[HTML][HTML] Deep learning change detection techniques for optical remote sensing imagery: Status, perspectives and challenges
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 …
but different dates, whereby revealing spatio-temporal change patterns of Earth's surface …
Foundation models for remote sensing and Earth Observation: A survey
Remote Sensing (RS) is a crucial technology for observing, monitoring, and interpreting our
planet, with broad applications across geoscience, economics, humanitarian fields, etc …
planet, with broad applications across geoscience, economics, humanitarian fields, etc …
[HTML][HTML] Advancements in Vision–Language Models for Remote Sensing: Datasets, Capabilities, and Enhancement Techniques
Recently, the remarkable success of ChatGPT has sparked a renewed wave of interest in
artificial intelligence (AI), and the advancements in Vision–Language Models (VLMs) have …
artificial intelligence (AI), and the advancements in Vision–Language Models (VLMs) have …
Aerogen: enhancing remote sensing object detection with diffusion-driven data generation
Remote sensing image object detection (RSIOD) aims to identify and locate specific objects
within satellite or aerial imagery. However, there is a scarcity of labeled data in current …
within satellite or aerial imagery. However, there is a scarcity of labeled data in current …
Open-cd: A comprehensive toolbox for change detection
We present Open-CD, a change detection toolbox that contains a rich set of change
detection methods as well as related components and modules. The toolbox started from a …
detection methods as well as related components and modules. The toolbox started from a …
From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing
Remote sensing has evolved from simple image acquisition to complex systems capable of
integrating and processing visual and textual data. This review examines the development …
integrating and processing visual and textual data. This review examines the development …
Multi-LoRA Fine-Tuned Segment Anything Model for Urban Man-Made Object Extraction
Mapping urban man-made objects, such as roads and buildings, from high-resolution
remote sensing imagery is an essential need for monitoring global urbanization. However …
remote sensing imagery is an essential need for monitoring global urbanization. However …
[HTML][HTML] Flooded Infrastructure Change Detection in Deeply Supervised Networks Based on Multi-Attention-Constrained Multi-Scale Feature Fusion
G Qin, S Wang, F Wang, S Li, Z Wang, J Zhu, M Liu… - Remote Sensing, 2024 - mdpi.com
Flood disasters are frequent, sudden, and have significant chain effects, seriously damaging
infrastructure. Remote sensing images provide a means for timely flood emergency …
infrastructure. Remote sensing images provide a means for timely flood emergency …
WildSAT: Learning Satellite Image Representations from Wildlife Observations
What does the presence of a species reveal about a geographic location? We posit that
habitat, climate, and environmental preferences reflected in species distributions provide a …
habitat, climate, and environmental preferences reflected in species distributions provide a …
[HTML][HTML] Semi-Supervised Change Detection with Data Augmentation and Adaptive Thresholding for High-Resolution Remote Sensing Images
W Zhang, X Shu, S Wu, S Ding - Remote Sensing, 2025 - mdpi.com
Change detection (CD) is an important research direction in the field of remote sensing,
which aims to analyze the changes in the same area over different periods and is widely …
which aims to analyze the changes in the same area over different periods and is widely …