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This paper investigates the performance of a full-duplex (FD) relaying-enabled satellite sensor network under residual loop interference, where the satellite uplink and the downlink transmissions simultaneously occur over the same frequency band. Specifically, the closed-form expressions for the outage probability and ergodic capacity of the FD relaying satellite sensor network are derived by considering residual loop interference, channel statistical property, propagation loss, geometric satellite antenna pattern, and terminal elevation angle. Simulation results show the achieved performance gains of a full-duplex relaying satellite sensor network over traditional half-duplex relaying, and highlight the impact of key system parameters on the performance of the considered FD relaying satellite sensor network.
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http://dx.doi.org/10.3390/s19245453 | DOI Listing |
Environ Monit Assess
September 2025
Department of Forestry Engineering, Federal University of Lavras (UFLA), Lavras, Minas Gerais State, Brazil.
In general, species on our planet are adapted to phenological patterns of vegetation, which are strongly influenced by various climatic and environmental factors that, when altered, can threaten biodiversity. Recent studies have utilized the spatiotemporal variability of vegetation to understand its dynamics, directly affecting biodiversity. Therefore, this research aimed to generate indices of temporal variability considering vegetation phenology and indices of spatial variability of vegetation to subsequently identify priority areas for biodiversity conservation in the Cerrado and Caatinga regions in Minas Gerais State, Brazil.
View Article and Find Full Text PDFSci Total Environ
September 2025
Department of Geological Sciences and Geological Engineering, Queen's University, 99 University Ave, K7L 3N6 Kingston, Ontario, Canada.
Hyperspectral data have been overshadowed by multispectral data for studying algal blooms for decades. However, newer hyperspectral missions, including the recent Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Ocean Color Instrument (OCI), are opening the doors to accessible hyperspectral data, at spatial and temporal resolutions comparable to ocean color and multispectral missions. Simulation studies can help to understand the potential of these hyperspectral sensors prior to launch and without extensive field data collection.
View Article and Find Full Text PDFTree Physiol
September 2025
Department of Plant Sciences, University of California, Davis, CA, USA.
Pigment dynamics in temperate evergreen forests remain poorly characterized, despite their year-round photosynthetic activity and importance for carbon cycling. Developing rapid, nondestructive methods to estimate pigment composition enables high-throughput assessment of plant acclimation states. In this study, we investigate the seasonality of eight chlorophyll and carotenoid pigments and hyperspectral reflectance data collected at both the needle (400-2400 nm) and canopy (420-850 nm) scales in Pinus palustris (longleaf pine) at the Ordway Swisher Biological Station in north-central Florida, USA.
View Article and Find Full Text PDFAust Vet J
September 2025
Faculty of Agricultural and Environmental Sciences, University of Salamanca, Salamanca, Spain.
Geotechnologies, such as Global Navigation Satellite Systems (GNSS) and remote sensing, are essential for documenting topographic features and analyzing land use. Among them, the GPS (Global Position System)-based sensors have proven highly effective in monitoring livestock, providing high-resolution data on movement patterns. This study tracked two Hispano-Breton mares in the Spanish Pyrenees during summer 2023 using GPS collars.
View Article and Find Full Text PDFJ Air Waste Manag Assoc
September 2025
Department of Civil, Environmental & Construction Engineering, University of Central Florida, Orlando, Florida, USA.
The Integrated Mass Enhancement (IME) method is among the most popular remote sensing method for estimating methane emissions from point sources, and it has gained significant popularity in recent years. In this study, we evaluated how key environmental and observational factors, namely wind speed, instrument noise, terrain topography, and the source of 10-meter wind speed (U) data, influence emission estimates derived from the IME method. Although landfills are typically area sources, we used a simplified point-source emission setup as a controlled case to systematically explore the sensitivity of IME to each of these factors.
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