Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning.

@article{Reid2015SpatiotemporalPO,
  title={Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning.},
  author={Colleen E Reid and Michael Jerrett and M. L. Petersen and Gabriele Pfister and Philip E. Morefield and Ira B. Tager and Sean M. Raffuse and John R Balmes},
  journal={Environmental science & technology},
  year={2015},
  volume={49 6},
  pages={3887-96}
}
Estimating population exposure to particulate matter during wildfires can be difficult because of insufficient monitoring data to capture the spatiotemporal variability of smoke plumes. Chemical transport models (CTMs) and satellite retrievals provide spatiotemporal data that may be useful in predicting PM2.5 during wildfires. We estimated PM2.5 concentrations during the 2008 northern California wildfires using 10-fold cross-validation (CV) to select an optimal prediction model from a set of 11… CONTINUE READING
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