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Use Case: Transport & Logistics

Linear Infrastructure Modelling for Optimal Route Planning

Reduce costs, optimise routes and minimise environmental impact. Find out how our Linear Infrastructure Modelling solution can help Transport companies reach optimal efficiency.

Identify the most efficient and cost-effective routes

Linear infrastructure modelling helps companies to identify the most efficient and cost-effective routes for new infrastructure projects, minimising construction costs and travel distances. Least-cost path analysis allows for the generation of routes that balanced various criteria, including cost, environmental impact, and engineering feasibility.

Detailed risk assessments for effective results

Geological and terrain data analysis can help the identify potential risks like landslides, flooding, and terrain instability. Detailed risk assessments allow for proactive mitigation measures, improving safety and reducing potential disruptions.

Data integration and management

We integrate diverse datasets (elevation, terrain, existing infrastructure, environmental constraints) into a unified model. This centralised data management improved data consistency and accessibility. Through our predictive analysis of potential hazards you can to take preventative measures that reduce down time.

Implement best practices that exceed regulatory expectations.

Incorporating environmental datasets (protected areas, water bodies, sensitive habitats) allowed for the avoidance of environmentally sensitive areas. This proactive approach can help organisation comply with environmental regulations and reduce its ecological footprint.

Putting Linear Infrastructure Modelling into context

Here we breakdown how this solution can be of huge benefit to transport, logistics and supply chain organisations, providing you with an example of how we deliver our Linear Infrastructure Modelling solution.

Client: A large, multinational Transport Company specialising in freight and logistics, seeking to optimise route planning for new and existing transportation corridors.

Context: This Transport Company operates across diverse geographical regions and faces challenges in efficiently planning and managing its infrastructure. They require a robust solution to model potential routes for new transportation projects (roads, rail, pipelines) and evaluate existing routes for efficiency and risk mitigation, considering various environmental and logistical factors.

 

The Challenge

Address key operational and strategic priorities

  • Identify optimal routes for new infrastructure projects, minimising construction costs and environmental impact.
  • Evaluate existing routes for potential risks (e.g., landslides, flooding, terrain instability) and identify areas for improvement.
  • Integrate diverse datasets (elevation, terrain, existing infrastructure, environmental constraints) into a unified model for informed decision-making.
  • Generate detailed, spatially accurate route proposals and risk assessments for presentation to stakeholders.

Our Solution

Tracsis Geo Intelligence provides a comprehensive linear infrastructure modelling solution, enabling Transport Companies to effectively plan and manage its transportation corridors.

We approach this challenge in four stages: 

Linear Infrastructure Modelling

1. Data Collection, Collation, and Criteria Evaluation:

Our team of specialists gather and integrate diverse datasets, including:

    • High-resolution elevation data (DEM) to assess terrain and slope.
    • Geological maps and soil data to evaluate terrain stability and potential hazards.
    • Existing infrastructure data (roads, railways, pipelines) to identify potential conflicts and synergies.
    • Environmental datasets (protected areas, water bodies, sensitive habitats) to minimise environmental impact.
    • Cost data (construction, land acquisition) to optimise route economics.   
    • Client provided origin and destination coordinates of proposed projects.

Our team then work closely with the Transport Company to define critical criteria and weightings for each dataset, reflecting the company’s priorities and operational requirements.

2. Data Reclassification and Business Rule Definition:

We define the “business rules” of the model, establishing the relative importance of each dataset in determining optimal routes. Data then gets reclassified and standardised to ensure consistency across the model. For example, slope values are categorised into risk levels, and proximity to protected areas was assigned a penalty score.

3. Multi-Criteria Analysis Implementation:

All relevant datasets are converted to a common raster format. Weighted overlay analysis are carried out, combining the reclassified datasets based on the defined business rules. This analysis generates a cost surface, representing the overall suitability of each location for infrastructure development, considering all relevant factors.

*The use of GIS decision support systems are paramount in this process.

4. Route Selection and Evaluation:

  • Using the cost surface, we implement a least-cost path algorithm to generate optimal route proposals between specified origin and destination points.
  • Multiple route alternatives are generated and evaluated, considering factors like length, cost, environmental impact, and risk. 
  • Detailed reports and maps are generated, providing Transport Companies with comprehensive information on each route proposal, including:
    • Route alignment and length.
    • Estimated construction costs.
    • Potential environmental impacts.
    • Risk assessments for identified hazards.
    • ESRI file geo-database output.

The solution outcome

  • Transport Companies gain access to a powerful tool for optimising route planning and infrastructure management.
  • Significant cost savings are achieved through the identification of efficient and cost-effective routes.
  • Environmental impact are minimized through the integration of environmental constraints into the model.
  • Risk assessments enable proactive mitigation of potential hazards, improving safety and operational efficiency.
  • Improved stakeholder communication through clear and concise geospatial reports.