Change detection based on remote sensing (RS) images has a wide range of applications
in many fields. However, many existing approaches for detecting changes in RS images with …

Change detection has been a hotspot in the remote sensing technology for a long time. With
the increasing availability of multi-temporal remote sensing images, numerous change …

Multispectral remote sensing images are the primary source in the land use and land cover
(LULC) monitoring. This is achieved by LULC classification and LULC change detection …

Change detection was one of the earliest and is also one of the most important applications
of remote sensing technology. For multispectral images, an effective solution for the change …

Land cover change detection (LCCD) based on bitemporal remote sensing images has
become a popular topic in the field of remote sensing. Despite numerous methods promoted …

Synthetic aperture radar (SAR) image change detection is a vital yet challenging task in the
field of remote sensing image analysis. Most previous works adopt a self-supervised method …

The fixed weights between the center pixel and neighboring pixels are used in the traditional
Markov random field for change detection, which will easily cause the overuse of spatial …

In this letter, a simple and effective unsupervised approach based on the combined
difference image and k-means clustering is proposed for the synthetic aperture radar (SAR) …

High spatial resolution (HSR) remote sensing images can reflect more subtle changes and
more specific types of land use and land cover (LULC) due to the abundant spatial …

Deep learning-based (DL-based) change detection (CD) using remote sensing (RS) images
has received increasing attention in recent years. However, how to effectively extract and …