Change detection (CD) is essential in remote sensing (RS) for natural resource monitoring,
territorial planning, and disaster assessment. With the abundance of data collected by …

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 …

Remote sensing image change captioning (RSICC) aims to articulate the changes in objects
of interest within bitemporal remote sensing images using natural language. Given the …

Change detection, a prominent research area in remote sensing, is pivotal in observing and
analyzing surface transformations. Despite significant advancements achieved through …

The existing Remote Sensing Image Change Captioning (RSICC) methods perform well in
simple scenes but exhibit poorer performance in complex scenes. This limitation is primarily …

Artificial intelligence (AI) has significantly advanced Earth sciences, yet its full potential in to
comprehensively modeling Earth's complex dynamics remains unrealized. Geoscience …

Recent advancements in Remote Sensing (RS) for Change Detection (CD) and Change
Captioning (CC) have seen substantial success by adopting deep learning techniques …

Remote sensing change detection (RSCD) recognizes pixel-level change regions between
images, while remote sensing change captioning (RSCC) describes the nature and …

Recently, while significant progress has been made in remote sensing image change
captioning, existing methods fail to filter out areas unrelated to actual changes, making …

Generative foundation models have advanced large-scale text-driven natural image
generation, becoming a prominent research trend across various vertical domains …