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 …

A wide range of methods for analysis of airborne-and satellite-derived imagery continues to
be proposed and assessed. In this paper, we review remote sensing implementations of …

The joint hyperspectral image (HSI) and light detection and ranging (LiDAR) data
classification aims to interpret ground objects at more detailed and precise level. Although …

Forest vegetation classification and structure measurements are fundamental steps for
planning, monitoring, and evaluating large-scale forest changes including restoration …

The successes of attention-driven deep models like the vision transformer (ViT) have
sparked interest in cross-domain exploration. However, current transformer-based …

With recent advances in sensing, multimodal data is becoming easily available for various
applications, especially in remote sensing (RS), where many data types like multispectral …

Transformer is a powerful tool for capturing long-range dependencies and has shown
impressive performance in hyperspectral image (HSI) classification. However, such power …

In recent years, with the rapid development of unmanned aerial vehicles (UAVs) and
lightweight hyperspectral imaging (HSI) sensors, mini-UAV-borne hyperspectral remote …

With recent advance in Earth Observation techniques, the availability of multi-sensor data
acquired in the same geographical area has been increasing greatly, which makes it …

Multisensor fusion is of great importance in Earth observation related applications. For
instance, hyperspectral images (HSIs) provide wealthy spectral information while light …