Satellite Image Database Creation for Road Quality Measurement of National Highways of Bangladesh

In this work, we proposed a monitoring system for the road quality measurement of Bangladesh using satellite imagery. The proposed system will enable a much larger scale and much lower costs than are achievable with existing methods. For this task, no dataset was available in this domain. We have collected data and created our dataset. We used two sets of data: a set of road quality management IRI (International Roughness Index) values as our ground truth data, and the corresponding set of satellite images to create our dataset. These data are used to build a model that can automatically measure road quality with the help of different kinds of feature extraction techniques and deep learning architectures. We tried to train the proposed model using two deep learning architectures: Vgg16 and ResNet50. We got the best result in ResNet50 with modification in a 70:30 split ratio where validation accuracy is 70%.