Guidebook on Machine Learning Techniques for Road Quality Monitoring

This publication highlights opportunities to harness geospatial data and machine learning algorithms to monitor rural roads efficiently to support connectivity. Resilient all-weather roads enable crucial access to services and economic opportunities, yet assessing and monitoring road quality can be costly and time-consuming. This publication explains how smartphones, open-source satellite imagery, and artificial intelligence can be used to augment traditional surveys to improve road data in cost-effective and efficient ways. It draws on a study developed in collaboration with the World Data Lab and the governments of the Philippines and Thailand, supported by the Japan Fund for Prosperous and Resilient Asia and the Pacific.

Pages: 156, Paperback, Asian Development Bank