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 …

Water is a kind of vital natural resource, which acts as the lifeblood of the ecosystem and the
energy source for the living and production activities of humans. Regularly mapping the …

Deep learning and remote sensing techniques have significantly advanced water surface
monitoring; however, the need for annotated data remains a challenge. This is particularly …

As one of the most significant components of the ecosystem, waterbody needs to be highly
monitored at different spatial and temporal scales. Nevertheless, waterbody variations in …

The extraction of buildings from remote sensing images is a challenging task. However,
existing methods are insufficiently accurate because of the diverse types of buildings, large …

Automatically extracting water bodies is a significant task in interpreting remote sensing
images (RSIs). Convolutional neural networks (CNNs) have exhibited excellent performance …

Global surface water detection in very-high-resolution (VHR) satellite imagery can directly
serve major applications such as refined flood mapping and water resource assessment …

Synthetic aperture radar (SAR) has the advantage of all-weather observation, but its imaging
principle based on the backscattering of electromagnetic waves makes its information less …

ABSTRACT Water Body Extraction (WBE) is a challenging task in remote sensing, owing to
the complexity of recognizing surface body objects with rich texture, spatial, spectral …

A common task in land-cover classification is water body extraction, wherein each pixel in an
image is labelled as either water or background. Water body detection is integral to the field …