Monitoring changes in the Earth's surface is crucial for understanding natural processes and
human impacts, necessitating precise and comprehensive interpretation methodologies …

Deep learning has shown remarkable success in remote sensing change detection (CD),
aiming to identify semantic change regions between co-registered satellite image pairs …

Remote sensing images provide a valuable way to observe the Earth's surface and identify
objects from a satellite or airborne perspective. Researchers can gain a more …

Change detection (CD) aims to compare and analyze images of identical geographic areas
but different dates, whereby revealing spatio-temporal change patterns of Earth's surface …

In long-term Earth observation, change detection (CD) is a crucial and intricate task with
applications spanning diverse fields, including land resource planning and natural disaster …

With the rapid advancement of remote sensing technology, bitemporal remote sensing
change detection (CD) techniques have also seen significant progress. However, existing …

As one of the most destructive natural disasters, earthquakes have struck many countries
around the world in recent years, causing serious economic losses. Change detection (CD) …

In recent years, the application of deep learning in remote-sensing (RS) image change
detection (CD) has been deepening, especially in the challenges faced in lightweight model …

Accurate remote sensing change detection (RSCD) tasks rely on comprehensively
processing multiscale information from local details to effectively integrate global …

The remote sensing image change detection methods based on deep learning have made
great progress. However, many convolutional neural network (CNN)-based methods …