Deep learning (DL) algorithms have seen a massive rise in popularity for remote-sensing
image analysis over the past few years. In this study, the major DL concepts pertinent to …

Technological growth is changing our everyday living, making it smarter and more
convenient day by day; Smart society 5.0, Healthcare 5.0, Agriculture 5.0 are only a few …

In order to approximate the underlying process of temporal data, time series prediction has
been a hot research topic for decades. Develo** predictive models plays an important role …

This article brings together the advances of multisource and multitemporal data fusion
approaches with respect to the various research communities and provides a thorough and …

Abstract Sentinel-2 and Sentinel-3 are two newly launched satellites for global monitoring.
The Sentinel-2 Multispectral Imager (MSI) and Sentinel-3 Ocean and Land Colour …

Landsat and Sentinel-2 sensors together provide the most widely accessible medium-to-
high spatial resolution multispectral data for a wide range of applications, such as vegetation …

Time-series remote sensing data offer a rich source of information that can be used in a wide
range of applications, from monitoring changes in land cover to surveillance of crops …

Over the last few years, Deep learning (DL) approaches have been shown to outperform
state-of-the-art machine learning (ML) techniques in many applications such as vegetation …

Deep Learning, and Deep Neural Networks in particular, have established themselves as
the new norm in signal and data processing, achieving state-of-the-art performance in …

In recent years, the rapid development of Earth observation technology has produced an
increasing growth in remote sensing big data, posing serious challenges for effective and …