Marek's paper wins ASPRS award!
Wednesday, May 14, 2014 at 8:55AM Marek's paper "Predicting surface fuel models and fuel metrics using lidar and CIR imagery in a dense, mountainous forest" has been awarded the 2014 ERDAS Award for Best Scientific Paper in Remote Sensing by ASPRS. They bestowed the award for an outstanding paper of scientific merit that advances the knowledge of remote sensing technology.
In the paper we compared the ability of several classification and regression algorithms to predict forest stand structure metrics and standard surface fuel models. We used clustering, regression trees, and support vector machine algorithms to analyze high density (average 9 pulses/m2), discrete return, smallfootprint lidar data, along with multispectral imagery.
Jakubowski, M. K., Q. Guo, B. Collins, S. Stephens, and M. Kelly. 2013. Predicting surface fuel models and fuel metrics using lidar and CIR imagery in a dense, mountainous forest. Photogrammetric Engineering and Remote Sensing 79(1):37-49
For more on the paper, see the abstract here.