The use of remotely sensed LiDAR and multispectral imagery for modeling eastern redcedar biomass within North Eastern Kansas

Abstract

Due in large part to changes in land management practices, eastern redcedar (Juniperus virginiana L.), a native Kansas conifer, is rapidly invading onto valuable rangelands. The suppression of fire and increase of intensive grazing, combined with the rapid growth rate, high reproductive output, and dispersal ability of the species have allowed it to dramatically expand beyond its original range. Based on its abundance and invasive nature there is a growing interest in harvesting this species for use as a biofuel. For economic planning purposes, density and biomass quantities for the trees are needed. Three methods are explored for mapping eastern redcedar and quantifying its biomass in Riley County, Kansas. First a comparison of plot-regression versus individual tree based techniques is conducted to determine the optimal approach for characterizing redcedar tree canopy using LiDAR (Light Detection and Ranging). Second a hybrid approach is utilized to characterize redcedar canopy biomass using LiDAR and high-resolution multispectral imagery. Finally, to explore alternative methods of characterizing the three-dimensional structure of redcedar canopy a comparison of “Structure from Motion” photogrammetric techniques and LiDAR is conducted. These methods showed promising results and proved to be useful in the forestry, range management, and bioenergy industries for better understanding the potential of invasive redcedar as a biofuel resource.