Recipient Organization
UNIVERSITY OF WASHINGTON
4333 BROOKLYN AVE NE
SEATTLE,WA 98195
Performing Department
Bioresource Science and Engineering
Non Technical Summary
Airborne laser scanning (LIDAR) data can be used to characterize vegetation structure across large land areas. Data layers derived directly from the LIDAR point cloud provide information describing vegetation size, density, and spatial distribution. When combined with appropriate field measurements, descriptive statistics computed from the point cloud can be used to model and predict forest inventory variables and structure (Strunk 2008, Means et al. 2000). Processing and analyzing the point cloud data for large acquisitions requires expertise, specialized software, and high-performance computers. The LIDAR-derived products can be used to design a set of sample locations and measurement protocols that represent the full range of variability in conditions. In addition, several LIDAR-derived products provide direct descriptions of vegetation characteristics such as overall height, canopy cover and the presence or absence of mid-story canopy layers.Specific objectives described in this agreement will be accomplished through collaboration between the USDA Forest Service Alaska Region (R10), Pacific Northwest Research Station (PNW) and the University of Washington's School of Environmental and Forest Sciences (SEFS).
Animal Health Component
85%
Research Effort Categories
Basic
5%
Applied
85%
Developmental
10%
Goals / Objectives
The primary objectives of the proposed project are to provide initial quality inspections of LIDAR deliverables, process LIDAR point and raster data to produce a set of GIS-ready data layers, design a field sample covering the full range of vegetation conditions present in the acquisition area, and summarize the field data to produce a data set for model development. The project area includes a significant portion of Prince of Wales (POW) Island in Alaska covering 2055 square miles or about 1.3 million acres. The area includes land managed by the USDA Forest Service (USFS), Alaska Department of Natural Resources, and Sealaska Corporation. The LIDAR-optimized sampling protocol, built on earlier work by Hawbaker et al. (2009) and prior SEFS-PNW projects, has been successfully used to develop sample locations (plot locations) that sample the full range of variability in forest types for projects in Alaska, Washington, Oregon, and South Carolina.
Project Methods
The UW School of Environmental and Forest Sciences Cooperator shall: 1. Collaborate with the Forest Service (PNW) in the preparation and execution of a mutually acceptable implementation plan. 2. Process the LIDAR data acquired for Prince of Wales Island, AK to produce descriptive metrics for the point cloud, canopy height models, and topographic metrics. 3. Develop GIS data layers describing forest structure and variability in structure over the entire acquisition area. 4. Create a set of field plot locations and related documentation using the LIDAR-derived information. 5. Summarize field measurements to produce plot-level summaries of inventory variables and format the results into format suitable for analysis and modeling that is consistent with previous PNW-SEFS projects. 6. Co-author publication of the project results as appropriate with respective participation by individual scientists on their particular subjects.The Forest Service Cooperator shall: 1. Collaborate with SEFS in the preparation and execution of a mutually acceptable implementation plan. 2. Evaluate the overall quality and completeness of the LIDAR deliverables. 3. Assist with the processing of the LIDAR data. 4. Provide guidance regarding the specific area to be sampled by field plots, LIDAR metrics used to stratify the area of interest, and criteria used to develop the sample design. 5. Review project results for quality and completeness. 6. Co-author publication(s) of the project results as appropriate with respective participation by individual scientists on their particular subjects.