Parks, S.A.; Dillon, G.K.; Miller, C. A New Metric for Quantifying Burn Severity: The Relativized Burn Ratio. Remote Sens. 2014, 6, 1827-1844. https://doi.org/10.3390/rs6031827
Widely used model for #fire-severity prediction for forest wildfires in Canada and USA.
Paper using fire risk prediction model.
Neural operators are guaranteed to be discretization invariant, meaning that they can work on any discretization of inputs and converge to a limit upon mesh refinement. Once neural operators are trained, they can be evaluated at any resolution without the need for re-training. In contrast, the performance of standard neural networks can degrade when data resolution during deployment changes from model training.
Look this up: anyone familiar with this? sounds complicated but very promising for domains with a large range of resolutions (medical-imaging, wildfire-management)