Abstract Prior studies on Remote Sensing Foundation Model (RSFM) reveal immense
potential towards a generic model for Earth Observation. Nevertheless these works primarily …

Spectral–spatial features are important for ground target identification and classification with
high spatial resolution remotely sensed (HSRRS) Imagery. In this article, two novel features …

Change detection (CD) is one of the most important research areas in remote sensing. With
the fast development of imaging techniques, CD using cross-domain remote sensing images …

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

In recent years, few-shot segmentation (FSS) has received widespread attention from
scholars by virtue of its superiority in low-data regimes. Most existing research focuses on …

Deep learning techniques have become popular in land cover change detection (LCCD)
with remote sensing images (RSIs). However, many existing networks mostly concentrate on …

Recently, deep learning (DL) models have become the main focus for the remote sensing
change detection tasks. Numerous publications on supervised and unsupervised DL-based …

Land cover change detection (LCCD) with very high-resolution remote-sensing images
(VHR_RSIs) is important in observing surface change on Earth. However, pseudo-changes …

Learning performance is unsatisfactory when training deep-learning networks without prior-
knowledge guidance. In this letter, a multiscale change detection neural network guided by …

Optical and synthetic aperture radar (SAR) images provide complementary information to
each other. However, the heterogeneity of same-ground objects brings a large difficulty to …