Look for complete geospatial metadata in this layer's associated xml document available from the download link

* Metric Name: Canopy Layer Count  

* Tier: 1  

* Data Vintage: 06/2020  

* Unit Of Measure: Count  

* Represent element and pillar: No  

* Type and distribution of data: Zero-inflated, right-skewed distribution representing count values. Raw data values range from 0 to 6.  

* Translation: Where is the canopy layer count highest?  

* Translation method and outcome: Raw data values translated to range from +1 to -1 representing more favorable to less favorable conditions, respectively. The proposition of more favorable is based on the objective of canopy layers being higher (positive linear slope). More favorable (translated to +1) and less favorable (translated to -1) are based on climate and vegetation regions (Table 5). 

Figure . Histogram and scoring criterion of canopy layer count across the
Central Coast.

Figure . Histogram of translated canopy layer count across the Central Coast.

Figure . Maps displaying raw metric and translated metric canopy layer count
across the Central Coast.

  

* Metric Definition and Relevance: This layer represents the number of distinct vertical canopy layers of trees. Vertical layer count is a proxy for leaf area index, and maps canopy complexity. Since LANDFIRE doesn’t support a NoData value, all NoData pixels in canopy fuel metrics were set to 0 in the Landscape files. (e.g., canopy cover was set to 0 in all NoData locations). Topographic data and surface fuel model remain unaltered.  

* Credits: California Forest Observatory (Salo Sciences), 2020