In this work, the use of a calibration satellite (L2-CalSat) flying in formation with a Cosmic Microwave Background (CMB) polarization mission in an orbit located at the second Lagrange point, is proposed. The new generation of CMB telescopes are expected to reach unprecedented levels of sensitivity to allow a very precise measurement of the B-mode of polarization, the curl-like polarization component expected from gravitational waves coming from Starobinski inflationary models. Due to the CMB polarized signal weakness, the instruments must be subjected to very precise calibration processes before and after launching. Celestial sources are often used as external references for calibration after launch, but these sources are not perfectly characterized. As a baseline option, L2-CalSat is based on the CubeSat standard and serves as a perfectly known source of a reference signal to reduce polarization measurements uncertainty. A preliminary design of L2-CalSat is described and, according to the scanning strategy followed by the telescope, the influence of the relative position between the spacecrafts in the calibration process is studied. This new calibration element will have a huge impact on the performance of CMB space missions, providing a significant improvement in the measurements accuracy without requiring new and costly technological developments.
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http://dx.doi.org/10.3390/s21103361 | DOI Listing |
Nat Commun
January 2025
Department of Earth Observation Science, Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Overijssel, The Netherlands.
Accurate global glacier mapping is critical for understanding climate change impacts. Despite its importance, automated glacier mapping at a global scale remains largely unexplored. Here we address this gap and propose Glacier-VisionTransformer-U-Net (GlaViTU), a convolutional-transformer deep learning model, and five strategies for multitemporal global-scale glacier mapping using open satellite imagery.
View Article and Find Full Text PDFJ Gen Intern Med
December 2024
Department of General Medicine, Shirakawa Satellite for Teaching And Research (STAR), Fukushima Medical University, Fukushima, Japan.
Background: Detailed grading of chills is more useful for diagnosing bacteremia than simply classifying the presence or absence of chills. However, its value added to other clinical information has not been evaluated.
Objective: To evaluate the value of adding chills grading to other clinical information compared to simply noting the presence or absence of chills for predicting bacteremia in patients with suspected infection.
Carbon Balance Manag
December 2024
Department of Land, Air and Water Resources, University of California, Davis, CA, 95616, USA.
Background: Understanding the impacts of climate change on forest aboveground biomass is a high priority for land managers. High elevation subalpine forests provide many important ecosystem services, including carbon sequestration, and are vulnerable to climate change, which has altered forest structure and disturbance regimes. Although large, regional studies have advanced aboveground biomass mapping with satellite data, typically using a general approach broadly calibrated or trained with available field data, it is unclear how well these models work in less prevalent and highly heterogeneous forest types such as the subalpine.
View Article and Find Full Text PDFSci Data
December 2024
Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China.
The global gridded crop production dataset at 10 km resolution from 2010 to 2020 (GGCP10) for maize, wheat, rice, and soybean was developed to address limitations of existing datasets characterized by coarse resolution and discontinuous time spans. GGCP10 was generated using a series of adaptively trained data-driven crop production spatial estimation models integrating multiple data sources, including statistical data, gridded production data, agroclimatic indicator data, agronomic indicator data, global land surface satellite products, and ground data. These models were trained based on agroecological zones to accurately estimate crop production in different agricultural regions.
View Article and Find Full Text PDFSci Data
December 2024
School of Spatial Planning and Design, Hangzhou City University, Hangzhou, 310015, China.
Nighttime light (NTL) data is recognized as a reliable proxy for measuring the scope and intensity of human activity, finding wide application in studies such as urbanization monitoring, socioeconomic estimation, and ecological environment assessment. However, the substantial discrepancies and limited temporal coverage of existing NTL datasets have constrained their potential for long-term research applications. To address this, a Nighttime Light U-Net super-resolution network is proposed for the cross-sensor calibration between the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) NTL data and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data.
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