LiDAR Scan Density and Spatial Resolution Effects on Vegetation Fuel Type Mapping

Abstract

This article presents the performance of a vegetation fuel type (FT) classification based on conditional rules according to the Prometheus system, including an analysis of the effect of cell size and scan density on mapping vertical structural types, exemplified as FT, using exclusively LiDAR data. Since the Prometheus system does not specify any criterion for the minimum extension where those methodologies can be applied, we searched for the optimal classification cell size by gridding the study area at 20 and 40 m cell sizes. We also included a study of the effects of varying the scan density from 2 to 0.5 pulses·m-2. To validate the classification method, we used a stratified random sampling without replacement of 15 cells per FT and made an independent visual assessment of FTs. The best results in terms of precision were obtained for the combination of 0.5 pulses·m-2 and 20 m-resolution dataset, with an overall accuracy of 84.13%. It was also showed that an increase in scan density would not improve the global accuracy of the classification, but it would be desirable for a better detection of the shrub stratum.