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SOLVING INDUSTRY CHALLENGES
Road & Rail
Linear Infrastructure
Growing complexity and pace
The operators of linear infrastructure manage a vast amount of land, which has a high ecological value due to its contribution to carbon capture, the regeneration of natural environment and the preservation of biodiversity. This is also a major financial challenge: the maintenance of natural assets over large areas of land is a cost factor that can be optimized by choosing the right strategy, while guaranteeing control of operational risks.
Green PRAXIS helps make the right decisions
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Our natural asset management platform automatically analyzes thousands of kilometers of infrastructure sites to identify areas of high biodiversity concern, locate invasive exotic species or vegetation hazardous to infrastructure, qualify habitat permeability, etc.
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Our modelling capabilities enable us to define uses adapted to ultra-local conditions and evaluate opportunities in terms of their ecological value (maintenance of biodiversity corridors, carbon sinks, etc.) or financial value (deployment of photovoltaic infrastructure, biomass, etc.).
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We enable our clients to modelize possible value-creative options (scenarios), draw up strategies and compare them using 4 scores: costs, biodiversity, carbon sequestration, risks, etc.
ILLUSTRATIVE USE CASE
Road & Rail
The Challenge
A highway operator typically manages 8 to 10 hectares of land per kilometer of highway. This considerable natural asset can be dedicated to various uses including carbon sequestration, biodiversity preservation, energy production or other utilitarian function. The objective is to automatically assign a function to every piece of land and optimally improve costs, risks, biodiversity and carbon sequestration.
The METHOD
Utilize GreenPraxis platform to automatically gather information on multiple dimensions such as satellite images, regulatory data, and observation databases, creating a comprehensive "data cube" that serves as a reference for subsequent actions. Analyze the collected data to classify risks and identify opportunities. Measure the proximity to specific environmental zones such as Natura 2000 and ZNIEFF, identify invasive species, and automatically calculate biodiversity indicators, providing insights for potential additions to the development plan. Candidate areas are automatically defined through a set of characteristics which match the conditions needed to support a given purpose of transformation. Specific objectives include carbon sequestration, cost reduction, risk mitigation, or biodiversity promotion. Subsequently, several scenarios are created based on the data and identified zones that align with the defined objectives.
The RESULTS
The creation of land use scenarios that combine different types of (provided) indicators of cost, biodiversity, carbon and risk. The aim here is to validate a list of nature-based solutions applicable to each area, with details of implementation costs, maintenance and long-term benefits. In the end, clients benefit from a micro and macro vision, and the ability to draw up a strategy and adapt it over time.