Machine learning can be used to automatically inventory roads and identify their quality and surrounding areas by analyzing imagery without human labeling or inspection. This process involves using machine learning models to detect roads from aerial or satellite imagery and extract attributes about each road like its class, surface type, and neighboring land use. The goal is to develop new methodologies for more efficient and accurate road mapping using machine learning.

1. Machine
Learning for
Road Inventory
Dr Mark Iliffe
Geospatial Lead – N-LAB
University of Nottingham

3. Factors of
Change

4. Factors For Research
●Machine Learning for Road Inventory
● Identification of Roads, Quality, surround areas
● Origin / Destination Matrices – Mobility of People
● New methodologies and practices of mapping

6. The
Opportunity

15. The
Process

16. Thank you. Asanteni.