Look for complete geospatial metadata in this layer's associated xml document available from the download link * Metric Name: Canopy Veg Cover * Tier: 1 * Data Vintage: 06/2020 * Unit Of Measure: Canopy cover is a 0-100% cover fraction and may be more precisely described as "canopy density." It calculates the proportion of all lidar returns >=5m divided by the total number of returns in that grid cell. This, therefore, does not include all vegetation, but instead describes the density of vegetation in the canopy vertical stratum (veg 5m and taller). * Metric Definition and Relevance: This layer represents horizontal cover fraction occupied by tree canopies. Maps community type & fire regime, as well as available habitat for tree-dwelling species. * Creation Method: Each forest structure metric was derived directly from airborne lidar data, hosted by the USGS 3D Elevation Program. However, these data are only available for a small fraction of California’s 423,970 km² area. To overcome this, we trained deep learning models—a form of pattern recognition—to identify these forest structure patterns in satellite imagery, then mapped each metric statewide. These algorithms are of the U-net family of neural network architectures that perform pixel-wise regression and classification tasks. The satellite data includes imagery from Sentinel-1 C-band radar sensors and Sentinel-2 multispectral sensors at 10 m spatial resolution, collected in Fall 2019. Future versions will include imagery from PlanetScope multispectral sensors at 3 m resolution. The 10m raster was resampled to 30m resolution by the RRK team. Original datset downloaded from [California Forest Observatory - Organizations - WIFIRE Commons Data Catalog (sdsc.edu)](https://wifire- data.sdsc.edu/organization/california-forest-observatory). For more information, go to * Credits: California Forest Observatory (Salo Sciences), 2020