Recent advances in airborne and spaceborne hyperspectral imaging technology have
provided end users with rich spectral, spatial, and temporal information. They have made a …

The recent success of attention mechanism-driven deep models, like vision transformer (ViT)
as one of the most representatives, has intrigued a wave of advanced research to explore …

With the development of remote sensing techniques, the fusion of multimodal data,
particularly hyperspectral-Light Detection And Ranging (HS-LiDAR) and hyperspectral-SAR …

In recent years, airborne and spaceborne hyperspectral imaging systems have advanced in
terms of spectral and spatial resolution, which makes the data sets they produce a valuable …

Recently, embedding and metric-based few-shot learning (FSL) has been introduced into
hyperspectral image classification (HSIC) and achieved impressive progress. To further …

Edge-preserving features (EPFs) obtained by the application of edge-preserving filters to
hyperspectral images (HSIs) have been found very effective in characterizing significant …

This paper proposes a simple and effective spatial-spectral (SESS) method for mapping
large-scale coastal wetlands using China ZY1-02D satellite hyperspectral data. First, the …

This paper proposes a novel framework for the fusion of hyperspectral and light detection
and ranging-derived rasterized data using extinction profiles (EPs) and deep learning. In …

Classification techniques for hyperspectral images based on random forest (RF) ensembles
and extended multiextinction profiles (EMEPs) are proposed as a means of improving …

The classification accuracy of remote sensing data can be increased by integrating ancillary
data provided by multisource acquisition of the same scene. We propose to merge the …