Deep learning detection methods use in ship detection remains a challenge, owing to the
small scale of the objects and interference from complex sea surfaces. In addition, existing …

To overcome the limitation of poor processing times for long-distance off-road path planning,
an improved A-Star algorithm based on terrain data is proposed in this study. The improved …

This paper presents a practical framework for the integration of unmanned aerial vehicle (UAV)
based photogrammetry and terrestrial laser scanning (TLS) with application to open-pit …

Highway crack segmentation is a critical task for highway infrastructure monitoring and
maintenance. While imagery from unmanned aerial vehicles (UAVs) is applied to the task of …

To address the disadvantage of traditional methods providing only two-dimensional (2D)
damage change of the collapsed buildings, this paper presents an approach for the detection of …

The accurate and timely identification of the degree of building damage is critical for disaster
emergency response and loss assessment. Although many methods have been proposed, …

Fire is an important ecosystem process and has played a complex role in terrestrial ecosystems
and the atmosphere environment. Sometimes, wildfires are highly destructive natural …

In this paper, we present a hybrid shadow-analysis approach that integrates the model- and
property-based methods for detecting collapsed buildings after an earthquake using high-…

Sea ice is one of the typical causes of marine disasters. Sea ice image classification is an
important component of sea ice detection. Optical data contain rich spectral information, but …

Attitude jitter is a common phenomenon in the application of high resolution satellites, which
may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to …