Remote sensing (RS) techniques are essential for studying hazardous landslide events
because they capture information and monitor sites at scale. They enable analyzing causes …

Abstract Domain knowledge of social and environmental sciences is generally derived from
less structured small data and/or small models. The integration of deep learning with …

Point cloud has emerged as the most popular three-dimensional (3D) data format in recent
years for several scientific and industrial applications. Point cloud semantic segmentation …

Traditional methods for assessing the stability of rubble mound breakwaters (RMBs) often
rely on 2.5 D data, which may fall short in capturing intricate changes in the armor units …

Change detection is an important task that rapidly identifies modified areas, particularly
when multitemporal data are concerned. In landscapes with complex geometry (eg, urban …

The preservation of underground cultural heritage is a challenging goal. Difficult acquisition
conditions, the need for uniformity of temporal data and the speed at which surfaces change …

We present LiSTA (LiDAR Spatio-Temporal Analysis), a system to detect probabilistic object-
level change over time using multi-mission SLAM. Many applications require such a system …

Due to the widespread applications of change detection technology in urban change
analysis, environmental monitoring, agricultural surveillance, disaster detection, and other …

Mass movements are predominant geomorphic processes on steep sloping areas and are
an important source of sediment delivered to rivers. However, current understanding on the …

Change detection plays a fundamental role in Earth observation for analyzing temporal
iterations over time. However, recent studies have largely neglected the utilization of …