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Our areas of expertise include remote sensing, geospatial analysis, GIS, soil science, water quality and demand evaluation, agricultural systems, salinity and nutrient management, ecosystem restoration, statistics, and regulatory policy.
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Possess proficiency in programming languages commonly used in geospatial analysis, such as Python, R, or MATLAB.Demonstrate strong theoretical and practical knowledge of remote sensing principles, image processing techniques, and geospatial analysis methods relevant to carbon monitoring and climate analysis.
$200,000 a yearExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Land IQ, LLC is seeking a Remote Sensing Scientist in its Sacramento, California office with a specialization in data driven analytics and algorithm development with digital images for agricultural and other land use applications (crop classification, yield modeling, land use impacts, land use change, etc.
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Research specialties and realms of collaborative opportunities within the DFM exist at the intersections of fire ecology, wildfire and prescribed fire, landscape ecology, forest operations, forest biometrics, silviculture, climatology and watershed hydrology, forest ecology, and remote sensing.
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AEVEX Aerospace, headquartered in Solana Beach, California, supports the U.S. national security mission and partner nation needs around the world by providing full-spectrum aviation, remote sensing, and analysis solutions.
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Use MATLAB, Python or similar tools to develop signal processing and beamforming algorithms for underwater remote sensing applications, including but not limited to, array signal processing, adaptive methods, ambient noise modeling, acoustic communications, PNT and synthetic aperture methods.
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Remote sensing-based land cover mapping over agricultural areas and crop classification; candidate will be responsible for working with our growing geospatial team comprised of remote sensing/GIS experts and a range of agronomic, environmental, and other land-based science disciplines.
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The successful Remote Sensing Scientist candidate will be responsible for working with our growing geospatial team comprised of remote sensing/GIS experts and a range of agronomic, environmental, and other land-based science disciplines.
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Applicants must have strong analytical, remote sensing and GIS skills and an exceptionally strong understanding of machine learning algorithms. Develop and implement remote sensing and statistical methodologies to perform land use and land cover classification (crop classification.
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Work in a team environment on a wide range of projects, supporting our team of scientists, remote sensing analysts, and GIS analysts. Remote sensing of crop evapotranspiration; and/or.
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Proficiency in using Remote Sensing software and tools, such as, TerraSolid, MicroStation, MetaShape, Photoshop, PLS-CADD, TopoDOT. Minimum 5+ years of experience or Associate degree or equivalent in a related field (e.g., geomatics, surveying, remote sensing.
RemoteExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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About AEVEX Aerospace AEVEX Aerospace, headquartered in Solana Beach, California, supports the U.S. national security mission and partner nation needs around the world by providing full-spectrum aviation, remote sensing, and analysis solutions.
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Note: This job description is a general outline of the key responsibilities and qualifications of a Remote Sensing Calibration Technician. Strong understanding of LiDAR and remote sensing principles and data processing.
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We specialize in high-reliability airborne and space-based remote sensing payloads that offer active and motion imaging and data processing, exploitation, and dissemination. Experience working with a multi-discipline technical teams (mechanical, structural, thermal, power, RF, Antenna, electrical, Systems) through all phases of program (initial concept, proposals, SRR, PDR/CDR, I&T, final sell-off.
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M. Simard, G. DeGrandi, S. Saatchi, P. Mayaux, “Mapping tropical coastal vegetation using JERS-1 and ERS-1 radar data with a decision tree classifier", International Journal of Remote Sensing, V.23, No.7, 2002, pp.
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