OMB Individually Reported
Neural network accelerated radiative transfer modeling
Low riskExact public inventory row
Description
Neural network accelerated radiative transfer modeling is intended to enhance efforts in the Earth Science domain.
Detailed example
fast radiative transfer modeling
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Specifically, JPL constructed a flexible radiative transfer model (RTM) that combines physics-based models and artificial neural networks with the intent of providing fast radiative transfer modeling for global imaging spectroscopy missions, as well as large-scale airborne campaigns (ABoVE, Western Diversity Time Series, FIREX-AQ, etc.)
Controls / human review
ATO: Not reported; PIA: Not published