Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …

Hyperspectral imaging has been emerged as a new generation of technology for earth
observation and space exploration since the beginning of this millennium and widely used …

Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-
modality-dominated remote sensing (RS) applications, especially with an emphasis on …

The fusion of multispectral (MS) and hyperspectral (HS) images has recently been put in the
spotlight. The combination of high spatial resolution MS images with HS data showing a …

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

Industrial emissions play a major role in the global methane budget. The Permian basin is
thought to be responsible for almost half of the methane emissions from all US oil-and gas …

Abstract Models of radiative transfer (RT) are important tools for remote sensing of
vegetation, allowing for forward simulations of remotely sensed data as well as inverse …

Hyperspectral image super-resolution, which refers to reconstructing the high-resolution
hyperspectral image from the input low-resolution observation, aims to improve the spatial …

Sporadic ocean color events with characteristic spectra, in particular algal blooms, call for
quick delivery of high-resolution remote sensing data for further analysis. Motivated by this …

Soil salinization has hampered the achievement of sustainable development goals (SDGs)
in many countries worldwide. Several countries have recently launched hyperspectral …