This raster layer represents forest residues for the state of California in 2018. It was developed by the Schatz Energy Research Center as part of the C-BREC (California Biomass Residue Emissions Characterization) model. The raster is based on the LEMMA (Landscape Ecology, Modeling, Mapping, and Analysis) group's forest state data for 2012, which was grown forward to represent residues in 2018 by NRSIG (Natural Resource Spatial Informatics Group) at University of Washington using FVS (Forest Vegetation Simulator).

2018 Tahoe Nearshore Topographic Bathymetric DEM. Green LiDAR from Spatial Informatics Group (SIG).

This raster layer represents forest residues for the state of California in 2018. It was developed by the Schatz Energy Research Center as part of the C-BREC (California Biomass Residue Emissions Characterization) model. The raster is based on the LEMMA (Landscape Ecology, Modeling, Mapping, and Analysis) group's forest state data for 2012, which was grown forward to represent residues in 2018 by NRSIG (Natural Resource Spatial Informatics Group) at University of Washington using FVS (Forest Vegetation Simulator).Pixel values are estimates of the total biomass residue generated by a 40% Thin From Below treatment, reported in imperial short tons per acre. The value for a given pixel is the sum of biomass estimates across all residue size classes (foliage, branches, logs 4-6" in diameter, logs 6-9" in diameter, and logs greater than 9" in diameter).For more information on the C-BREC model, you can visit the following links:C-BREC tool webpage: https://schatzcenter.org/cbrec/C-BREC model background and use: https://iopscience.iop.org/article/10.1088/1748-9326/acbd93#erlacbd93s3

Spatial distribution evaluation results.