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Future astrophysics missions will seek extraterrestrial life via transmission and direct imaging observations. To assess habitability and biosignatures, we need robust retrieval tools to analyze observed spectra, and infer surface and…
Remote sensing hyperspectral and more generally spectral instruments are common tools to decipher surface features in Earth and Planetary science. While linear mixture is the most common approximation for compounds detection (mineral,…
The rapid accumulation of Earth observation data presents a formidable challenge for the processing capabilities of traditional remote sensing desktop software, particularly when it comes to analyzing expansive geographical areas and…
Low-latency delivery of satellite imagery is essential for time-critical applications such as disaster response, intelligence, and infrastructure monitoring. However, traditional pipelines rely on downlinking all captured images before…
Super-resolution is a classical problem in image processing, with numerous applications to remote sensing image enhancement. Here, we address the super-resolution of irregularly-sampled remote sensing images. Using an optimal interpolation…
This work has been accepted by IEEE TGRS for publication. The majority of optical observations acquired via spaceborne earth imagery are affected by clouds. While there is numerous prior work on reconstructing cloud-covered information,…
Understanding the structure of Earth's polar ice sheets is important for modeling how global warming will impact polar ice and, in turn, the Earth's climate. Ground-penetrating radar is able to collect observations of the internal structure…
Spatiotemporal fusion aims to improve both the spatial and temporal resolution of remote sensing images, thus facilitating time-series analysis at a fine spatial scale. However, there are several important issues that limit the application…
Because of the internal malfunction of satellite sensors and poor atmospheric conditions such as thick cloud, the acquired remote sensing data often suffer from missing information, i.e., the data usability is greatly reduced. In this…
We explore the potential of three-dimensional data assimilation for assimilating sparsely-distributed 2-metre temperature observations across the coupled atmosphere-land interface into the soil moisture. Using idealised twin experiments…
Atmospheric correction is a fundamental task in remote sensing because observations are taken either of the atmosphere or looking through the atmosphere. Atmospheric correction errors can significantly alter the spectral signature of the…
Tungsten is a leading candidate material for plasma-facing components in future fusion reactors. Extensive studies have been performed to better understand its behavior under irradiation. Recent experiments of Rutherford backscattering…
Inversion codes allow reconstructing a model atmosphere from observations. With the inclusion of optically thick lines that form in the solar chromosphere, such modelling is computationally very expensive because a non-LTE evaluation of the…
The intrinsic capability of the Human Vision System (HVS) to perceive depth of field and failure of Instrument Landing Systems (ILS) stimulates a pilot to perform a vision-based manual landing over an autoland approach. However, harsh…
The occlusion of the sun by clouds is one of the primary sources of uncertainties in solar power generation, and is a factor that affects the wide-spread use of solar power as a primary energy source. Real-time forecasting of cloud movement…
In the near-future, atmospheric characterization of Earth-like planets in the habitable zone will become possible via reflectance spectroscopy with future telescopes such as the proposed LUVOIR and HabEx missions. While previous studies…
Cloud detection is a specialized application of image recognition and object detection using remotely sensed data. The task presents a number of challenges, including analyzing images obtained in visible, infrared and multi-spectral…
Using polarization measurements in remote sensing and optical studies allows retrieving more information. We consider relationship between the reflection coefficients of plane and rough surfaces for linearly polarized waves. Certain…
In recent years, the wide availability of high-resolution radar satellite images has enabled the remote monitoring of wetland surface areas. Machine learning models have achieved state-of-the-art results in segmenting wetlands from…
Remote sensing analysts continuously monitor the amount of pollutants in the atmosphere. They are usually performed via satellite images. However, these images suffer from low temporal and low spatial resolution. Therefore, observations…