The main goal of this paper is to detect roads from aerial imagery recorded by drones. To achieve this, we propose a modification of SegNet, a deep fully convolutional neural network for image segmentation. In order to train this neural network, we have put together a database containing videos of roads from the point of view of a small commercial drone. Additionally, we have developed an image...

This publication shows the results of measurements of the noise level emitted by the motor trucks on the internal roads of the steelworks. The distribution of the metallurgical products with the use of trucks is, next to the rail transport, one of the main logistic forms of products delivery to the customer. The research was conducted on one of the busiest internal roads of metallurgical enterp...

The paper studies an optimal decision problem for several groups of drivers on a network of roads. Drivers have different origins and destinations, and different costs, related to their departure and arrival time. On each road the flow is governed by a conservation law, while intersections are modeled using buffers of limited capacity, so that queues can spill backward along roads leading to a ...

From 2006 to 2008, the Monash University Accident Research Centre, in conjunction with the Office of Road Safety and Department of Main Roads in Western Australia, attempted to gain the support of a Local Government Area in W.A. to implement a demonstration trial of lower speed limits, based on a new Harm Reduction approach. Attempts to gain the support made over these three years included enli...

India’s rural roads program, Pradhan Mantri Gram Sadak Yojana, aims to draw villagers into the mainstream by improving not only their terms of trade, but also their educational attainments and health. Treating each all-weather feeder road as an isolated element within the larger network, and using shadow prices to value the main components of costs and benefits, this paper demonstrates that fur...

The automatic interpretation of aerial and satellite imagery is one of the main research tasks in photogrammetry and related disciplines. The primary goal is the automatic extraction of visible, spatial, topographic objects from imagery. The extracted objects are one possible input for updating or creating geographic data bases. In order to simplify the task, automatic image interpretation was ...

In this paper we discuss trends and perspectives of automated data collection for Geographic Information Systems (GIS). We focus on aerial imagery and employ road extraction for the examples. The paper is split into three parts: In the first we present major findings for the (fully) automatic extraction of buildings, roads, and other topographic objects in the form of a model and a strategy. In...

We calculated the usable distance of the main roads in the coastal area of Iwate prefecture following the 2011 Tohoku Earthquake. Calculations were based on a vehicle tracking map built from G-BOOK telematics data using QGIS, an open source geographic information system. The main findings are as follows. (1) The change in the accumulative usable road distance ratio during the research period di...

Roads are significant objects of an infrastructure and the extraction of roads from aerial and satellite images are important for different applications such as automated map generation and change detection. Roads are also important to detect other structures such as buildings and urban areas. In this paper, the road extraction approach is based on Active Contour Models for 1-meter resolution g...