This paper introduces an innovative road network extraction algorithm using synthetic aperture radar (SAR) imagery for improving the accuracy of road extraction. The state-of-the-art approaches, such as fraction extraction and road network optimization, failed to obtain continuous road segments in separate successions, since the optimization could not change the parts ignored by the fraction ex...

Based on the research progress in related fields and the distribution characteristics of road networks in valley cities, the complex network model of a city road network is established to study its connectivity reliability. Taking Lanzhou as the example, several parameters of the complex network abstracted from the road network are calculated and the practical meanings of them are described, re...

What does it mean to say that a physical network (such as a road network, electricity grid, or telephone network) is optimal? Different optimality criteria for different networks have been developed and studied. In the case of road networks connecting cities, an intuitive notion of an “optimal” network is one that provides the shortest routes between any two cities in the network while requirin...

Road detection in remote sensing imagery is an important field of interest in remote scene analysis. In complex process of road network extraction one has to cope with many separate problems. One is presence of objects which are similar (or identical) in colour to road surface. Another is absence of some road fragments in the image. In this paper we propose a new approach with use of morphologi...

In this paper we report on research on road extraction at TUM (Technische Universität München). We propose a scheme for road extraction in rural areas that integrates three different modules with specific strengths. The first module employs local grouping and uses multiple scales and context to reliably extract most parts of the road network. In order to connect these parts, the second module e...

In this paper we report on research on road extraction at TUM (Technische Universität München). We propose a scheme for road extraction in rural areas that integrates three different modules with specific strengths. The first module employs local grouping and uses multiple scales and context to reliably extract most parts of the road network. In order to connect these parts, the second module e...

The popularity of location-based services and the need to perform real-time processing on them has led to an interest in queries on road networks, such as finding shortest paths and finding nearest neighbors. The challenge here is that the efficient execution of operations usually involves the computation of distance along a spatial network instead of “as the crow flies,” which is not simple. T...

aid uses, including fire stations, according to critical activities that are responsible, in comparison to other city services, are more important. identify areas where are located outside of the fire stations covered services can help urban planners to site selection of this important land use. the purpose of this paper is detection the areas that are beyond the services coverage of the fire s...

We present a novel method for automatically synthesizing road networks that are perceptually similar to given example road networks. Our algorithm can grow a new road network from an initial node or expand an existing network. For an unfinished node in the network, we search a set of candidate nodes in the example road networks that have similar node topology, and then find a best one by neighb...

We present a fast method for road network extraction in satellite images. It can be seen as a transposition of the segmentation scheme “watershed transform + region adjacency graph + Markov random fields” to the extraction of curvilinear objects. Many road extractors which are composed of two stages can be found in the literature. The first one acts like a filter that can decide from a local an...