STIX records X-rays from Solar activity from 4 to 150 keV with 32 detectors, each divided into 12 pixels. Background is obtained using the BKG detector and is known to essentially correspond to the background radioactive sources onboard STIX. This study aims to construct an analytical model of the STIX background based on available measures. The model will allow predicting the background at any time interval of the mission. We analysed 256 background files recorded by STIX from January 2022 to July 2023, and we assume that onboard calibration sources ( ^133 Ba) dominate the background. We fitted with an exponential function corresponding to the half-life of ^133 Ba to the background in each of the 384 pixels and each of the science energy bins. Interpolated background values were validated against additional files for consistency. These values were then integrated into image reconstruction algorithms to assess variability in source parameters across background approaches. A determined background was also tested in OSPEX to evaluate its impact on spectral fitting. The analysis shows that the STIX background is non-uniform, with pixel-to-pixel variations affecting moiré patterns in weak flares. Our approximation matches background files collected during quiet Sun periods, but it can also differ from them during high activity or perihelion, where onboard files include additional signals. In such cases, our radioactive-source-based background offers a more reliable basis for imaging and spectral analysis than file-based background and enables a higher degree of automation in the analysis. Background analysis from Jan 2022 to Jul 2023 shows that STIX background is usually dominated by ^133 Ba over the full energy spectrum. Interpolated background methods improve accuracy during high solar activity or close Sun approaches, where standard methods falter. This enhances X-ray image quality and enables reconstruction from fewer counts, supporting more precise analyses, especially of microflares.
The DFSAR (Dual-Frequency Synthetic Aperture Radar) onboard the Chandrayaan-2 spacecraft, launched on July 22, 2019, represents a significant advance in radar-based exploration of solid celestial bodies. Chandrayaan-2 is equipped with an array of sophisticated sensors, including the DFSAR, which operates in both the L-band and the S-band in Fully Polarimetric (FP) and compact polarimetric (CP) modes. In this study, we utilize L-band Synthetic Aperture Radar (SAR) data to analyze the lunar regolith. The L-band has superior penetration capabilities, allowing for more effective retrieval of subsurface parameters compared to previous S-band SAR missions. By using L-band in Fully Polarimetric (FP) mode, we can effectively characterize the lunar surface. This technology enables detailed polarimetric analysis of the lunar surface, particularly in the challenging Permanently Shadowed Regions (PSRs) at the lunar poles. These PSRs serve as cold traps for water molecules and are ideal locations for exploring water ice. DFSAR, SLI data is imported, and pre-processing is carried out after generating the scattering matrix. Multilooking is performed with a factor of 38. Refined Lee filter [5x5] window size is applied after coherency matrix generation to remove the speckle in the data, and also multiple decomposition techniques are employed, including the H/A/α̅ decomposition (based on eigenvalue-eigenvector analysis) and the Yamaguchi four-component decomposition model (based on double-bounce, surface, and volume scattering), which effectively characterize the variations in surface roughness, material composition, and topography of the crater’s inner and outer walls. This study focuses on the polar and non-polar regions (Hermite-A, Peary, Gardner, and Korolev X crater regions), utilizing DFSAR data to conduct a comprehensive polarimetric analysis aimed at identifying the potential presence of water ice deposits. The results reveal the dominance of volume scattering within the walls of the crater, which is verified across all decomposition methods. Circular Polarization Ratio (CPR) analysis further demonstrates a pronounced difference between the interior and exterior regions, with the interior values suggesting rough textures and a higher probability of water ice presence. This aligns with prior studies that associate elevated CPR values and volume scattering with ice deposits in the lunar Polar Regions. To validate the SAR-based analysis, high-resolution lunar surface images captured by the Navigation camera onboard Pragyan Rover at the Chandrayaan-3 landing site were examined. The change in surface roughness before and after landing was reflected in scattering powers, confirming changes in the lunar terrain.
Anthropogenic alterations to the nocturnal environment pose a fundamental effect to the optical viability of ground-based astronomical observatories. This study presents a comprehensive spatiotemporal assessment of light pollution dynamics affecting Türkiye’s premier research facilities, the Eastern Anatolia Observatory (DAG) in Erzurum and the TÜBİTAK National Observatory (TUG) in Antalya within the Türkiye National Observatories, situated in contrasting highland and coastal topographies. To bridge the scale gap between the remote sensing and ground-based site testing, we developed a traditional regression and a hybrid machine learning regression Kriging framework. These approaches synthesized high-resolution, high-quality radiance data from the Suomi-NPP VIIRS with extensive in-situ sky quality meter measurements. A rigorous methodological comparison revealed that traditional geostatistical methods (Ordinary/Universal Kriging) suffered from smoothing effects and overfitting in complex terrains. Furthermore, while advanced algorithms like support vector regression achieved high statistical scores, they produced physically implausible extrapolations in data-sparse regions. In contrast, the proposed random forest regression Kriging model proved superior, achieving robust validation accuracy (R2 = 0.74 and 0.80) while maintaining strict physical consistency with natural sky brightness limits. Temporal analyses in the study demonstrated that the high-altitude Erzurum plateau exhibited a distinct seasonal cycle with the snowglow effect, where surface snow cover increased human-induced skyglow by > 1.5 times. In contrast, the Antalya coast exhibited a monotonous deterioration independent of seasonality, triggered by rapid tourism-oriented urbanization.
Modern video cameras use either global or rolling shutter to create individual video frames. In case of global shutter, the whole frames are exposed and read out at the same time. In case of rolling shutter, the exposure and readout proceed sequentially line by line. Such cameras are now commonly used for meteor observations. It is then necessary to perform a correction for this type of image reading in order to correctly and accurately determine the velocity of recorded meteors. We provide here the correct procedure, which replaces the previous assumption P=1/F with a measured value of P. The correction must include the value of the rolling period of the sensor, which is generally not provided in camera specifications. We discuss five methods of determining the rolling period experimentally. The most accurate method uses the New EXposure Timing Analyser (NEXTA) of [1]. We list rolling periods measured for several cameras.
