28 data "https:" "https:" "https:" "https:" positions at National Aeronautics and Space Administration (NASA)
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carbon-cycle modeling. The project will build a unified modeling framework that uses GEDI LiDAR and Landsat/HLS data to train deep learning models capable of predicting forest structure variables such as
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 12 hours ago
marine planktonic ecosystems. For example, the 2019-2020 Australian wildfires triggered widespread phytoplankton blooms, evidenced in chlorophyll data obtained from satellite remote sensing and in situ
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 12 hours ago
traditional predictive attempts and limits the availability of training data for high-resolution atmospheric and hydrological models. This limitation is compounded by the fact that many atmospheric reanalysis
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distribution information, but did not comprehensively de-bias the results. This work will build from the prior studies, based on the full surveyed populations of those missions, more comprehensive knowledge of
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 18 hours ago
process models often lack the spatially explicit, high-frequency data needed to accurately simulate these rapidly changing dynamics and their cascading effects on vegetation health, carbon cycling, and
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 1 day ago
, identify physically consistent constraints, and recommend data assimilation configurations tailored to specific scientific objectives. All AI modules will be designed within a physics-constrained framework
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retrievals from remote sensing data, particularly for near-infrared space-based observations. Consequently, retrieving greenhouse gases under high aerosol loading conditions remains a significant challenge. To
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 12 hours ago
preprocessing; image remapping, color adjustment and combining; comparison to data from other telescopes; and subsequent investigations of reprocessed images which can focus on one or multiple scientific areas
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. Description: This project aims to develop a next-generation wildfire risk assessment platform that tightly integrates Earth Observation (EO) data, deep learning, and dynamic fire behavior modeling
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 12 hours ago
, modeling, assessment and evaluation must be carefully completed before deployment to space. To this end, it is advantageous to simulate autonomous operations, including assessment of prior spacecraft data