Quantitative assessment of problematic forest structure in Eastern Washington and Oregon

Forests of Eastern Washington and Oregon (EOW) are structurally heterogeneous, exhibiting complex patterns in three-dimensions at multiple spatial scales. This heterogeneity, coupled with the susceptibility of these forests to fire, disease, and insect attack, creates problems for managers, policymakers, scientists, and residents. In order to address these problems, quantitative assessments of forest structure in Eastern Washington and Oregon are needed that are accurate and wide in their spatial extent. In this dissertation, I have (1) developed a new method for assessing forest density using airborne LiDAR (Light Detection and Ranging), (2) identified the limitations of airborne LiDAR in assessing understory structure, (3) identified landscape metrics derived from airborne LiDAR that provide good assessment of three-dimensional pattern, (4) developed a method for delineating forest stands at an appropriate scale using airborne LiDAR, (5) used landscape metrics to quantify three-dimensional patterns in those stands, (6) presented two methods for reducing the complex patterns in those stands into interpretable classes, (7) developed two new metrics of understory density and patchiness using terrestrial LiDAR, (8) demonstrated the metrics' utility in complex forests, (9) and identified how assessments of forest structure and density, and geospatial analysis, can be used to drive a techno-economic analysis of bioenergy potential. The results from this dissertation provide quantitative methods of assessing three-dimensional structure pattern in EOW that can be used to address the real problem of problematic forest structure.