Fully supervised road segmentation neural networks from remote sensing images rely on a
large number of densely labeled road samples, limiting their potential in large-scale …

Earth, as humans' habitat, is constantly affected by natural events, such as floods,
earthquakes, thunder, and drought among which earthquakes are considered one of the …

Road information is fundamental not only in the military field but also common daily living.
Automatic road extraction from a remote sensing images can provide references for city …

Rapid disaster assessment is critical for public security and rescue. As a secondary disaster
of large-scale meteorological disasters, power outages cause severe outcomes and thus …

Road information as a type of basic geographic information is very important for services
such as city planning and traffic navigation, as such there is an urgent need for updating …

Road is one of important traffic lifelines that could be damaged after disaster by landslide
rubble, buildings debris, and collapsed branches of trees. Therefore, road damage detection …

This paper focuses on the emergency task planning problem with the following
characteristics: incomplete initial environment information, concurrent execution and …

Road blockage information extraction from a single-phase postdisaster image is difficult
because roads are narrow and easily covered by vegetation. The traditional object-oriented …

When a strong earthquake occurs, roads are the lifelines of rescue. The rapid development
of high-resolution satellite imaging platforms has made the application of remote sensing …

This article presents an effective classification method for earthquake damage mapping from
unmanned aerial vehicles (UAV) photogrammetric point clouds. The classification method …