AI tool for tertiary roads

Public sector Colombia Resource Planning

This AI tool helps users identify and map tertiary roads (smaller rural roads) across a country using satellite images. It processes satellite data to automatically detect and georeference these roads, providing an accurate and up-to-date inventory. Users can then visualize road networks, assess accessibility, and make informed decisions for infrastructure planning and development. By automating this process, the AI reduces the time and cost associated with manual road mapping, supporting more efficient resource allocation for future projects. It ultimately helps improve transportation systems, particularly in rural and underserved areas.

SDG 9 Industry, innovation and infrastructure

SDG 11 Sustainable cities and economies

#detect The AI tool analyzes satellite images to detect and identify tertiary roads across Colombia, enabling the classification and georeferencing of these roads. By applying machine learning algorithms, the tool analyzes spatial data, which allows for the identification of road networks that are difficult to detect using traditional methods. This analytical process provides a more accurate and efficient way to assess road infrastructure, offering a solid foundation for further development and prioritization.

#retrieve The tool allows users to retrieve satellite images and the related georeferenced data of identified tertiary roads, available for download in multiple formats. Municipalities and government entities can use this feature to access up-to-date road inventories, enhancing planning efforts and infrastructure investments. This retrieval capability provides stakeholders with the most current data, making it easier to manage and implement effective policies for rural road development.

#visualize The platform allows users to visualize georeferenced maps of the tertiary road network in Colombia, providing a clear representation of road locations in relation to geographical features. This visualization aids stakeholders in understanding the extent and distribution of rural roads, supporting better decision-making and resource allocation. By transforming complex data into easy-to-read maps, the tool enables decision-makers to interpret the information effectively and prioritize infrastructure projects.