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The evacuation zones are the local and distant tsunami scenarios shown on the tsunami evacuation brochures which can be found on the Oregon Tsunami Clearinghouse web site: www.oregontsunami.org
The local tsunami evacuation zone is equal to the XXL tsunami scenario. The distant tsunami evacuation zone is equal to the AKMax tsunami scenario. DOGAMI modeled 7 tsunami scenarios altogether; 5 local tsunami events (S, M, L, XL, and XXL) and 2 distant tsunami events (AK64 and AKMax). These are the worst case scenarios for a local and distant earthquake/tsunami event. These polygons represent the evacuation zones for the entire Oregon coast.
All 7 tsunami scenarios, along with a text report and other supplemental files, can be found in DOGAMI publication: OFR O-13-19, Summary of Tsunami Hazard Data for Oregon.
This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the United States and its Territories. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979). The National Wetlands Inventory - Version 2, Surface Waters and Wetlands Inventory was derived by retaining the wetland and deepwater polygons that compose the NWI digital wetlands spatial data layer and reintroducing any linear wetland or surface water features that were orphaned from the original NWI hard copy maps by converting them to narrow polygonal features. Additionally, the data are supplemented with hydrography data, buffered to become polygonal features, as a secondary source for any single-line stream features not mapped by the NWI and to complete segmented connections. Wetland mapping conducted in WA, OR, CA, NV and ID after 2012 and most other projects mapped after 2015 were mapped to include all surface water features and are not derived data. The linear hydrography dataset used to derive Version 2 was the U.S. Geological Survey's National Hydrography Dataset (NHD). Specific information on the NHD version used to derive Version 2 and where Version 2 was mapped can be found in the 'comments' field of the Wetlands_Project_Metadata feature class. Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery. By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps. This dataset should be used in conjunction with the Wetlands_Project_Metadata layer, which contains project specific wetlands mapping procedures and information on dates, scales and emulsion of imagery used to map the wetlands within specific project boundaries.
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 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 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). Urban growth boundaries (UGBs) are lines drawn on planning and zoning maps to show where a city expects to experience growth for the next 20 years. UGBs were established under Oregon Statewide Planning Goals in 1973 by the Oregon State Legislature (Senate Bill 100). Goal 14 specifically deals with UGBs (OAR 660-15-0000(4)). Other specific ORS that relate to the designation and delineation of UGBs are: 197.626 Expanding urban growth boundary and designating urban reserve area subject to periodic review. A city with a population of 2,500 or more within its urban growth boundary that amends the urban growth boundary to include more than 50 acres or that designates urban reserve areas under ORS 195.145 shall submit the amendment or designation to the Land Conservation and Development Commission in the manner provided for periodic review under ORS 197.628 to 197.650. [1999 c.622 §14; 2001 c.672 §10] and 197.628 Periodic review; policy; conditions that indicate need for periodic review.(1) It is the policy of the State of Oregon to require the periodic review of comprehensive plans and land use regulations in order to respond to changes in local, regional and state conditions to ensure that the plans and regulations remain in compliance with the statewide planning goals adopted pursuant to ORS 197.230, and to ensure that the plans and regulations make adequate provision for needed housing, employment, transportation and public facilities and services. Determining UGBs in Oregon is done based on input from city and county governments. Such special districts as public safety and utilities also participate because they provide important services. Local citizens and other interested people also provide input at public hearings, and by voting. After local governments determine the UGB, they submit a Post Acknowledgement Plan Amendment and the state Department of Land Conservation and Development (DLCD) reviews it for consistency with Goal 14. As part of this process jurisdictions send GIS files to DLCD highlighting the amended area. UGBs that are currently in the appeal process at the time of publication are not included. The effDate attribute is populated to indicate the data version and year in which the UGB was updated. UGB amendments are verified with DLCD’s Post Acknowledgement Plan Amendment (PAPA) database to ensure that all UGB updates reported to DLCD have been included in this data. In 2019 DLCD acknowledged amendments to the following UGBs: Madras, Mill City, Redmond, Springfield and Stanfield.
The roads found in this dataset were digitized by using a combination of aerial photos (mostly NAIP 2012) and LiDAR, where available. The roads were placed as best as possible to the center of the road based on each of these underlying data sources. Roads were attirbuted with Functional Classifications based on local Transportation System Plans (TSP) when available. The functional classes were then grouped together to aid in their display on Clatsop County WebMaps and for easier use in cartographic representation (i.e. symbology).
The roads found in this dataset were digitized by using a combination of aerial photos (mostly NAIP 2012) and LiDAR, where available. The roads were placed as best as possible to the center of the road based on each of these underlying data sources. Roads were attirbuted with Functional Classifications based on local Transportation System Plans (TSP) when available. The functional classes were then grouped together to aid in their display on Clatsop County WebMaps and for easier use in cartographic representation (i.e. symbology).
The roads found in this dataset were digitized by using a combination of aerial photos (mostly NAIP 2012) and LiDAR, where available. The roads were placed as best as possible to the center of the road based on each of these underlying data sources. Roads were attirbuted with Functional Classifications based on local Transportation System Plans (TSP) when available. The functional classes were then grouped together to aid in their display on Clatsop County WebMaps and for easier use in cartographic representation (i.e. symbology).
The roads found in this dataset were digitized by using a combination of aerial photos (mostly NAIP 2012) and LiDAR, where available. The roads were placed as best as possible to the center of the road based on each of these underlying data sources. Roads were attirbuted with Functional Classifications based on local Transportation System Plans (TSP) when available. The functional classes were then grouped together to aid in their display on Clatsop County WebMaps and for easier use in cartographic representation (i.e. symbology).