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Currently, numerous remote sensing satellites provide a huge volume of diverse earth observation data. As these data show different features regarding resolution, accuracy, coverage, and spectral imaging ability, fusion techniques are…
We present a new technique for obtaining model fittings to VLBI images of astrophysical jets. The method minimizes a performance function proportional to the sum of the squared difference between the model and observed images. The model…
This paper describes the VIS Processing Function (VIS PF) of the Euclid ground segment pipeline, which processes and calibrates raw data from the VIS camera. We present the algorithms used in each processing element, along with a…
Estimating the landscape and soil freeze-thaw (FT) dynamics in the Northern Hemisphere is crucial for understanding permafrost response to global warming and changes in regional and global carbon budgets. A new framework is presented for…
We investigate the feasibility and scientific potential of the Cosmic Positioning System (CPS), a space mission concept enabling purely geometric distance measurements to sources at hundreds of megaparsecs by directly detecting…
On-board processing of hyperspectral data with machine learning models would enable unprecedented amount of autonomy for a wide range of tasks, for example methane detection or mineral identification. This can enable early warning system…
We present the results of a polarization study based upon relativistic magnetohydrodynamic modelling of jets running into hydrostatic, spherically symmetric cluster atmospheres. For the first time in a numerical simulation, we derive…
Operating satellites in Very Low Earth Orbit (VLEO) benefits the already expanding New Space industry in applications including Earth Observation and beyond. However, long-term operations at such low altitudes require propulsion systems to…
Remote sensing has emerged as a critical tool for large-scale Earth monitoring and land management. In this paper, we introduce AgriPotential, a novel benchmark dataset composed of Sentinel-2 satellite imagery captured over multiple months.…
A new apodized Keplerian (AK) model is proposed for the analysis of precision radial velocity (RV) data to model both planetary and stellar activity (SA) induced RV signals. A symmetrical Gaussian apodization function with unknown width and…
The ESA global astrometry space mission Gaia has been monitoring the position of a billion stars since 2014. The analysis of such a massive dataset is challenging in terms of the data processing involved. In particular, the blind detection…
We present new constraints on parameters of cosmic dawn and the epoch of reionization derived from the EDGES High-Band spectrum ($90-190$ MHz). The parameters are probed by evaluating global $21$ cm signals generated with the recently…
Satellites in core level spectra of photoelectron spectroscopy (PES) can provide crucial information on the electronic structure and chemical bonding in materials, particular in transition metal oxides. This paper explores satellites of the…
Euclid will collect an enormous amount of data during the mission's lifetime, observing billions of galaxies in the extragalactic sky. Along with traditional template-fitting methods, numerous machine learning algorithms have been presented…
Ground Penetrating Radar (GPR) has been widely studied as a tool for extracting soil parameters relevant to agriculture and horticulture. When combined with Machine Learning (ML) methods, air-coupled Stepped Frequency Continuous Wave Ground…
In this paper, we consider downlink low Earth orbit (LEO) satellite communication systems where multiple LEO satellites are uniformly distributed over a sphere at a certain altitude according to a homogeneous binomial point process (BPP).…
We design the proof of concept for high-resolution (HR) real-time (RT), Geosynchronous and Geostationary (Geo) Polarimetric (Pol) using orbital angular momentum (OAM) interferometry - radio detection and ranging (RADAR)…
Improving the representation of precipitation in Earth system models (ESMs) is critical for assessing the impacts of climate change and especially of extreme events like floods and droughts. In existing ESMs, precipitation is not resolved…
Uncertainties and errors in magnetic equilibrium reconstructions are a wide-spread problem in interpreting experimental data measured in the tokamak edge. This study demonstrates errors in EFIT++ reconstructions performed on the COMPASS…
Deforestation detection using satellite images can make an important contribution to forest management. Current approaches can be broadly divided into those that compare two images taken at similar periods of the year and those that monitor…