2 citations · 3 across the 5 of their papers we have counts for
5 papers
Transfer Learning for Dead Fuel Moisture Prediction Using Time-Warping Recurrent Neural Networks
Jonathon Hirschi, Jan Mandel, Adam Kochanski
This paper proposes a time-warping transfer learning method, a technique for temporally rescaling the learned dynamics of a recurrent neural network (RNN) with a Long Short-Term Me…
Optimal Planning and Machine Learning for Responsive Tracking and Enhanced Forecasting of Wildfires using a Spacecraft Constellation
Sreeja Roy-Singh, Vinay Ravindra, Richard Levinson +8
We propose a novel concept of operations using optimal planning methods and machine learning (ML) to collect spaceborne data that is unprecedented for monitoring wildfires, process…
Generative Algorithms for Wildfire Progression Reconstruction from Multi-Modal Satellite Active Fire Measurements and Terrain Height
Bryan Shaddy, Brianna Binder, Agnimitra Dasgupta +8
Increasing wildfire occurrence has spurred growing interest in wildfire spread prediction. However, even the most complex wildfire models diverge from observed progression during m…
Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts
Bryan Shaddy, Deep Ray, Angel Farguell +7
Increases in wildfire activity and the resulting impacts have prompted the development of high-resolution wildfire behavior models for forecasting fire spread. Recent progress in u…
Coupled Atmosphere-Fire Simulations of Fireflux: Impacts of Model Resolution on Model Performance
Adam K. Kochanski, S. K. Krueger, M. A. Jenkins +2
The ability to forecast grass fire spread could be of a great importance for agencies making decisions about prescribed burns. However, the usefulness of the models used for fire-s…