Remote sensing technologies and machine learning (ML) algorithms play an increasingly
important role in accurate detection and monitoring of oil spill slicks, assisting scientists in …

Floods are among the most severe and impacting natural disasters. Their occurrence rate
and intensity have been significantly increasing worldwide in the last years due to climate …

As artificial intelligence (AI) techniques are becoming more popular in landslide modeling, it
is important to understand how decisions are made. Fairness, and transparency becomes …

Deep learning in remote sensing has received considerable international hype, but it is
mostly limited to the evaluation of optical data. Although deep learning has been introduced …

It is well-known that the convolutional neural network (CNN) is an effective method for
synthetic aperture radar (SAR) target classification. In the convolutional layer of CNN …

Building change detection in high-resolution satellite images plays a special role in urban
management and development. Recently, methods for building change detection have been …

Polarization can provide information largely uncorrelated with the spectrum and intensity.
Therefore, polarimetric imaging (PI) techniques have significant advantages in many fields …

The diversity of change detection (CD) methods and the limitations in generalizing these
techniques using different types of remote sensing datasets over various study areas have …

Abstract Synthetic Aperture Radar (SAR) has emerged as a pivotal technology in
geosciences, offering unparalleled insights into Earth's surface. Indeed, its ability to provide …

Artificial intelligence research in the area of computer vision teaches machines to
comprehend and interpret visual data. Machines can properly recognize and classify items …