Predicting road quality using high resolution satellite imagery: A transfer learning approach.

ABSTRACT: Recognizing the importance of road infrastructure to promote human health and economic development, actors around the globe are regularly investing in both new roads and road improvements. However, in many contexts there is a sparsity-or complete lack-of accurate information regarding existing road infrastructure, challenging the effective identification of where investments should be made. Previous literature has focused on overcoming this gap through the use of satellite imagery to detect and map roads. In this piece, we extend this literature by leveraging satellite imagery to estimate road quality and concomitant information about travel speed. We adopt a transfer learning approach in which a convolutional neural network architecture is first trained on data collected in the United Sta

SUBMITTER: Brewer E 

PROVIDER: S-EPMC8270213 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature