Thesis (M.S.)--Oregon State University, 2008. / Printout. Includes bibliographical references. Also available on the World Wide Web.

Thesis (M.S.)--Oregon State University, 2006. / Printout. Includes bibliographical references. Also available on the World Wide Web.

Thesis (M. For. Sc.)--University of Canterbury, 2006. / Typescript (photocopy). Includes bibliographical references (leaves 80-82). Also available via the World Wide Web.

Thesis (M.S.)--Oregon State University, 1999. / Typescript (photocopy). Includes bibliographical references (leaves 34-37). Also available on the World Wide Web.

Thesis (Ph. D.)--Oregon State University, 1998. / Typescript (photocopy). Includes bibliographical references (leaves 99-107). Also available on the World Wide Web.

Thesis (M.S.) in Forest Resources--University of Maine, 2009. / Includes vita. Includes bibliographical references (leaves 133-144).

There is growing interest in airborne lidar for forest carbon accounting and precision forestry purposes. Airborne lidar systems offer a cost-effective, versatile, operationally flexible and robust sampling tool for forest managers. The objective of this study was to develop and test lidar canopy surface enhancement and segmentation processes for estimating dominant above-ground biomass (DAB) in a harvested eucalypt forest on the Central Coast of New South Wales (Australia). The Crown Infill, Trim and Smooth (CITS) process, incorporating a series of filters, algorithms, and selective multi-stage smoothing, was used to enhance lidar canopy surfaces prior to segmentation. Canopy segmentation was achieved using a vertical crown template approach termed the Spatially and Morphologically Isolated Crest (SMIC) process. SMIC delineates dominant tree crowns by detecting elevated crown crests within a 3D lidar canopy surface. Consolidated crown units constitute the basic sampling, analysis and reporting units for wall-to-wall forest inventory. The performance, sensitivity and limitations of these procedures were evaluated using a combination of simulated forest models and actual lidar forest data. Automated crown polygons were used as a sampling template to extract dominant tree height values which were converted to DAB estimates via height-to-biomass relationships derived from field survey and on-site destructive sampling. Results were compared with field based tree height and biomass estimates. Compared against a manually derived crown map from a 2ha field plot, canopy segmentation results revealed a producer???s accuracy of 76% and overall accuracy of 67%. Results indicated a trend toward greater crown splitting (fragmentation) as trees increase in age, height, stem diameter and crown size. Extracted dominant tree height values were highly correlated with ground survey height estimates (r2 0.95 for precision survey and r2 0.69 for standard survey). There was also no significant difference between SMIC and manual crown height estimates. SMIC units overestimated ground-based DAB by 5%; this increased to 36% with the inclusion of segmentation errors. However, SMIC estimation of total plot above-ground biomass (AGB) was within 9% of the ground-based estimate. Results are encouraging considering the mixed-species, multi-aged composition of the forest, and the combined effects of SMIC segmentation and lidar height errors.

The United States Forest Service (USFS) Forest Inventory and Analysis (FIA) program provides a diverse selection of data used to assess the status of the nation’s forested areas using sample locations dispersed throughout the country. Airborne, and more recently, terrestrial lidar (light detection and ranging) systems are capable of producing accurate measurements of individual tree dimensions and also possess the ability to characterize three-dimensional vertical forest structure. This study investigates the potential of airborne and terrestrial scanning lidar systems for modeling forest volume and aboveground biomass on FIA subplots in the Malheur National Forest, eastern Oregon. A methodology for the creation of five airborne lidar metric sets (four point cloud-based and one individual tree based) and four terrestrial lidar metric sets (three height-based and one distance-based) is presented. Metrics were compared to estimates of subplot aboveground biomass and gross volume derived from FIA data using national and regional allometric equations respectively. Simple linear regression models from the airborne lidar data accounted for 15 percent of the variability in subplot biomass and 14 percent of the variability in subplot volume, while multiple linear regression models increased these amounts to 29 percent and 25 percent, respectively. When subplot estimates of biophysical parameters were scaled to the plot-level and compared with plot-level lidar metrics, simple linear regression models were able to account for 60 percent of the variability in biomass and 71 percent of the variation in volume. Terrestrial lidar metrics produced moderate results with simple linear regression models accounting for 41 percent of the variability in biomass and 46 percent of the variability in volume, with multiple linear regression models accounting for 71 percent and 84 percent, respectively. Results show that: (1) larger plot sizes help to mitigate errors and produce better models; and (2) a combination of height-based and distance-based terrestrial lidar metrics has the potential to estimate biomass and volume on FIA subplots.

The search for alternative energy sources has increased interests in forest biomass. During the last few years, the sever infestation of the Mountain Pine Beetle (MPB) within the Interior BC forests has led to huge volumes of dead wood that exceed the capacity of the lumber industry. One way to make the most value of the surplus wood is to use it as the feedstock for bioenergy. The forest biomass can be supplied through conventional (roadside residuals), full-tree chipping, or satellite yard systems. This thesis presents the development of a simulation model of supply logistics of forest biomass and its application to a case of supplying MPB-killed biomass from Quesnel Timber Supply Area (one of the most infested areas in the Interior BC) to a potential 300 MW power plant adjacent to the city of Quesnel. The model has the ability of providing estimates of quantity, delivery cost, and moisture content of biomass which are critical in feasibility study of any bioenergy project. The results obtained from simulation model showed a delivery cost of C$45 per oven dry tonne of wood chips to the power plant. The results also revealed that the feedstock recovered from roadside residues in one year meets about 30% of the annual demand of the power plant. Potential increase in the Allowable Annual Cut (AAC) for Quesnel TSA increases the quantity of biomass supplied from roadside residuals. However, as long as the biomass is supplied only through conventional harvesting, increasing the AAC even by 40% does not provide enough feedstock to meet the annual demand of the plant. Using the simulation modeling, this research has the benefit of considering the logistics of forest biomass supply as an integrated and interacting system as well as providing different critical parameters over time. The model also has the potential of considering dynamic and random behavior of the logistics system of supplying forest biomass. The model can be modified and applied to similar cases of conventional forest biomass supply. It also can be extended to other harvesting systems including satellite yard and whole-tree chipping.

The use of forest biomass (by thermal combustion to electricity processes), has been recognized by the Government of Nova Scotia (NS) as one option which could help meet short- and long term energy generation goals (aggressively set at 25% and 40% by 2015 and 2020 respectively). However, while approximately 77% of NS land area is forest covered, there is significant concern about the sustainability and stewardship of this natural resource. This controversy inspired a deeper investigation into the attitudes towards forest biomass held by one particular stakeholder group—small-woodland owners—and also the rural community members living in the same regions. 51% of the forested area in NS is owned by small-private woodland owners and as such, they will play an integral role in the future of NS’s forest economy and sustainability. How these stakeholders feel about the forests, the alternative uses for forest biomass and its use in large scale energy production could have a significant impact on the future of forest biomass use - particularly for energy - in NS. 489 small-woodland owners responded to mail-out surveys and 14 rural community members participated in three focus groups. Three major findings emerged. Firstly, it was found that the acceptability of using forest products varied depending on multiple factors— the source of biomass, harvesting methods, and [predicted] end-use. Secondly, forest sustainability and keeping resources local were the two most important concerns amongst respondents. Finally, respondents felt that better collaboration with other stakeholders and objective education around the issues would be the best strategies to overcoming these concerns.