This data layer is an element of the Oregon GIS Framework. The Oregon Wetlands Database (2019) is a geodatabase consisting of three feature classes: 1) Local Wetland Inventory (LWI) Wetlands, 2) National Wetland Inventory (NWI) Wetlands, and 3) More Oregon Wetlands (MOW). Each feature class contains polygons representing wetland boundaries. The three feature classes originated from different sources with distinct purposes, methodologies and time frames for generating geospatial wetlands data, and there is overlap among them; however, all are relevant to the conservation and management of wetlands across the state of Oregon. See the metadata of the individual feature classes for more background information and details per dataset.

This data layer is an element of the Oregon GIS Framework. Seed zones for Alaska Yellow Cedar, Cottonwood, Douglas Fir, Engelmann Spruce, Grand Fir, Incense Cedar, Jeffrey Pine, Lodgepole Pine, Noble Fir, Pacific Silver Fir, Pacific Yew, Ponderosa Pine, Port Orford Cedar, Red Alder, Sitka Spruce, Sugar Pine, Western Hemlock, Western Red Cedar, Western White Pine, and basic zones for other species in Oregon. Zones are based on genetic variation patterns obtained by evaluating genotypes of trees from locations in the region. Wherever possible, the zone lines follow natural boundaries such as crests of mountain ranges, ridge tops, rivers -or physical boundaries, such as highways and railroads, since it would be impossible for cone collectors to recognize any other type of boundary.

This data layer is an element of the Oregon GIS Framework. The Oregon Wetlands Database (2019) is a geodatabase consisting of three feature classes: 1) Local Wetland Inventory (LWI) Wetlands, 2) National Wetland Inventory (NWI) Wetlands, and 3) More Oregon Wetlands (MOW). Each feature class contains polygons representing wetland boundaries. The three feature classes originated from different sources with distinct purposes, methodologies and time frames for generating geospatial wetlands data, and there is overlap among them; however, all are relevant to the conservation and management of wetlands across the state of Oregon. See the metadata of the individual feature classes for more background information and details per dataset.

This data layer is an element of the Oregon GIS Framework. The Oregon Wetlands Database (2019) is a geodatabase consisting of three feature classes: 1) Local Wetland Inventory (LWI) Wetlands, 2) National Wetland Inventory (NWI) Wetlands, and 3) More Oregon Wetlands (MOW). Each feature class contains polygons representing wetland boundaries. The three feature classes originated from different sources with distinct purposes, methodologies and time frames for generating geospatial wetlands data, and there is overlap among them; however, all are relevant to the conservation and management of wetlands across the state of Oregon. See the metadata of the individual feature classes for more background information and details per dataset.

This data layer is an element of the Oregon GIS Framework. The Oregon Wetlands Database (2019) is a geodatabase consisting of three feature classes: 1) Local Wetland Inventory (LWI) Wetlands, 2) National Wetland Inventory (NWI) Wetlands, and 3) More Oregon Wetlands (MOW). Each feature class contains polygons representing wetland boundaries. The three feature classes originated from different sources with distinct purposes, methodologies and time frames for generating geospatial wetlands data, and there is overlap among them; however, all are relevant to the conservation and management of wetlands across the state of Oregon. See the metadata of the individual feature classes for more background information and details per dataset.

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This data layer is an element of the Oregon GIS Framework. This data layer represents the Existing Vegetation data element. This statewide grid was created by combining four independently-generated datasets: one for western Oregon (USGS zones 2 and 7), and two for eastern Oregon (USGS zones 8 and 9; forested and non-forested lands), and selected wetland types from the Oregon Wetlands geodatabase. The landcover grid for zones 2 and 7 was produced using a modification of Breiman's Random Forest classifier to model landcover. Multi-season satellite imagery (Landsat ETM+, 1999-2003) and digital elevation model (DEM) derived datasets (e.g. elevation, landform, aspect, etc.) were utilized to build two predictive models for the forested landcover classes, and the nonforested landcover classes. The grids resulting from the models were then modified to improve the distribution of the following classes: volcanic systems and wetland vegetation. Along the eastern edge, the sagebrush systems were modified to help match with the map for the adjacent region. Additional classes were then layered on top of the modified models from other sources. These include disturbed classes (harvested and burned), cliffs, riparian, and NLCD's developed, agriculture, and water classes. A validation for forest classes was performed on a withheld of the sample data to assess model performance. Due to data limitations, the nonforest classes were evaluated using the same data that were used to build the original nonforest model. Two independent grids were combined to map landcover in adjacent zones 8 and 9. Tree canopy greater than 10% (from NLCD 2001), complemented with a disturbance grid, served as a mask to delineate forested areas. A grid of non-forested areas was extracted from a larger, regional grid (Sagemap) created using decision tree classifier and other techniques. Multi-season satellite imagery (Landsat ETM+, 1999-2003) and digital elevation model (DEM) derived datasets (e.g. elevation, landform, aspect, etc.) were utilized to derive rule sets for the various landcover classes. Eleven mapping areas, each characterized by similar ecological and spectral characteristics, were modeled independently of one another and mosaicked. An internal validation for modeled classes was performed on a withheld 20% of the sample data to assess model performance. The portion of this original grid corresponding to USGS map zones 8 and 9 was extracted and split into three mapping areas (one for USGS zone 8, two for USGS zone 9: Northern Basin and Range in the south, Blue Mountains in the north) and modified to improve the distribution of the following classes: cliffs, subalpine zone, dunes, lava flows, silver sagebrush, ash beds, playas, scabland, and riparian vegetation. Agriculture and urban areas were extracted from NLCD 2001. A forest grid was generated using Gradient Nearest Neighbor (GNN) imputation process. GNN uses multivariate gradient modeling to integrate data from regional grids of field plots with satellite imagery and mapped environmental data. A suite of fine-scale plot variables is imputed to each pixel in a digital map, and regional maps can be created for most of the same vegetation attributes available from the field plots. However, due to lack of sampling plots in the southern half of zone 9, the GNN model proved unreliable there; forest data from Landfire were used instead. To compensate for known under-representation of wetlands, selected wetland types from the Oregon Wetlands Geodatabase (version 2009-1030) were converted to raster and overlaid (replaced) pixel value assignments from the previous steps just detailed. See Process Steps for more information. The ecological systems were crosswalked to landcover (based on Oregon landcover standard, modified from NLCD 2001) and to wildlife habitats (based on integrated habitats used in the Oreg