File Name

20220930 File Name raster digital data This geospatial dataset, the Regional Resource Kit, was created for the California Wildfire and Forest Resilience Task Force and for use by the many federal, state, and local efforts to restore resiliency to forests in California. It was assembled by a federal-state-university consortium that includes the Climate and Wildfire Institute (CWI), USDA Forest Service Pacific Southwest Research Station(PSW). the Center for Ecosystem Climate Solutions (CECS) - UC Irvine, California Department of Forestry and Fire Protection (CAL FIRE) and partners at UC Berkeley. ACCEL project: The USDA Forest Service, in collaboration with the California Natural Resources Agency and other partners, is committed to increasing the “pace and scale” of forest treatments in California. Multiple federal and state initiatives in the last few years detail this commitment. Land managers need support to plan and implement treatments that will address restoration at a landscape scale. An essential component of these initiatives is the spatial data representing landscape conditions and new analytical tools for planning management investments. The Pacific Southwest Research Station (PSW) scientists and staff from Region 5 Information Management, Mapping and Remote Sensing (MARS) Team, joined forces to develop and/or collect and assemble existing sources of spatial data. This project, referred to as the ACCEL project (for accelerating pace and scale of treatments), combines the expertise and experience of research and management to build this library of data on landscape conditions. These data reflect landscape conditions across ten “Pillars of Resilience” which address the full array of landscape management objectives. • Pillars are the desired long-term, landscape-scale outcomes of restoring resilience. They include ecological values, such as biodiversity, as well as societal benefits to communities, such as water security. • Elements represent the primary processes and functions that altogether make up a pillar, such as focal species, water quality, or economic health. • Metrics describe the characteristics of elements in quantitative or qualitative terms. Users can use metrics to assess, plan for, measure, and monitor progress towards desired outcomes and greater resilience. While pillars and elements are consistent across the Sierra Nevada, the metrics that a group uses may vary from region to region based on ecological and social differences (for example forest types, economy), available data, and user preferences. The ten pillars are Forest Resilience, Water Security, Carbon Sequestration, Air Quality, Fire Dynamics, Fire Adapted Communities, Economic Diversity, Social & Cultural Well-Being, Wetland Integrity, Biodiversity Conservation. The individual “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. Landscape level assessment using these high-quality data, combined with decision support tools that can help evaluate alternative treatment strategies, are fundamental to inform and support large landscape restoration planning. These data are assembled in one place to provide comprehensive access for land managers. They represent conditions as of 2022 and intentions are to refresh these data on an annual basis. Each metric is defined to help the end-users of the data (and for use with any decision support tools) to understand: • The definition meant by a given metric • The expected use(s) of the metric • The resolution of the developed data • The data sources used to derive the metric • The intended method of metric derivation • Where reasonable, a desired management target References have been included to help the reader understand methods used for deriving metrics. This information will help people make better use of all the assembled information and how it can best be used with various decision support tools. The metric dictionary that accompanies this set of data will be updated periodically, as necessary. Complete Unknown ISO 19115 Topic Categories environment geoscientificInformation planningCadastre None Appropriate use includes regional to 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 USDA Forest Service makes 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: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.ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything this license permits. USDA Forest Service, Pacific Southwest Research Station Patricia Manley Research Program Manager patricia.manley@usda.gov Esri ArcGIS 12.9.2.32739 Raster Grid Cell 3300 2550 29.976734 29.983910 32 1 Upper Left FALSE LZ77 1 pixel codes FGDBR TRUE 20221221 FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 local time 20240724 ArcGIS Metadata 1.0 <DIV STYLE="text-align:Left;"><DIV><DIV>The user is responsible to verify the limitations of the geospatial data and to use the data accordingly. For all data layers, please check each data source and adhere to any limitations established by the data creator. In general, adhere to the terms for use listed at the bottom of this paragraph. 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.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. ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. 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. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything this license permits.</DIV></DIV></DIV> Esri ArcGIS 12.9.2.32739 Project Manager, Regional Resource Kit Project Climate and Wildfire Institute pstine@climateandwildfire.org Peter A. Stine Senior Geospatial Data Analyst Climate and Wildfire Institute cclark@climateandwildfire.org Carol Clark CECS; <https://california-ecosystem-climate.solutions/> RRK project: Reducing the risk of large, high intensity fire (and other mega-disturbances) through forest treatments has become a management imperative in California. A Strategy for Shared Stewardship (2018) (https://www.fs.usda.gov:443/sites/default/files/toward-shared-stewardship.pdf) and the USFS Wildfire Crisis Implementation Plan (2022) (https://www.fs.usda.gov:443/sites/default/files/Wildfire-Crisis-Implementation-Plan.pdf) reinforce specific goals for pace and scale of strategic forest treatments over the next decade. Concurrently, the State of California has issued a new Wildfire and Forest Resilience Action Plan (2022) (https://wildfiretaskforce.org:443/wp-content/uploads/2022/04/californiawildfireandforestresilienceactionplan.pdf), designed to strategically accelerate efforts to restore the health and resilience of California forests through a joint State of California - Forest Service framework to improve and enhance forest stewardship in California. The social incentives and the scientific knowledge to pursue meaningful restoration of forested landscapes in California are firmly established. High quality geospatial data are an essential ingredient to address restoration/conservation of the broad suite of core socio-ecological values across landscapes, and to drive analytic tools for planning management investments. To support these initiatives an interagency team of scientists from the Forest Service/Pacific Southwest Research Station, California Natural Resources Agency/CALFIRE, and the University of California at Berkeley and University of California at Irvine collaborated on development of a comprehensive set of mapped data layers needed to accomplish large-scale landscape planning and restoration. Landscape level assessment using high quality data developed from ecological modeling techniques, informative analytical approaches and the resulting credible scientific outputs will be fundamental to inform and support large landscape restoration planning and execution. The data layers included in this kit are meant to assist land managers in assessing their current landscape and plan for treatments to enhance resilience to human and natural disturbances. Thus each layer represents what the interagency team believes are the most relevant and reliable geospatial data available at this time. Each layer has been examined by the team and is supported by published data and/or was developed using standard methods. The methods for developing each layer are documented in the metric dictionary; however, the accuracy of each layer has not been quantified. It is anticipated that all data layers will be updated and refined as methods and source data evolve and improve. RRK Components: The authors and their partners are committed to increasing the “pace and scale” of forest treatments in California. Multiple federal and state initiatives in the last few years detail this commitment. Land managers need support to plan and implement treatments that will address restoration at a landscape scale. An essential component of these initiatives is the spatial data representing landscape conditions combined with new analytical tools for planning management investments. The authors joined forces to develop and/or collect and assemble existing sources of spatial data. This project, referred to as RRK (Regional Resource Kit), combines the expertise and experience of research and management to build this library of data on landscape conditions. These data reflect landscape conditions across ten “Pillars of Resilience” which address the full array of landscape management objectives. • Pillars are the desired long-term, landscape-scale outcomes of restoring resilience. They include ecological values, such as biodiversity, as well as societal benefits to communities, such as water security. • Elements represent the primary processes and functions that altogether make up a pillar, such as focal species, water quality, or economic health. • Metrics describe the characteristics of elements in quantitative or qualitative terms. Users can use metrics to assess, plan for, measure, and monitor progress towards desired outcomes and greater resilience. While pillars and elements are consistent across the Sierra Nevada, the metrics that a group uses may vary from region to region based on ecological and social differences (for example forest types, economy), available data, and user preferences. The ten pillars are Forest and Shrubland Resilience, Water Security, Carbon Sequestration, Air Quality, Fire Dynamics, Fire Adapted Communities, Economic Diversity, Social & Cultural Well-Being, Wetland Integrity, Biodiversity Conservation. The individual “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. Landscape level assessment using these high-quality data, combined with decision support tools that can help evaluate alternative treatment strategies, are fundamental to inform and support large landscape restoration planning. These data are assembled in one place to provide comprehensive access for land managers. They represent conditions as of 2022 (or otherwise, as noted) and intentions are to refresh these data on an annual basis. Each metric includes the following information to help users of the data (and for use with any decision support tools) to understand the details of the metric. This information is also included in a "metric dictionary" that comes with this set of metrics. • Tier group the metric is in (1, 2, or 3) • The vintage of the data • The definition meant by a given metric • The expected use(s) of the metric • The resolution of the developed data • The data sources used to derive the metric • The intended method of metric derivation • Where reasonable, a desired management target References have been included in the metric dictionary to help the reader understand methods used for deriving metrics and will be updated periodically, as necessary. This information will help people make better use of all the assembled information and how it can best be used with various decision support tools. The data layers included in this Sierra Nevada Regional Resource Kit were originally developed by the U.S. Forest Service “ACCEL” program, a joint effort of the Pacific Southwest Research Station and Region 5. The transition to the Regional Resource Kit reflects the growth of the partnership to include interests of the California Wildfire and Forest Resilience Task Force and academic scientists from UC Berkeley and UC Irvine who have been developing information that contributes to this overall effort. 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 provide 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 ones included for calculations or regional statistics. Example: Annual Burn Probability. Tier 2 – metrics relevant to a single region or relevant to multiple Regions but data layers differ among Regions because of varied data availability (sources) across Regions. Example: California gnatcatcher habitat suitability. Tier 3 - metrics are those that would be of interest to some land managers for specific applications but not included as a core metric in an RRK. Example: Distribution of the Quino checkerspot butterfly. Each RRK will contain all Tier 1 and Tier 2 data together to comprise the kit. Tier 3 data will be pointed to for reference and use, as needed. Within each Tier, the data layers are available in two forms: 1) data values native to the metric (raw), and 2) translated data values. The raw data values are in the units of the metric, so for example the species richness map will show an estimated number of terrestrial vertebrate species per acre that can range from 0 to any number for each 30-m pixel, and the departure from historical fire return interval (FRID) map will have values that range from -100% to +100% departure. The translated data values represent each metric using a common unit of measure with the same range of values from -1 to +1 that represent values that are generally considered favorable (+1) and unfavorable (-1). In the case of species richness, higher species counts are considered more favorable and lower species counts are considered less favorable. In the case of FRID, values within the historical fire return interval are considered favorable, and high departure from the historical fire return interval is considered less favorable. In both cases, more and less favorable conditions for each metric are represented by values that range from +1 to -1 (respectively) so that multiple metrics can be evaluated together, including summarizing overall conditions at element and pillar levels to characterize socio-ecological resilience. Some data layers within this kit contain null values. We point this out here so users of the data will be aware and take whatever measures appropriate as they use and analyze the data. For some raster datasets in the RRK, areas have been masked (blanked) out and have a cell value of NoData (also referred to as null, NaN or missing). We, as producers and users of the data, cannot ignore NoData or fill them with zeros, since zero is often a valid value for some datasets. Removing NoData cells is not an option, a raster is a continuous grid. For users of the data performing further analyses and combining or "stacking" rasters, these NoData cells will mask out all values in that location in the output. To avoid this issue, the user must create values for the cells before combining them (i.e. 999 or any numeric value that is not real and clearly out of the range of the other values). Reasons for masking (blanking) out cells in RRK data: · Cells are lakes or reservoirs · Cells are urban or agriculture · Cells contain no information relevant to the dataset (i.e. streams, habitat) · Area (cells) subject to fire or other disturbance but the post disturbance condition or value is unknown - Metric Name: Shrub Cover - Tier: 1 - Data Vintage: 12/2021 - Unit Of Measure: Fractional non-overlapping absolute cover; continuous variable from 0 to 1. - Metric Definition and Relevance: Total shrub cover as measured by the fractional non-overlapping absolute shrub cover, viewed vertically. Provides a first order measure of vegetation type when combined with parallel observations of tree and herbaceous cover. Data from the National Land Cover Database (NLCD) are used for training, and NLCD definitions for cover (for example, the distinction between tree vs shrub) are expected to be similar in the CECS data sets. - Creation Method: Machine learning (Random Forest) using the National Land Cover Database for training and Landsat observations as predictors. See https://doi.org/10.1029/2021AV000654 for further information. VegCover_Shrub_2021.tif 2022-09-30 raster digital data Climate and Wildfire Institute Peter A. Stine Project Manager, Regional Resource Kit Project pstine@climateandwildfire.org Peter A. Stine environment, geoscientific Information, planning Cadastre, land management, landscape restoration ISO 19115 Topic Categories environment geoscientific Information planning Cadastre land management landscape restoration 1 -121.844496 -121.639402 40.162097 39.975478 2 3300 2550 1.0 150000000 5000 VegCover_Shrub_2021_tif -157080.084775 -139963.369831 219258.533639 239677.576134 1 Projected GCS_North_American_1983 Linear Unit: Meter (1.000000) NAD_1983_California_Teale_Albers <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><WKT>PROJCS["NAD_1983_California_Teale_Albers",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Albers"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",-4000000.0],PARAMETER["Central_Meridian",-120.0],PARAMETER["Standard_Parallel_1",34.0],PARAMETER["Standard_Parallel_2",40.5],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",3310]]</WKT><XOrigin>-16909700</XOrigin><YOrigin>-8597000</YOrigin><XYScale>266332319.7555542</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>3310</WKID><LatestWKID>3310</LatestWKID></ProjectedCoordinateSystem> FGDC 20240724 11533300 20240724 11533300 Peter A. Stine Climate and Wildfire Institute Project Manager, Regional Resource Kit Project pstine@climateandwildfire.org Peter A. Stine Carol Clark Climate and Wildfire Institute Senior Geospatial Data Manager cclark@climateandwildfire.org File Geodatabase Raster Dataset dataset EPSG 6.8(9.2.0) row and column 29.976734 29.983910