A Method for Optimizing Height Threshold When Computing Airborne Laser Scanning Metrics

In airborne laser scanning (ALS), a reference height threshold is employed for computation of height and density metrics, which are used as auxiliary variables for predicting forest attributes. Lacking consensus, practitioners employ different criteria to define a height threshold, which is applied to all the metrics collectively. In this paper, we propose a change of paradigm in ALS metric computation: height thresholds must be optimized for each metric individually, instead of applying a single one for all them. We present an optimization method based on the maximal information coefficient (MIC), which is applied for each metric, one-by-one. Results showed how a bad choice of height thresholds damages the predictive potential of most metrics. While increasing thresholds strengthened height metrics' relationship to volume, it weakened for density metrics, and therefore choosing different thresholds makes sense.