Predicting Surface Fuel Models and Fuel Metrics Using Lidar and CIR Imagery in a Dense , Mountainous Forest

@inproceedings{Jakubowksi2013PredictingSF,
  title={Predicting Surface Fuel Models and Fuel Metrics Using Lidar and CIR Imagery in a Dense , Mountainous Forest},
  author={Marek K. Jakubowksi and Qinghua Guo and Brandon M. Collins and Scott L. Stephens and Maggi Kelly},
  year={2013}
}
0099-1112/13/7901–37/$3.00/0 © 2012 American Society for Photogrammetry and Remote Sensing Abstract We compared the ability of several classification and regression algorithms to predict forest stand structure metrics and standard surface fuel models. Our study area spans a dense, topographically complex Sierra Nevada mixed-conifer forest. We used… CONTINUE READING