Accurate estimation of terrestrial biomass on regional to global scales is a key step towards better understanding the global carbon cycle. Remotely sensed data have become the primary source for large-scale biomass estimations (Goetz et al. 2009); however, large uncertainty levels and a lack of long-term data have limited the usefulness of these approaches. We will examine ways to integrate data from multiple sensors (optical and LiDAR) in order to
- Increase the accuracy of regional aboveground biomass estimates
- Create standardized long-term datasets of biomass changes
We will leverage the spatial coverage provided by the LTER network to examine biomass dynamics across multiple scales.
In the first hour of the workshop, organizers will give presentations on how LiDAR and Landsat data are currently being used to estimate aboveground biomass at certain LTER sites (e.g. Andrews Experimental Forest). We will then describe newly developed methods to integrate LiDAR and Landsat to produce accurate long-term estimates of biomass losses and gains at regional scales (e.g. Asner 2009). We will also introduce a database of long-term (1984-2011) Landsat data for every LTER site that will be housed by the LTER network office. During the second hour, we will discuses ways to implement standardized methodologies for estimating aboveground biomass at multiple LTER sites in order to facilitate cross-site research projects.
This working group will generate cross-site collaborations that will continue following the LTER ASM meeting. Our goal is to initiate a cross-site project that will investigate drivers of biomass dynamics across local, regional, and continental scales.
Asner, G.P. 2009. Tropical forest carbon assessment: integrating satellite and airborne mapping approaches. Environmental Research Letters 4:034009
Goetz, S.J. et al. 2009. Mapping and monitoring carbon stocks with satellite observations: a comparison of methods. Carbon Balance and Management 4:2-7
This working group is sponsored by the LTER Spatial Data and Analysis Committee.