into four proposed risk-management categories: action recommended, further evaluation, monitoring, and no action recommended. The risk estimation process was considered preliminary; further consideration of risk tolerance and consequence definitions should be conducted. Preliminary risk results indicated that 499 management areas and 1.4% of the total area was categorized as action recommended under the proposed risk matrix. The results of this study were intended to be the first step of actions required in minimizing slope failure effects including expensive mitigation and maintenance repairs and threats to public safety.

Phase 3 Slope Vulnerability Assessments is a continuation of Phases 1 and 2 previously conducted by WSB and MnDOT to determine the risk of slope failure along state highways. This phase includes 27 counties located in MnDOT districts 1; 2; 3; and 4. The three main components of the model are 1) identify past slope failures; 2) model the causative factors of past slope failures and how they vary locally; and 3) model the risk of new slope failures. Vulnerability factors; failure types; and model results reflect the geomorphology of this region. Vulnerability factors for the new study area include slope angle; terrain curvature; and water table depth. Field verification validates the model's capability of identifying risk in regions with different geology; geomorphology; and hydrology including deep-seated slides. Model results were ranked into four proposed risk management categories: action recommended; further evaluation; monitoring; and no action recommended. The risk estimation process for this phase is considered preliminary; further consideration of risk tolerance and consequence definitions should be conducted. Preliminary risk results indicate that 370 management areas; and 3% of the total area falls into the action recommended category under the proposed risk matrix. The results of this study are intended to be the first step of actions required in minimizing the effects of slope failure including expensive mitigation and maintenance repairs and threats to public safety.

This application was developed to expand a low-cost asset inventory program called Geographic Roadway Inventory Tool (GRIT) to include roadway forecasting based on the American Association of State Highway and Transportation Officials (AASHTO) 93 model with inventory; pavement condition; and traffic forecasting data. Existing input data from GRIT such as pavement thickness; roadway structural information; and construction planning information will be spatially combined with current MnDOT Pathway pavement condition and traffic data to automatically forecast the future condition and age of roadways using the AASHTO 93 model. This forecasting model will allow roadway managers to use this information with comprehensive geographic information system (GIS) web maps to prioritize roadways in their construction schedules or multi-year plans.

This project; Phase 2 Slope Vulnerability Assessments; is a continuation of the Phase 1 project previously conducted by WSB and MnDOT to determine the risk of slope failure along state highways. The Phase 2 study area includes 32 counties located in districts 4; 6; 7; 8; and Metro. This reports outlines the methods and results of this project including the new landforms; geomorphic processes; and causative factors influencing slope failures in this part of the state. The three main components of the model are the same 1) identify past slope failures; 2) model the causative factors of past slope failures and how they vary locally; and 3) model the risk of new slope failures. Vulnerability factors; failure types; and model results reflect the geomorphology of this region. Vulnerability factors for the new study area include slope; terrain curvature; incision potential; and local relief. Field verification results validate the model's capability of identifying risk in regions with different geology; geomorphology; and hydrology including ravines and bluffs located along the Minnesota River Valley. Model results are ranked into four proposed risk management categories: action recommended; further evaluation; monitoring; and no action recommended. Risk incorporates the model outputs with consequence to infrastructure including distance to roads and populated areas. The risk estimation process for this phase is considered preliminary; further consideration of risk tolerance and consequence definitions should be conducted. Preliminary risk results indicate that 858 management areas; or 0.7% of the total area; would be recommended for mitigation under the proposed risk matrix. Next steps include field visits and a site-specific mitigation program. The results of this study are intended as the first step of actions required in minimizing the effects of slope failure including expensive mitigation and maintenance repairs and threats to public safety.

Transportation infrastructure intersects challenging terrain that can negatively impact integrity. Minnesota's climate; geomorphology; and steep terrain along rivers increase the incidence of slope failures such as rockfalls and landslides. WSB was contracted by MnDOT to determine the risk of slope failure along state highways in districts 6; 7; and the Metro. This report outlines the methods and results of the MnDOT Slope Vulnerability project including a new Geographic Information Systems (GIS) model that can be implemented anywhere in the state. The model contains three main parts: 1.) identify past slope failures; 2.) model the causative factors of past slope failures and how they vary locally; 3.) model the risk of new slope failures. Vulnerability factors including slope; terrain curvature; proximity to rivers; and proximity to bedrock outcrops were statistically tested to determine their capabilities in causing slope failure. Field verification results validate the model's capability of identifying risk in regions with different geology; geomorphology; and hydrology. Model results were ranked into four risk management categories: action recommended; further evaluation; monitoring; and no action recommended. Risk incorporates the model outputs with consequence to infrastructure including distance to roads and populated areas. Results indicate that 826 of the 35;000 "management areas" delineated and ranked in GIS are recommended for mitigation. Next steps include field visits and a site-specific mitigation program. The results of this study are intended as the first step of actions required in minimizing the effects of slope failure including expensive mitigation and maintenance repairs and threats to public safety.

The Minnesota Department of Transportation (MnDOT) operates 137 truck stations and 18 headquarter sites. Replacement of 80 of these truck stations will be required within the next 20 years based on expected life cycles. There is a need to optimize the locations of truck stations on a statewide basis. Truck stations serve several functions for MnDOT maintenance operations. They exist to maintain the state's trunk highway system and provide a base of operation for many personnel and maintenance vehicles. Alternative locations were developed for each truck station and optimized individually. Truck station locations were optimized using a GIS optimization model to determine operational outputs. The outputs of each optimization model were used in a cost-analysis model to determine the 50-year life-cycle savings of each alternative. The cost analysis included factors for the number of events per year; number of cycles per event; wages; over time versus straight time; and vehicle operating costs. Implementation optimization was conducted to determine which alternatives should be implemented and in what order. The implementation modeling was an iterative process where each optimal location replaced the existing location and became the baseline scenario to which the next iteration was compared. Results indicated that 123 truck stations should be rebuilt on site; 24 should be relocated; and 2 should be combined. The total expected cost savings from implementing the optimal alternatives over a 50-year period is $23;362;000. The implementation plan recommends the order for truck station replacement for each district based on age; condition; and implementation priority.