Skip to main content
Efficient, Cost-Effective Field Sampling Protocol to Pair with Remote Sensing Data for Carbon Monitoring
State-of-the-art, lidar-based remote sensing technologies are high-precision tools that are being used to support cost-effective carbon monitoring systems around the world. Researchers at the Pacific Northwest Research Station and their colleagues developed an efficient sampling design and measurement protocol that can be used in combination with remote sensing data sources to estimate and model forest biomass and carbon at multiple scales. This method supports more accurate carbon monitoring in programs worldwide.
Resource Monitoring and Assessment
State-of-the-art remote sensing technologies and advanced spatial analysis techniques are increasingly being used to support carbon monitoring systems around the world. These lidar-based remote sensing methods increase precision and reduce the costs associated with traditional estimations of greenhouse gas emissions. As demand for this information grows, there is a need for cost-effective, efficient sampling protocols that will provide accurate estimates of forest biomass and carbon at multiple spatial scales.
Together with their partners, researchers at the Pacific Northwest Research Station developed an efficient field sampling design and measurement protocol that provides field-based estimates of biomass and carbon stored in trees and woody materials to support carbon monitoring systems that use Landsat time series and airborne lidar. The prototype's “measurable, reportable, verifiable” (MRV) design uses a limited number of field plots, lidar sampling, and disturbance information derived from Landsat time series data. Measurements from this field sampling protocol can be used in combination with remote sensing data sources to estimate forest carbon and biomass at multiple spatial scales that can be applied across entire states or regions. The new protocol will support a variety of carbon monitoring activities nationally and internationally.