We review both widely used methods and new techniques proposed in the recent literature.
The basic concepts, categories, open issues, and challenges related to CD in HS images …

For hyperspectral image (HSI) change detection (CD), multiscale features are usually used
to construct the detection models. However, the existing studies only consider the multiscale …

Accurate information about the location, extent, and type of Land Cover (LC) is essential for
various applications. The only recent available country-wide LC map of Iran was generated …

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 …

Hyperspectral image change detection (HSI-CD) is a challenging task that focuses on
identifying the differences between multitemporal HSIs. The recent advancement of …

Recently, the research area of hyperspectral (HS) image change detection (CD) is popular
with convolutional neural networks (CNNs) based methods. However, conventional CNNs …

Multitemporal hyperspectral images (HSIs) have wide applications in change detection (CD)
of different land covers for their rich spectral features and image details. Traditional …

Change detection (CD) with hyperspectral images (HSIs) can be effectively performed using
deep learning networks (DLNs) by taking advantage of HSIs for their abundant spectral and …

Hyperspectral change detection (CD) can be effectively performed using deep-learning
networks. Although these approaches require qualified training samples, it is difficult to …

Hyperspectral image (HSI) change detection aims to identify the differences in multitemporal
HSIs. Recently, a graph convolutional network (GCN) has attracted increasing attention in …