Recipient Organization
UNIVERSITY OF WASHINGTON
4333 BROOKLYN AVE NE
SEATTLE,WA 98195
Performing Department
Sustainable Resource Management
Non Technical Summary
The development of robust MRV (Monitoring, Reporting, and Verification) systems for assessing forest carbon status and dynamics are an important element for ensuring that UN member countries meet their commitments under REDD (Reducing Emissions from Deforestation and Forest Degradation) programs. The US, while not a REDD country, is a party to the UNFCCC and has a need for similar National Greenhouse Gas Inventory (NGHGI) baseline information. This project will support the development and implementation of a carbon monitoring program in different study sites distributed throughout the United States (Alaska, Oregon, Colorado, Minnesota, South Carolina, Maine), as well as technical transfer activities to support MRV programs to enable detection of forest degradation and associated changes in aboveground carbon stocks in the tropics (Brazil, Indonesia).
Animal Health Component
40%
Research Effort Categories
Basic
60%
Applied
40%
Developmental
(N/A)
Goals / Objectives
The purpose of this project is to support the development of a carbon monitoring system. The work will include both design-based andmodel-based approaches to sampling, estimation and inference.
Project Methods
We will:Develop a sampling design to support carbon monitoring using sampled high-density lidar data and field plot data collected over six sites in Oregon, Colorado, South Carolina, Maine, Minnesota, and New Jersey/Pennsylvania. The field plot data will:Consist of 50 1/5th acre circular main plots at each site (300 total plots) acquired as a stratified random sample, where lidar-based structural information (size class, cover) is used to stratify the area covered by the strips into structural classes, and plots distributed so as to cover the full range of lidar structural size and cover classes.These plots will be located in accessible areas (and obviously where we have prior permission from landowners to work).A quality assurance/quality control procedure will likely be used to quantify the accuracy of the field measurements.The primary measurements to be acquired at the plot include:DBH for all large trees (live and dead) on main plot (1/5th acre - 52.7 ft radius)DBH for seedlings and saplings (live and dead) on smaller microplotPosition (dist/azimuth from plot center) for all tally treesHeights on subsample of trees (by species & DBH class)Survey-grade GPS for plot centerHeight profile (cover by layer) for (live and dead) vegetation on plot (> 3 % cover)Develop and test methods to determine how inventory plots, sampled high-resolution airborne (lidar/hyperspectral/thermal) remote sensing data, and satellite imagery can be most efficiently integrated to support both the NGHGI and FIA programs, especially in remote regions such as interior Alaska. This work will include both design-based and model-based Bayesian approaches to sampling, estimation and inference.Support the monitoring of forest carbon stock changes associated with forest degradation in tropical countries.Collaborate to regularly interact with the various Forest Service teams and outside stakeholders to guide the use of LIDAR and other advanced remote sensing technologies to support MRV programs.Co-author publication(s) of research findings, as appropriate, with respective participation by individual scientists on their particular subjects.