With the fast development of remote sensing platforms and sensors technology, change
detection with heterogeneous remote sensing images (Hete-CD) has become an attractive …

Upon the introduction of machine learning (ML) and its variants, in the form that we know
today, to the landslide community, many studies have been carried out to explore the …

Land cover change detection (LCCD) using remote sensing images (RSIs) plays an
important role in natural disaster evaluation, forest deformation monitoring, and wildfire …

This study presents a new end-to-end change detection network, called difference-
enhancement dense-attention convolutional neural network (DDCNN), that is designed for …

Deep learning-based object detection solutions emerged from computer vision has
captivated full attention in recent years. The growing UAV market trends and interest in …

Land cover change detection (LCCD) with remote sensing images is an important
application of Earth observation data because it provides insights into environmental health …

Land cover change detection (LCCD) using bitemporal remote sensing images is a crucial
task for identifying the change areas on the Earth's surface. However, the utilization of …

Landslides are one of the most critical categories of natural disasters worldwide and induce
severely destructive outcomes to human life and the overall economic system. To reduce its …

Most of the approaches used for Landslide inventory map** (LIM) rely on traditional
feature extraction and unsupervised classification algorithms. However, it is difficult to use …