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The data layers included in this Northern California Regional Resource Kit were assembled/developed by a partnership that includes the Pacific Southwest Research Station of the U.S. Forest Service, the Fire and Resource Assessment Program (FRAP) of CALFIRE, the Climate and Wildfire Institute, and faculty from the University of California Berkeley and Irvine. This science team is working together at the behest of the California Wildfire and Forest Resilience Task Force. As we continue to develop geospatial data for landscape assessment and planning throughout the state, this partnership has now taken the lead in the creation of the Regional Resource Kits for the four regions of California.
The RRK has adopted the Framework for Resilience to provide a structure for assessing landscape conditions, setting objectives, designing projects, and measuring progress towards social-ecological resilience. There are ten pillars that represent the desired outcomes of landscape resilience. Each of the pillars provides a series of elements and under the elements, metrics (the data layers) for assessing landscape conditions and verifying that actions meet resilience objectives.
The metrics are organized by the ten pillars of resilience in the Framework for Resilience. The Metrics describe the characteristics of the elements (key characteristics) of each pillar in quantitative or, in a few cases, qualitative terms. Metrics are used to assess, plan for, measure, and monitor progress toward desired outcomes and greater resilience. Metrics are selected to be informative, meaningful, and actionable to meet the needs of management.
The metrics are also divided into three “tiers.” Among all these metrics, some are created and relevant statewide. Other metrics are more suited to conditions within a given region. The “Tiers” for metrics included in each RRK:
Tier 1 – metrics that are a single, consistent data layer, developed statewide; they can also be clipped to the boundary of the region so values within that region are the only... |
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The data layers included in this Northern California Regional Resource Kit were assembled/developed by a partnership that includes the Pacific Southwest Research Station of the U.S. Forest Service, the Fire and Resource Assessment Program (FRAP) of CALFIRE, the Climate and Wildfire Institute, and faculty from the University of California Berkeley and Irvine. This science team is working together at the behest of the California Wildfire and Forest Resilience Task Force. As we continue to develop geospatial data for landscape assessment and planning throughout the state, this partnership has now taken the lead in the creation of the Regional Resource Kits for the four regions of California.
The RRK has adopted the Framework for Resilience to provide a structure for assessing landscape conditions, setting objectives, designing projects, and measuring progress towards social-ecological resilience. There are ten pillars that represent the desired outcomes of landscape resilience. Each of the pillars provides a series of elements and under the elements, metrics (the data layers) for assessing landscape conditions and verifying that actions meet resilience objectives.
The metrics are organized by the ten pillars of resilience in the Framework for Resilience. The Metrics describe the characteristics of the elements (key characteristics) of each pillar in quantitative or, in a few cases, qualitative terms. Metrics are used to assess, plan for, measure, and monitor progress toward desired outcomes and greater resilience. Metrics are selected to be informative, meaningful, and actionable to meet the needs of management.
The metrics are also divided into three “tiers.” Among all these metrics, some are created and relevant statewide. Other metrics are more suited to conditions within a given region. The “Tiers” for metrics included in each RRK:
Tier 1 – metrics that are a single, consistent data layer, developed statewide; they can also be clipped to the boundary of the region so values within that region are the only... |
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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 |
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- 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., p, ul, p, p, p, - 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:, p, ol, p, p, p, p, p, p, p, p, p, p, p, p, p, p, p, p, p, p, p |
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<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Appropriate use includes regional to statewide assessments of vegetation cover, land cover, or land use change trends, total extent of vegetation cover, land cover, or land use change, and aggregated summaries of vegetation cover, land cover, or land use change. Further use includes applying these data to assess management opportunities for treatments to restore landscape resiliency. The authors make no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness, or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly. For all data layers you are free to share, copy, and redistribute the material in any medium or format AND adapt, remix, transform, and build upon the material for any purpose, even commercially under the following terms:</SPAN></P><P><SPAN>Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. </SPAN></P><P><SPAN>ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. </SPAN></P><P><SPAN>No commercial use – the user is responsible for acknowledging those data layers within this RRK (as determined by the source of the data) that are not permitted for commercial use. </SPAN></P><P><SPAN>No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything this license permits.</SPAN></P></DIV></DIV></DIV> |
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biomassTreatmentCost_high.tif |
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["environment","geoscientific Information","planning Cadastre","land management","landscape restoration"] |
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150000000 |
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