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.