Kennedy (CMS 2020): Developing a framework to quantify uncertainty and harmonize diverse earth observation estimates of forest carbon
Robert E Kennedy, Oregon State University, rkennedy@coas.oregonstate.edu (Presenter)
Tools are needed to quantify uncertainty in a manner that is spatially explicit, transparent and scalable. Moreover, as new EO methods emerge, registration and verification bodies need tools to quantify how those methods improve the uncertainty.
Through three progressive objectives, we propose a framework to address these challenges. The first objective focuses on building a hierarchical Bayesian structure that models spatial dependence and produces spatially explicit estimates of uncertainty that can be quantified for any arbitrary area. The second objective tests and demonstrates the framework in incorporating new EO-derived maps, new data types, and in providing tools to harmonize across existing biomass maps. The third objective extends these tests to the temporal realm, evaluating how the framework can be used to extend monitoring of carbon. We will test the objectives at sites across gradients of forest type and climate in the West Coast states of the U.S., and we will incorporate prior CMS biomass data both at the broad and the local scales.
As a synthetic effort, our proposing team (both Co-Is and collaborators) brings together experts who formerly worked on diverse CMS projects, as well as experts in carbon markets. The origins of this project emerged from discussions with carbon-interested groups, and our work is heavily driven by stakeholder need. Through stakeholders already committed and additional stakeholders we recruit in the project, we will convene a Technical Advisory Group (TAG) to help guide implementation of the project goals. Current committed members include those from industry, agencies, and carbon registries.
Overall project deliverables include:
- baseline maps of forest biomass, tree lists, and associated uncertainty surfaces
- demonstrations of improvement in uncertainty surfaces resulting from incorporation of small-footprint lidar maps, GEDI data, and potentially from other EO products from photogrammetry and private firms
- tools to bring time-series predictions into carbon-market monitoring paradigms
- web-based interfaces to allow broad use and adoption of the framework by agencies, registries, and private landowners.
Associated Project(s):
Poster Location ID: 18
Presentation Type: Poster
Session: Poster Session 1
Session Date: Wednesday (9/27) 1:15 PM