U.S. States and Canada Provinces represents the states of the United States and the provinces of Canada.

Metadata https://oe.oregonexplorer.info/metadata/bnd_us_states.htm

Download https://oregonexplorer.info/ExternalContent/SpatialDataForDownload/bnd_us_states.zip

This feature class GIS dataset contains building footprints depicting building shape and location in the state of Oregon. All contributing datasets were compiled into the stateside dataset. Static datasets or infrequently maintained datasets were reviewed for quality. New building footprint data were reviewed and digitized from the Oregon Statewide Imagery Program 2017 and 2018.

This data layer is an element of the Oregon GIS Framework. This theme contains PLS lines for the State of Oregon. This PLS theme includes donation claims lands. Attributes in this theme show Township Range and Section values.

This theme delineates Urban Growth Boundaries (UGBs) in the state of Oregon. Oregon land use laws limit development outside of urban growth boundaries. The line work was created by various sources including the Oregon Department of Land Conservation and Development (DLCD), the Oregon Department of Transportation (ODOT), Metro Regional Council of Governments (Metro), county and city GIS departments, and the Oregon Department of Administrative Services - Geospatial Enterprise Office (DAS-GEO).

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Download http://oe.oregonexplorer.info/ExternalContent/SpatialDataforDownload/UGB_2013.zip

This layer was derived from the Oregon Watershed Restoration Inventory (OWRI) for use in the SageCon Landscape Planning Tool (https://tools.oregonexplorer.info/viewer/sagecon_landscape_planning_tool ) on Oregon Explorer. It includes only activities completed in the year 2000 or later, clipped to the boundary of Eastern Oregon Counties, and representing the a subset of activities within the following activity types: Upland, Wetland, Riparian. The following activity types were excluded: Instream, Estuarine, Urban, Fish Passage, Instream Flow, Fish Screening, Road. Activities were re-categorized into five categories for display: Invasive plant control, Juniper removal, Other vegetation management, Riparian or wet meadow restoration, Vegetation planting or seeding. Users are encourage to download the original GIS and associated tabular data from the Oregon Watershed Enhancement Board to access complete restoration project data: https://hub.oregonexplorer.info/pages/water-planning-enhancing-watersheds-in-oregon#TheOWRIDatabaseandGISdata

OverviewORS 477.490 requires Oregon Sate University (OSU) and the Oregon Department of Forestry (ODF) to develop a statewide wildland-urban interface (WUI) map that will be used in conjunction with the statewide wildfire hazard map (ORS 477.490) by the Oregon State Fire Marshal to determine on which properties defensible space standards apply (ORS 476.392) and by the Building Codes Division to determine to which structures home hardening building codes apply (ORS 455.612).Rules directing development of the WUI are listed in OAR-629-044-1011 and 629-044-1016. A comprehensive description of datasets and geospatial processing is available at https://hazardmap.forestry.oregonstate.edu/understand-map. The official statewide WUI map is available on the Oregon Wildfire Risk Explorer at https://tools.oregonexplorer.info/viewer/wildfire.Following is an overview of the data and methods used develop the statewide WUI map.Wildland-Urban InterfaceCreating a statewide map of the WUI involved two general steps. First, we determined which parts of Oregon met the minimum building density requirements to be classified as WUI. Second, for those areas that met the minimum building density threshold, we evaluated the amount and proximity of wildland or vegetative fuels. Following is a summary of geospatial tasks used to create the WUI.Develop a potential WUI map of all areas that meet the minimum density of structures and other human development - According to OAR 629-044-1011, the boundary of Oregon’s WUI is defined in part as areas with a minimum building density of one building per 40 acres, the same threshold defined in the federal register (Executive Order 13728, 2016), and any area within an Urban Growth Boundary (UGB) regardless of the building density. Step One characterizes all the locations in Oregon that could be considered for inclusion in the WUI on building density and UGB extent alone. The result of Step One was a map of potential WUI which was then further refined into final WUI map based on fuels density and proximity in Step Two.Compile statewide tax lots.Map all eligible structures and other human development.Simplify structure dataset to no more than one structure per tax lotCalculate structure density and identify all areas with greater than one structure per 40 acresAdd urban growth boundaries to all the areas that meet the density requirements from the previous step.Classify WUI based on amount and proximity of fuel. The WUI is also defined by the density and proximity of wildland and vegetative fuels (“fuels”). By including density and proximity of fuels in the definition of the WUI, the urban core is excluded, and the focus is placed on those areas with sufficient building density and sufficient fuels to facilitate a WUI conflagration. Consistent with national standards, we further classified the WUI into three general classes to inform effective risk management strategies. The following describes how we refined the potential WUI output from step one into the fina

This map shows the location and names of populated places in Oregon. This information is from the United States Geological Survey Geographic Names Information System (GNIS).

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Social vulnerability refers to the social, economic, and cultural factors that influence access to resources and influence the ability of individuals, households, or communities to prevent, respond to, and recover from events such as wildfire (Coughlan et al., 2019; Cutter et al., 2003). Some examples of social, economic, or cultural factors that may influence social vulnerability to wildfire include income, language proficiency, cultural and psychological relationships to fire and land management, and level of trust in government (Coughlan et al., 2019). The SVI map layer developed for SB 762 identifies areas in the state that may be more vulnerable to the impacts of wildfire following the methodologies of the Centers for Disease Control (CDC) and Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index (SVI) (Centers for Disease Control Social Vulnerability Index 2018 Documentation, 2022) which was initially developed by Flanagan et al. (2011) for disaster risk management. NOTE: The SVI dataset within the Oregon Explorer tool underwent an update on February 5, 2024 to rectify inaccuracies in the original data. The initial SVI layer computations omitted data pertaining to the indicator "adults over age 65." We strongly recommend individuals who downloaded SVI data prior to this update revise their records accordingly.

This data layer is an element of the Oregon GIS Framework. This digital, geographically referenced data set was developed for the Oregon GIS department to provide updated state wide imagery. Digital 4 band ortho imagery covering the state of Oregon was flown in 2020. The 4 Band imagery was rectified and cut into a DOQs. Using web services to stream imagery: https://imagery.oregonexplorer.info/arcgis/rest/services/NAIP_2020

Download the data2023 PNW Quantitative Wildfire Risk Assessment MethodsThis dataset is a product of the 2023 Pacific Northwest Quantitative Wildfire Risk Assessment (PNW QWRA 2023). The purpose of the PNW QWRA 2023 is to provide foundational information about wildfire risk across the Pacific Northwest Region (which encompasses the states of Oregon and Washington). Analytics from the QWRA are used to guide vegetation management, fire response, and community planning at multiple scales. A QWRA considers several different components, each resolved spatially across the region, including:• likelihood of a fire burning, • the intensity of a fire if one should occur,• the exposure of assets and resources based on their locations, and • the susceptibility of those assets and resourcesData users are encouraged to refer to the PNW QWRA 2023 Methods Report for full details: https://oe.oregonexplorer.info/externalcontent/wildfire/PNW_QWRA_2023Methods.pdfPyrologix LLC modeled wildfire intensity and likelihood for the PNW QWRA 2023. Wildfire intensity was modeled using the WildEST model. These WildEST results were completed on the 2022 current-condition fuelscape (derived from LANDFIRE v2.2.0), which reflects fuelscape conditions for the year 2022 and includes all historical fuel disturbances through 2021. WildEST results were modified for risk calculations in the PNW QWRA 2023 using an irrigated agriculture mask to assign FLPs to pixels which are likely to be irrigated during fire season. An irrigated agriculture mask was created from LANDFIRE 2.2.0 Fire Behavior Fuel Models (where the model = “NB3”), and data collected from IrrMapper (Ketchum et al., 2020). All NB3 pixels as well as pixels that were classified as irrigated in three of the most recent five years in IrrMapper were included in the irrigated agriculture mask. Pixels in the irrigated agriculture mask were assigned an FLP of 0.75 for flame lengths between 0 – 2 feet, 0.25 for flame lengths 2 – 4 feet, and an FLP of 0 for all intensity values greater than 4 feet. Fire-effects flame-length probability rasters generated in WildEST were used for effects analysis in a landscape wildfire risk assessment, as described in USFS GTR-315. Wildfire likelihood was modeled using the large fire simulator, FSim (Finney et a., 2011). FSim is a comprehensive fire occurrence, growth, behavior, and suppression simulation system that uses locally relevant fuel, weather, topography, and historical fire occurrence information to generate spatially resolved estimates of the contemporary likelihood and intensity of wildfire events. FSim generates stochastic simulation data based on many thousands of iterations, then integrates those iterations into a probabilistic result. These FSim model results were completed on the 2022 current-condition fuelscape (derived from LANDFIRE). which reflects fuelscape conditions for the year 2022 and includes all historical fuel disturbances through 2021. This simulation is calibrated to the 2022 trend in wildfire occurrence. Wildfire likelihood is represented as burn probability (BP), which is the probability that a specific geographic location (30-m pixel) will experience a wildland fire during a specified time period (1 year).The PNW QWRA 2023 evaluated risk to eight highly-valued resources and assets (HVRAs): People and Property, Infrastructure, Drinking Water, Timber, Ecological Integrity, Wildlife Habitat, Agriculture, and Recreation. This data layer, Integrated Expected Net Value Change (ieNVC) represents risk integrated across eight HVRAs. Risk is estimated within the QWRA framework by integrating wildfire hazard with HVRA susceptibility (Scott et al., 2013). Risk is calculated for each pixel separately based on the fire hazard data for that pixel and based on which HVRAs are present. Fire impacts to each HVRA are characterized by the estimated change in value, a unitless approximation of whether the HVRA is beneficially or adversely affected by fire and to what magnitude. Accordingly, risk is expressed as net value change (NVC). Net value change is first calculated for all pixels across a sub-HVRA. The NVC for each HVRA is then calculated by summing the NVC of all its constituent sub-HVRAs. Finally, HVRA-level NVC risk can be summed across several or all HVRAs to calculate integrated NVC, representing risk to multiple HVRAs.Positive values indicate that wildfire is likely to have beneficial impacts on the HVRA while negative values indicate that the net outcomes are likely to be adverse. Risk is calculated based on a very wide range of plausible weather conditions, much wider than the range under which we have typically experienced large fires in the past. The specific conditions under which a wildfire occurs will determine the outcomes. When interpreting QWRA risk results bear in mind that fire will not always be beneficial in areas with positive NVC values and likewise it may be possible to experience beneficial fire in areas with negative NVC values. Citations:Ketchum, D., Jencso, K., Maneta, M.P., Melton, F., Jones, M.O., Huntington, J., 2020. IrrMapper: A Machine Learning Approach for High Resolution Mapping of Irrigated Agriculture Across the Western U.S. Remote Sensing 12, 2328. https://doi.org/10.3390/rs12142328Scott, J.H., Thompson, M.P., Calkin, D.E., 2013. A wildfire risk assessment framework for land and resource management (No. RMRS-GTR-315). U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Ft. Collins, CO. https://doi.org/10.2737/RMRS-GTR-315Finney, M.A., McHugh, C.W., Grenfell, I.C., Riley, K.L., Short, K.C., 2011. A simulation of probabilistic wildfire risk components for the continental United States. Stoch Environ Res Risk Assess 25, 973–1000. https://doi.org/10.1007/s00477-011-0462-z

OverviewORS 477.490 requires Oregon Sate University (OSU) and the Oregon Department of Forestry (ODF) to develop a statewide wildland-urban interface (WUI) map that will be used in conjunction with the statewide wildfire hazard map (ORS 477.490) by the Oregon State Fire Marshal to determine on which properties defensible space standards apply (ORS 476.392) and by the Building Codes Division to determine to which structures home hardening building codes apply (ORS 455.612).Rules directing development of the WUI are listed in OAR-629-044-1011 and 629-044-1016. A comprehensive description of datasets and geospatial processing is available at https://hazardmap.forestry.oregonstate.edu/understand-map. The official statewide WUI map is available on the Oregon Wildfire Risk Explorer at https://tools.oregonexplorer.info/viewer/wildfire.Following is an overview of the data and methods used develop the statewide WUI map.Wildland-Urban InterfaceCreating a statewide map of the WUI involved two general steps. First, we determined which parts of Oregon met the minimum building density requirements to be classified as WUI. Second, for those areas that met the minimum building density threshold, we evaluated the amount and proximity of wildland or vegetative fuels. Following is a summary of geospatial tasks used to create the WUI.Develop a potential WUI map of all areas that meet the minimum density of structures and other human development - According to OAR 629-044-1011, the boundary of Oregon’s WUI is defined in part as areas with a minimum building density of one building per 40 acres, the same threshold defined in the federal register (Executive Order 13728, 2016), and any area within an Urban Growth Boundary (UGB) regardless of the building density. Step One characterizes all the locations in Oregon that could be considered for inclusion in the WUI on building density and UGB extent alone. The result of Step One was a map of potential WUI which was then further refined into final WUI map based on fuels density and proximity in Step Two.Compile statewide tax lots.Map all eligible structures and other human development.Simplify structure dataset to no more than one structure per tax lotCalculate structure density and identify all areas with greater than one structure per 40 acresAdd urban growth boundaries to all the areas that meet the density requirements from the previous step.Classify WUI based on amount and proximity of fuel. The WUI is also defined by the density and proximity of wildland and vegetative fuels (“fuels”). By including density and proximity of fuels in the definition of the WUI, the urban core is excluded, and the focus is placed on those areas with sufficient building density and sufficient fuels to facilitate a WUI conflagration. Consistent with national standards, we further classified the WUI into three general classes to inform effective risk management strategies. The following describes how we refined the potential WUI output from step one into the final WUI map.Intermix WUI: Areas that met the minimum building density threshold in step one and which had at least 50% vegetative or wildland fuel cover were classified as Intermix WUIInterface WUI: Interface WUI includes areas that met the minimum building density threshold in step one, and which had less than 50% vegetative and/or wildland fuel cover but were within 1.5 miles of a large patch (≥ 2 sq. miles) of at least 75% vegetation and/or wildland fuelsOccluded WUI includes areas that met the minimum building density threshold in step one, and which had less than 50% vegetative and/or wildland fuel cover but were within 1.5 miles of a moderate patch (1 – 2 sq. miles) of at least 75% vegetation and/or wildland fuels.Detailed geospatial processing steps are described in the technical guide available at https://hazardmap.forestry.oregonstate.edu/understand-map

The Wildland Fire Interagency Geospatial Services (WFIGS) Group provides authoritative geospatial data products under the interagency Wildland Fire Data Program. Hosted in the National Interagency Fire Center ArcGIS Online Organization (The NIFC Org), WFIGS provides both internal and public facing data, accessible in a variety of formats.This service contains all wildland fire incidents from the IRWIN (Integrated Reporting of Wildland Fire Information) integration service that meet the following criteria:Categorized in IRWIN as a Wildfire (WF), Prescribed Fire (RX), or Incident Complex (CX) recordHas not been declared contained, controlled, nor outHas not had fire report record completed (certified)Is Valid and not "quarantined" in IRWIN due to potential conflicts with other records"Fall-off" rules are used to ensure that stale records are not retained. Records are removed from this service under the following conditions:Fire size is less than 10 acres (Size Class A or B), and fire information has not been updated in more than 3 daysFire size is between 10 and 100 acres (Size Class C), and fire information hasn't been updated in more than 8 daysFire size is larger than 100 acres (Size Class D-L), but fire information hasn't been updated in more than 14 days.Fire size used in the fall off rules is from the IncidentSize field.Criteria were determined by an NWCG Geospatial Subcommittee task group. Data are refreshed from IRWIN every 5 minutes.Fall-off rules are enforced hourly.Full details: https://data-nifc.opendata.arcgis.com/datasets/nifc::current-wildland-fire-incident-locations/about

This data layer is an element of the Oregon GIS Framework. A State Lambert mosaic derived from one-foot resolution color Digital Orthophoto Quadrangles (DOQ) of the eastern half of the state of Oregon. This digital, geographically referenced data set was developed for the Oregon GIS department to provide updated state wide imagery. Digital 4 band ortho imagery covering the state of Oregon was flown in 2018. The 4 Band imagery was rectified and cut into a DOQs. The imagery is provided in the Web Mercator Auxiliary Sphere projection as a tiled service, and in the State Lambert projection as an image service. Using web services to stream imagery: https://imagery.oregonexplorer.info/arcgis/rest/services/OSIP_2018

The Institute for Natural Resources (INR) at Oregon State University (OSU) worked with the OSU Extension Fire Program (OSU Extension) from March – June 2020 to compile and synthesize the best available data and information on the distribution of values at risk (VAR) of wildfire in Oregon. This documentation contains information about each of these.For information on classification and data processing see: https://oe.oregonexplorer.info/externalcontent/valuesatrisk/wildfire_values_at_risk_documentation_INR_june_2020.pdfDocumentation prepared by Megan Creutzburg, Jimmy Kagan, Myrica McCune, and Janine Salwasser.

GRA_ALLOTMENT_POLY: Livestock grazing allotments and associated attributes describing some basic characteristics of the allotments for allotments on BLM lands in Oregon and Washington.

Fire locations from 1992-2020 are from: Short, Karen C. 2022. Spatial wildfire occurrence data for the United States, 1992-2020 [FPA_FOD_20221014]. 6th Edition. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2013-0009.6Fire locations from 2021-2022 were provided by the Oregon Department of Forestry.The attributes of both datasets were simplified for use in the CWPP Planning Tool Advanced Report by the Institute for Natural Resources at Oregon State University. See original datasets for full attributes (https://doi.org/10.2737/RDS-2013-0009.6 and https://oe.oregonexplorer.info/externalcontent/spatialdatafordownload/ODF_2022_Fire_Points.zip ).

This map represents the Oregon City Limit boundaries. Each city limit is defined as a continuous area within the statutory boundary of an incorporated city, which is the smallest subdivision of an annexed area, as of 2009.

An incorporated city may have multiple areas that are not contiguous. Each such area is represented separately with its own polygon (boundary on map).

Metadata https://spatialdata.oregonexplorer.info/geoportal/details;id=fc688695127e4cb9b59d800657b2d600 Download http://navigator.state.or.us/sdl/data/shapefile/k24/citylim_2009.zip

This data layer is an element of the Oregon GIS Framework. This digital, geographically referenced one-meter resolution color Digital Orthophoto Quadrangles (DOQ) data set was developed for the Oregon GIS department to provide updated state wide imagery. Digital 4 band ortho imagery covering the state of Oregon was flown in 2016.The 4 Band imagery was rectified and cut into a DOQs. The imagery is provided in the Web Mercator Auxiliary Sphere projection as a tiled service, and in the State Lambert projection as an image service. Using web services to stream imagery: https://imagery.oregonexplorer.info/arcgis/rest/services/NAIP_2016

This data layer is an element of the Oregon GIS Framework. Digital 4 band ortho imagery covering the state of Oregon was flown over the Summer of 2009. Imagery was collected with a Lecia ADS40-SH51 digital camera at a flight height of 19'000 agl. The 4 Band imagery was rectified and cut into a DOQs. The imagery is provided in the Web Mercator Auxiliary Sphere projection as a tiled service, and in the State Lambert projection as an image service. Using web services to stream imagery: https://imagery.oregonexplorer.info/arcgis/rest/services/NAIP_2009

This data layer is an element of the Oregon GIS Framework. The purpose is to provide a seamless raster image for Oregon of the 2000 one-meter orthoimagery. This data depicts physical features on the surface of the earth. It has been constructed to be used for online access. Digital orthoimages serve a variety of purposes, from interim maps to field references for earth science investigations and analysis. The imagery (or extracts from it) may be useful as a layer of a geographic information system and as a tool for revision of digital line graphs and topographic maps. Orthophotos combine the image characteristics of a photograph with the geometric qualities of a map. The primary digital orthophotoquad (DOQ) is a 1-meter ground resolution, quarter-quadrangle (3.75-minutes of latitude by 3.75-minutes of longitude) image cast on the Universal Transverse Mercator Projection (UTM) on the North American Datum of 1983 (NAD83).The geographic extent of the DOQ is equivalent to a quarter-quad plus The overedge ranges a minimum of 50 meters to a maximum of 300 meters beyond the extremes of the primary and secondary corner points. The overedge is included to facilitate tonal matching for mosaicking and for the placement of the NAD83 and secondary datum corner ticks. The normal orientation of data is by lines (rows) and samples (columns). Each line contains a series of pixels ordered from west to east with the order of the lines from north to south. The standard, archived digital orthophoto is formatted as four ASCII header records, followed by a series of 8-bit binary image data records. The radiometric image brightness values are stored as 256 gray levels ranging from 0 to 255. The imagery is provided in the Web Mercator Auxiliary Sphere projection as a tiled service, and in the State Lambert projection as an image service. Using web services to stream imagery: https://imagery.oregonexplorer.info/arcgis/rest/services/NAIP_2000