| Machine learning estimation of fire arrival time from level-2 active fires satellite data A Farguell, J Mandel, J Haley, DV Mallia, A Kochanski, K Hilburn Remote Sensing 13 (11), 2203, 2021 | 18 | 2021 |
| An interactive data-driven HPC system for forecasting weather, wildland fire, and smoke J Mandel, M Vejmelka, A Kochanski, A Farguell, J Haley, D Mallia, ... 2019 IEEE/ACM HPC for Urgent Decision Making (UrgentHPC), 35-44, 2019 | 12 | 2019 |
| Assimilation of fire perimeters and satellite detections by minimization of the residual in a fire spread model A Farguell Caus, J Haley, AK Kochanski, AC Fité, J Mandel Computational Science–ICCS 2018: 18th International Conference, Wuxi, China …, 2018 | 6 | 2018 |
| Retrieving Fire Perimeters and Ignition Points of Large Wildfires from Satellite Observations J Mandel, A Kochanski, EA Ellicott, J Haley, A Farguell, L Hearn, ... AGU Fall Meeting Abstracts 2018, NH23C-0859, 2018 | 2 | 2018 |
| Data likelihood of active fires satellite detection and applications to ignition estimation and data assimilation J Haley, AF Caus, AK Kochanski, S Schranz, J Mandel arXiv preprint arXiv:1808.03318, 2018 | 1 | 2018 |
| Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts B Shaddy, D Ray, A Farguell, V Calaza, J Mandel, J Haley, K Hilburn, ... Artificial Intelligence for the Earth Systems, 2024 | | 2024 |
| Sensitivity of the WRF-SFIRE Model to Changes in Fuel Moisture Content J Haley, KA Hilburn, A Farguell, J Mandel, A Kochanski 35th Conference on Agricultural and Forest Meteorology/14th Fire and Forest …, 2023 | | 2023 |
| Building a fuel moisture model for the coupled fire-atmosphere model WRF-SFIRE from data: From Kalman filters to recurrent neural networks J Mandel, J Hirschi, AK Kochanski, A Farguell, J Haley, DV Mallia, ... arXiv preprint arXiv:2301.05427, 2023 | | 2023 |
| Building a Fuel Moisture Model from Data: From Kalman Filters to Recurrent Neural Networks J Mandel, AK Kochanski, A Farguell, J Haley, B Shaddy, AA Oberai, ... 103rd AMS Annual Meeting, 2023 | | 2023 |
| Interpolating Satellite Active Fire Detections Using Unsupervised Learning Methods and a Shortest Path Algorithm J Haley, J Mandel, KA Hilburn, A Kochanski, A Farguell 103rd AMS Annual Meeting, 2023 | | 2023 |
| A Workflow for Initializing Wildfires in WRF-SFIRE for Real-Time Forecasting KA Hilburn, A Kochanski, A Farguell, J Mandel, J Haley 103rd AMS Annual Meeting, 2023 | | 2023 |
| Deep-Learning Based Estimation of the Initial Atmospheric State for Wildfire Prediction B Shaddy, D Ray, I Asareh, A Farguell, J Haley, KA Hilburn, DVV Mallia, ... 103rd AMS Annual Meeting, 2023 | | 2023 |
| A systematic review and meta-analysis assessing the effectiveness of physical activity behaviour change interventions in adults with spinal cord injury J Haley, D Rhind, V Tolfrey, D Maidment Journal of Exercise, Movement, and Sport (SCAPPS refereed abstracts …, 2022 | | 2022 |
| Assimilation of Satellite Active Fires Data JD Haley University of Colorado at Denver, 2021 | | 2021 |
| Fire arrival time estimation from satellite observations using machine learning A Farguell, J Haley, K Hilburn, A Kochanski, DV Mallia, J Mandel AGU Fall Meeting Abstracts 2020, IN038-06, 2020 | | 2020 |
| Assimilation of satellite fire detections in coupled atmosphere-fire model WRF-SFIRE by machine learning A Farguell, J Mandel, J Haley, K Bergstrom, A Kochanski, KA Hilburn, ... AGU Fall Meeting Abstracts 2019, NG21B-0950, 2019 | | 2019 |
| WRFx: An Online Data-Driven Coupled Atmosphere-Fire Modeling System with Automated Acquisition and Assimilation of Satellite Active Fires Detection and RAWS Fuel Moisture Data J Mandel, A Kochanski, J Haley, A Farguell, M Vejmelka, S Schranz AGU Fall Meeting Abstracts 2018, EP33E-2482, 2018 | | 2018 |
| Coupled fire-atmosphere-smoke forecasting: current capabilities and plans for the future AK Kochanski, J Mandel, M Vejmelka, D Burke, L Hearn, J Haley, ... Advances in Forest Fire Research 2018, 2018 | | 2018 |
| CHALLENGES AND OPPORTUNITIES IN BAYESIAN AND SUPPORT VECTOR MACHINE ESTIMATION OF FIRE ARRIVAL TIME IN A COUPLED ATMOSPHERE-WILDLAND FIRE MODEL JAN MANDEL, A FARGUELL, J HALEY, L HEARN, A KOCHANSKI | | |
