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

* Metric Name: Cost of Potential Treatments  

* Tier: 2  

* Data Vintage: last updated 09/2023  

* Unit Of Measure: Dollars per CCF (100 cubic feet) for sawlog layers and Dollars per BDT (bone dry ton) for biomass layers  

* Metric Definition and Relevance: This metric is dependent on predefined treatments or silvicultural prescriptions, which are best generated at the local and/or project level. The cost to perform each treatment depends on a defined prescription and should consider an array of factors including the spatial juxtaposition of the resources and infrastructure, as well as the location of the saw timber and biomass processing plants. 

Treatment cost calculations take into consideration the multiple costs
necessary to move material from the forest harvest site to a processing
location (sawmill or biomass facility) and includes the costs of felling,
processing, skidding and hauling:

  * costs to move material along different types of roads (i.e., dirt, paved, highways, etc.)
  * across barriers (i.e., water courses)
  * operational costs
  * machine costs
  * speed of moving material across the landscape.

Cost values have been broken down into the costs to move either biomass or
sawlogs, and for a high-cost and low-cost scenario (reflecting variation in
machine rates). Non-mechanical hand treatments, piling and burning operations,
and prescribed fire treatments are not addressed in this data set. We hope to
provide cost estimates on those types of treatments later.

  

* Creation Method: The methods are based on the “RMRS Raster Utility and Function Modeling” and the “Delivered Cost Modeling” approaches developed by John Hogland at the Rocky Mountain Research Station. Using a series of sliders that define various rates for multiple harvesting systems and then running the delivered cost model. Within the modeling, the following analyses will be performed:

  1. Subset and attribute OSM roads with speed based on criteria in Table 1.
  2. Create barrier to offroad motion for off road analysis using a subset of OSM streams, water bodies, interstates, and highways.
  3. Estimate potential on road and offroad cost surfaces for each harvesting system using interactive sliders based on the criteria in Table 2.
  4. Create felling and processing surfaces and add potential costs.
  5. Specify where harvesting systems occur and subset system costs to those locations.
  6. Create final spatial representation of the potential cost to treat each raster cell on a dollar per CCF basis.
  7. Save raster surfaces.
  8. Remove non-forest types (source FVEG 2023)
  9. Remove wilderness areas (source PAD Wilderness)
  10. Convert units on biomass rasters from $/CCF to $/BDT (bone dry ton)

The data has been extracted from open street maps and USFS 3dep and consist of
base Raster and Vector datasets that have been used throughout the study area:

· Elevation (raster): elevation surface units meters (3dep)

· Roads (vector): Open Street Map roads based on Tiger Lines (OSM)

· Streams (vector): Open Street Map streams based on NHD (OSM)

· Water bodies (vector): OSM water bodies

· Sawmills (vector): location of the sawmill

· Biomass facilities (vector): location of biomass facilities (USFS)

· North Coast RRK study area extent (vector): North Coast RRK study area
extent

 ****

**Reference Tables**

Table 1: Road segment travel speed by[ OSM
highway](https://wiki.openstreetmap.org/wiki/Key:highway) class types

Table 2: Criteria used to spatially define harvesting systems and treatment
costs. Default machine rate of travel, and capacity estimates (“high cost
scenario”) derived from meetings with Lisa Ball, Jacob Baker (STF), Michal Jow
(STF), Brian McCrory, and John Hogland. Machine rates of travel for “low cost
scenario” derived from Chang et al. 2023.

Chang, H., et al. (2023). "The Cost of Forest Thinning Operations in the
Western United States: A Systematic Literature Review and New Thinning Cost
Model." Journal of Forestry **121** (2): 193-206.

  

* Credits: Rocky Mountain Research Station, U.S. Forest Service U.S. Geological Survey (USGS), Protected Areas Database (PAD-US) 3.0 FVEG 2023 \--CALFIRE, CDFW, LANDFIRE, California Forest Observatory (SALO), USDA Forest Service Chang, H, Han-Sup Han, Nathaniel Anderson, Yeon-Su Kim, Sang-Kyun Han. 2023. The Cost of Forest Thinning Operations in the Western United States: A Systematic Literature Review and New Thinning Cost Model. Journal of Forestry, **121** (2): 193-206