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

The integration of Artificial Intelligence (AI) and Satellite Remote Sensing in Land Cover
Change Detection (LCCD) has gained increasing significance in scientific discovery and …

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

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 …

Labeled samples are important in achieving land cover change detection (LCCD) tasks via
deep learning techniques with remote sensing images. However, labeling samples for …

Deep learning-based coastline detection algorithms have begun to outshine traditional
statistical methods in recent years. However, they are usually trained only as single-purpose …

Change detection based on heterogeneous images, such as optical images and synthetic
aperture radar images, is a challenging problem because of their huge appearance …

Change detection (CD) of remote sensing (RS) images is one of the important problems in
earth observation, which has been extensively studied in recent years. However, with the …

This work presents a robust graph map** approach for the unsupervised heterogeneous
change detection problem in remote sensing imagery. To address the challenge that …

Building change detection (BCD) for very-high-spatial-resolution (VHR) remote sensing
images is very important and challenging in the field of remote sensing, as the building is …