Wildland fires are one of the most dangerous natural risks, causing significant economic
damage and loss of lives worldwide. Every year, millions of hectares are lost, and experts …

Water body classification from high-resolution optical remote sensing (RS) images, aiming at
classifying whether each pixel of the image is water or not, has become a hot issue in the …

Satellite imagery offers extensive information that can be used for a variety of societal
applications, from the number of buildings in a metropolis to the land cover types of a …

Deep learning networks have recently demonstrated yielded impressive progress for multi-
exposure image fusion. However, how to restore realistic texture details while correcting …

Remote sensing (RS) images enable high-resolution information collection from complex
ground objects and are increasingly utilized in the earth observation research. Recently, RS …

Water features (eg, water quantity and water quality) are one of the most important
environmental factors essential to improving climate-change resilience. Remote sensing …

Smart UAVs have been developed under the consumer Internet of Drone Things (CIoDTs)
framework to improve the quality of service (QoS) for several commercial and consumer …

Weakly supervised semantic segmentation (WSSS) has gained significant popularity as it
relies only on weak labels such as image level annotations rather than the pixel level …

Artificial intelligence (AI) and machine learning (ML) are novel techniques to detect hidden
patterns in environmental data. Despite their capabilities, these novel technologies have not …

The unmanned aerial vehicle (UAV)-captured panoptic remote sensing images have great
potential to promote robotics-inspired intelligent solutions for land cover map**, disaster …