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Passive microwave sensors use a radiative transfer model (RTM) to retrieve soil moisture (SM) using brightness temperatures () at low microwave frequencies. Vegetation optical depth (VOD) is a key input to the RTM. Retrieval algorithms can analytically invert the RTM using dual-polarized measurements to retrieve the VOD and SM concurrently. Algorithms in this regard typically use the types of models, which consist of two third-order polynomial equations and, thus, can have multiple solutions. Through this work, we find that uncertainty occurs due to the structural indeterminacy that is inherent in all types of models in passive microwave SM retrieval algorithms. In the process, a new analytical solution for concurrent VOD and SM retrieval is presented, along with two widely used existing analytical solutions. All three solutions are applied to a fixed framework of RTM to retrieve VOD and SM on a global scale, using X-band Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) data. Results indicate that, with structural uncertainty, there ensues a noticeable impact on the VOD and SM retrievals. In an era where the sensitivity of retrieval algorithms is still being researched, we believe the structural indeterminacy of RTM identified here would contribute to uncertainty in the soil moisture retrievals.
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http://dx.doi.org/10.3390/s20041225 | DOI Listing |
Laser Photon Rev
December 2024
Énergie, Matériaux et Télécommunications Institut National de la Recherche Scientifique Montréal H5A 1K6 Canada.
The rapid advancements in machine learning have exacerbated the interconnect bottleneck inherent in binary logic-based computing architectures. An interesting approach to tackle this problem involves increasing the information density per interconnect, i.e.
View Article and Find Full Text PDFSci Justice
November 2024
Law School, University of Strathclyde, Glasgow G4 0LT, Scotland, UK. Electronic address:
Human rights investigations demand reliable data sources to substantiate alleged events, and satellite imagery offers diverse options crucial for evidential support. This paper delineates how Earth Observation (EO) imagery can be tailored to align with the requirements outlined by the Office of the United Nations High Commissioner for Human Rights (OHCHR) indicators, facilitating stakeholders in optimising their studies with applicable technological applications. To streamline EO technology, the paper categorises it into six primary payloads capable of observing such events: multispectral visible.
View Article and Find Full Text PDFAdv Mater
November 2024
Department of Microwave Engineering, School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, 150001, China.
Characterization of electromagnetic wave polarization states is critical in various applications of materials, biomedical, and imaging. The emergence of metasurfaces opens up the possibility of implementing highly integrated full-Stokes imagers. Despite rapid development, prevailing schemes on metasurface-based full-Stokes imagers require interleaved or cascaded designs, inevitably resulting in performance deterioration, bulky size, and complicating the imaging procedure due to misalignment.
View Article and Find Full Text PDFSci Rep
October 2024
ISPA, UM 1391, INREA/Bordeaux SCience Agro, Villenave, d'Ornon, 33140, France.
Sci Rep
October 2024
Faculty of Environment, University of Tehran, Tehran, Iran.
Soil moisture (SM) is a critical variable influencing various environmental processes, but traditional microwave sensors often lack the spatial resolution needed for local-scale studies. This study develops a novel stacking ensemble learning framework to enhance the spatial resolution of satellite-derived SM data to 1 km in the Urmia basin, a region facing significant water scarcity. We integrated in-situ SM measurements (obtained using time-domain reflectometry [TDR]), Soil Moisture Active Passive (SMAP) and Advanced Microwave Scanning Radiometer 2 (AMSR2) SM products, Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and vegetation indices, precipitation records, and topography data.
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