Statewide Mapping of Aboveground Biomass by Integrating Airborne Lidar Data and National Forestry Inventory Plots

Abstract:

The freely available airborne lidar data at the sub-national level in the United States provide unprecedented opportunities for mapping large-area yet accurate information about vegetation structure, biomass, and carbon. However, the challenge of processing massive lidar data and extracting useful information is huge. This study is to conduct a statewide mapping study of aboveground biomass (AGB) by integrating airborne lidar data and FIA (Forest Inventory and Analysis) plot data for the whole state of Minnesota. We will share our experience and lessons in issues including 1) automatic generation of Digital Terrain Model from point cloud, 2) classification of vegetation returns, 3) calculation of AGB from FIA plots using different allometric models, 4) statistical modeling of AGB by integrating with FIA plots, and 5) assessing the uncertainty of mapped AGB.