Ecological Systems

Metadata also available as

Metadata:


Identification_Information:
Citation:
Citation_Information:
Originator: ORNHIC
Originator: Forest Sciences Lab, OSU
Publication_Date: 20100823
Title: Ecological Systems
Edition: version 1.0
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: \\tsclient\S\sdl\bioscience\orveg\orveg10
Larger_Work_Citation:
Citation_Information:
Description:
Abstract:
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 Oregon, Washington, and Idaho Dept of Fish & Wildlife conservation strategies). These codes and names are included in the value attribute table provided with the ecological systems grid.
Purpose:
The digital landcover dataset may be used for various purposes with user's discretion. Specifically, this dataset was created for use in Northwest ReGap. These data are not intended to be used at scales larger than 1:100,000.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 1999-2003
Currentness_Reference: ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -125.993468
East_Bounding_Coordinate: -115.422619
North_Bounding_Coordinate: 46.607493
South_Bounding_Coordinate: 41.612976
Keywords:
Theme:
Theme_Keyword_Thesaurus: none
Theme_Keyword: landcover
Theme_Keyword: vegetation cover
Theme_Keyword: ecological system
Place:
Place_Keyword_Thesaurus: none
Place_Keyword: Oregon
Place_Keyword: Intermountain West
Access_Constraints: none
Use_Constraints:
Appropriate scale for these data is 1: 100,000 smaller. The user assumes responsibility when using this dataset.
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Jimmy Kagan
Contact_Organization: Oregon Biodiversity Information Center (ORBIC)
Contact_Position: Director
Contact_Address:
Address_Type: mailing address
Address: 1322 SE Morrison
City: Portland
State_or_Province: Oregon
Postal_Code: 97214
Country: USA
Contact_Voice_Telephone: 503-725-9955
Contact_Electronic_Mail_Address: jkagan@pdx.edu
Data_Set_Credit:
Jimmy Kagan Oregon Natural Heritage Information Center 1322 SE Morrison Street, Portland, OR 97214-2423
Eric Nielsen Oregon Natural Heritage Information Center 1322 SE Morrison Street, Portland, OR 97214-2423
Claudine Tobalske Oregon Natural Heritage Information Center 1322 SE Morrison Street, Portland, OR 97214-2423
Janet Ohmann Forest Science, Oregon State University 354-1 Forest Sciences Lab Corvallis, OR 97331
Emilie Grossmann Forest Science, Oregon State University 321 Richardson Hall Corvallis, OR 97331-5752
John Bauer The Wetlands Conservancy Tualatin, OR
Matthew Gregory Forest Science, Oregon State University 321 Richardson Hall Corvallis, OR 97331-5752
Jon Hak Natureserve 4001 Discovery Drive Boulder, CO 80303
Steve Hanser USGS, Forest and Rangeland Ecosystem Science Center, Snake River Field Station, 970 Lusk Street, Boise, ID, 83706
Steve Knick USGS, Forest and Rangeland Ecosystem Science Center, Snake River Field Station, 970 Lusk Street, Boise, ID, 83706
Southwest Regional GAP Project RS/GIS Laboratory, College of Natural Resources, UMC 5275, Utah State University, Logan, UT 84322-5275
NatureServe: NatureServe, 2400 Spruce St., Suite 201, Bolder, CO 80302
USGS/EROS Data Center: EROS Data Center, USGS, Sioux Falls, SD 57198
Native_Data_Set_Environment:
Microsoft Windows 2000 Version 5.2 (Build 3790) Service Pack 1; ESRI ArcCatalog 9.3.1.3000

Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
Model validation for the non-forest dataset was performed by testing model accuracy using a 20% withheld portion of the sample data. Model validation for the updates (lava flows, ash beds, playas and riparian vegetation) was performed by testing model accuracy with points not used for model development.
Logical_Consistency_Report: Not applicable for raster data
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator:
United States Geological Survey, EROS Data Center, National Elevation Dataset
Publication_Date: 19990101
Title: 30 Meter Digital Elevation Model
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: <http://ned.usgs.gov/>
Source_Scale_Denominator: 30m pixels
Type_of_Source_Media: digital tape media
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 19990101
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: USGS
Source_Contribution:
A digital elevation model (DEM) obtained from the National Elevation Dataset (NED) in 1999 was used to generate the landform GIS dataset.
Source_Information:
Source_Citation:
Citation_Information:
Originator:
United States Geological Survey, EROS Data Center, Multi-Resolution Land Characteristics Consortium
Publication_Date: 1999-2001
Title: Landsat 7 , ETM+ Imagery
Geospatial_Data_Presentation_Form: remote sensing image
Online_Linkage: <http://www.mrlc.gov/index.asp>
Source_Scale_Denominator: 30m pixels
Type_of_Source_Media: digital tape media
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1999
Ending_Date: 2003
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: USGS
Source_Contribution:
Landsat 7 ETM+ Imagery provided for Spring, Summer and Fall dates between 1999 and 2003
Source_Information:
Source_Citation:
Citation_Information:
Originator: BLM Burns, Lakeview and Vale Districts
Title: ESI data
Other_Citation_Details: Contact Burns: Pam Keller 541-573-4486
Source_Scale_Denominator: 1:24,000
Type_of_Source_Media: Shapefile
Source_Citation_Abbreviation: BLM ESI data
Source_Contribution:
BLM ESI data were obtained from the Burns and lakeview districts.
Source_Information:
Source_Citation:
Citation_Information:
Originator: MRLC Consortium
Publication_Date: 20030901
Title: National Land Cover Dataset, 2001
Edition: 1.0
Geospatial_Data_Presentation_Form: remote-sensing image
Other_Citation_Details:
References: Homer, C., C. Huang, L. Yang, B. Wylie and M. Coan, 2004. Development of a 2001 national land cover database for the United States. Photogrammetric Engineering and Remote Sensing Vol.70,No.7,pp 829-840 or online at www.mrlc.gov/publications.
Online_Linkage: <http://www.mrlc.gov/mrlc2k_nlcd.asp>
Source_Scale_Denominator: 30m pixels
Type_of_Source_Media: raster grid
Source_Citation_Abbreviation: NLCD 2001
Source_Contribution: Agricultural and urban areas, water.
Source_Information:
Source_Citation:
Citation_Information:
Originator: MRLC Consortium
Publication_Date: 20030901
Title: NLCD 2001 Imperviousness and Tree Canopy Data
Edition: 1.0
Geospatial_Data_Presentation_Form: remote-sensing image
Other_Citation_Details:
Homer, C., C. Huang, L. Yang, B. Wylie and M. Coan, 2004. Development of a 2001 national land cover database for the United States. Photogrammetric Engineering and Remote Sensing. Huang, C., L. Yang, B. Wylie, and C. Homer, 2001. A strategy for estimating tree canopy density using Landsat 7 ETM+ and high resolution images over large areas. In: Third International Conference on Geospatial Information in Agriculture and Forestry; November 5-7, 2001; Denver, Colorado. CD-ROM, 1 disk.
Online_Linkage: <http://www.mrlc.gov>
Source_Scale_Denominator: 30m pixels
Type_of_Source_Media: raster grid
Source_Citation_Abbreviation: NLCD 2001 Imperviousness and Tree Canopy Data
Source_Contribution: Used to generate a mask of forested areas.
Source_Information:
Source_Citation:
Citation_Information:
Originator: USGS
Publication_Date: Sept 2006
Title:
The National Map LANDFIRE: LANDFIRE National Existing Vegetation Type layer
Geospatial_Data_Presentation_Form: raster digital data
Other_Citation_Details:
Metadata: <http://extract.cr.usgs.gov/distmeta/servlet/gov.usgs.edc.MetaBuilder?TYPE=html&DATASET=F0I>
Online_Linkage: <http://www.landfire.gov/NationalProductDescriptions21.php>
Source_Scale_Denominator: 30-m pixels
Type_of_Source_Media: raster grid
Source_Citation_Abbreviation: Landfire National Existing Vegetation Type layer
Source_Contribution: Forest ESLF in southern half zone 9
Source_Information:
Source_Citation:
Citation_Information:
Publication_Date: 20100420
Title: Oregon Wetlands Geodatabase
Online_Linkage: <http://www.oregon.gov/DAS/EISPD/GEO/alphalist.shtml#w>
Source_Scale_Denominator: Varies; 1:4800 to 1:60000
Type_of_Source_Media: polygon file geodatabase
Source_Time_Period_of_Content:
Source_Currentness_Reference: 1981 - current
Source_Citation_Abbreviation: Oregon Wetlands Geodatabase, Version 20100420
Source_Contribution:
Oregon Biodiversity Information Center and The Wetlands Conservancy
Process_Step:
Process_Description:
NON-FOREST GRID (SAGEMAP), ZONES 8 AND 9
Introduction: This project was a coordinated multi-institution endeavor. The USGS, Snake River Field Station coordinated activities to assure as much standardization as possible. Detailed documentation on process steps will be posted online at <http://sagemap.wr.usgs.gov> and included with individual mapping area datasets as they become available. The following provides a brief outline of the process steps.
1) Mapping area delineation: The Columbia Basin Region (Idaho, Oregon, and Washington) was divided into 11 ecologically and spectrally similar mapping areas. Bailey's (1995) and Omernik's (1987) ecoregions, Landsat TM imagery and existing landcover maps were used as a backdrop for digitizing boundary lines. Columbia Basin mapping area boundaries were matched with the SWGAP mapping areas across the Oregon/Idaho and Utah/Nevada borders and extended 50km into the SWGAP regional boundary in order to utilize SWGAP training data and facilitate edge matching. The responsibility for mapping was split with the USGS-Snake River field Station mapping the Idaho mapping areas with exception of the Owyhee mapping area and the Oregon Natural Heritage Program mapping Oregon and Washington.
2) Predictor layer preparation: Landsat 7 ETM+ images were selected from 1999-2003 for three seasons: spring, summer and fall. Scenes were selected for optimal representation of seasonal phenology, and minimal cloud cover. Landsat scenes were standardized using the MRLC 2001 Preprocessing Procedure and mosaicked for each mapping area. Thirty-meter digital elevation data, provided by the National Elevation Dataset (1999) were mosaicked for the region and subset for each mapping area. The digital elevation data was used to derive attributes such as aspect and landform for each mapping area. Each mapping area had a 2 km overlap with the adjacent mapping area, providing an overall 4 km overlap region between mapping areas.
3) Training sample collection: Approximately 128,000 samples were used for the 3-state region. Field surveys were conducted during the 2002 and 2003 field seasons and involved ocular estimates of biotic and abiotic characteristics, which were recorded on a field form, and subsequently entered into a database. Percent cover of dominant species for Trees, Shrubs, Grasses and Forbs were recorded, as were physical data such as elevation, slope and aspect. A GPS coordinate pair and a polygon was digitized using a laptop computer with TM imagery as a backdrop to record the location of each sample site. A cost analysis was performed by NatureServe to help maximize the sampling effort. A combination of distance to road and landcover composition from previous land cover maps was used to identify regions that were most efficient for data collection. Crews traveled to the regions identified by the cost model and then traversed all navigable roads in the area and opportunistically selected samples based on appropriate size and composition (representative) of stands. Samples were also obtained from other projects, from imagery, DOQ or aerial photo interpretation. In many of the mapping areas the additional data was primary source of data. Each sample location was assigned an appropriate landcover label. Natural and semi-natural vegetation classes were assigned a label based on the Ecological System concept developed by NatureServe.
4) Landcover modeling: The majority of natural and semi-natural landcover classes were modeled using a decision tree classifier. This was done using a custom interface for ERDAS Imagine (developed under contract by Earthsat, Corp. for USGS Eros Data Center) that facilitated the integration of the spatial modeling capabilities of Imagine with the decision tree/data mining capabilities of the See5 software (www.rulequest.com). Approximately 20 sub-samples were randomly selected from each sample site polygon, and were used as separate replicates within the decision tree classifier. These sub-samples were 'drilled' through the predictor layers to obtain training information for the decision tree classifier. The decision tree classifier was run using the See5 software with subsequent generation of decision tree 'ruleset'. The rules were then spatially applied to create a GIS dataset in *.img format. Choice of optimal predictor layers for each model was determined iteratively, through examination of the spatial output of the models and results of the model validation error matrices. In Oregon and Washington, an additional modeling step (Jennings et al. 2004) was used by the Oregon Natural Heritage Program to model shrub cover for each map zone in order to separate shrubland and steppe communities. Some landcover types were not mapped using the decision tree classifier (e.g. burn scars, water bodies, developed and agricultural areas, etc.). These classes were mapped using other techniques such as localized unsupervised classification or screen digitizing.
5) Model validation: Decision tree models were validated by generating initial models using 80% of available samples, while withholding 20% of samples. Withheld samples were randomly selected and stratified by cover class (i.e. proportion of withheld samples per cover class was the same for both the training set and the validation set). Withheld sample polygons were intersected through the spatially applied decision rules (i.e. landcover map) to create an error matrix, presenting users, producers and overall accuracies. The kappa statistic was also calculated for the error matrix. This validation approach does not explicitly present an accuracy of the map. This approach only provides a measure of the ability of the decision tree model to 'predict' landcover in geographic regions where samples were not used, and. Also of importance, for some classes that were modeled with the decision tree classifier, the number of withheld samples was small. Additionally, a small number of classes were not mapped using the decision tree classifier due to the relative rarity of occurrence.
6) Map refinement (by mapping area): The objective of the project was to produce the best map possible. Therefore, the next step was to generate a final decision tree model using 100% of the available sample data. This resulted in a GIS dataset (*.img format) containing all the modeled landcover classes. This dataset was generalized to the minimum mapping unit (MMU) of 1 acre using Imagine's CLUMP utility (4 connected neighboring pixels) and then Imagine's ELIMINATE utility with a minimum clump of pixels set to approximately 1 acre (5 pixels). The non-modeled landcover classes (e.g. developed, agriculture, water, etc.) were then superimposed over the generalized modeled landcover classes using a conditional statement with Imagine's graphical modeler.
7) Regional mosaic: Using the 4 km overlap region between mapping areas a cutline was used to edge-match adjacent mapping areas where landcover discontinuities resulted from the modeling process although the majority of the overlapping areas were consistent. The Columbia Basin region (ID, OR, and WA) and the Southwest Regional Gap Landcover Dataset were then mosaicked -utilizing a cutline and the 50km overlap between the regions.
8) Data formatting for distribution: The landcover modeling resulted in a final unsigned 16 bit *.img file. To make the data more practical for distribution, the 16 bit image was converted to ArcInfo grid format.
This grid will be referred to as the "original grid" in Process Step 2.
Process_Date: 200509
Process_Step:
Process_Description:
NON-FOREST GRID, MODIFICATIONS, ZONES 8 AND 9
The original grid was split into three mapping areas: south (corresponding to USGS zone 9 and the Northern Basin and Range ecoregion), center (USGS zone 9 and Blue Mountains ecoregion), and north (USGS zone 8). It was modified for the following vegetation classes, either as a whole or within each mapping area.
1) Cliff and canyons.
The NLCD 2001 canopy raster was used to generate a forest mask, with forest defined as canopy greater than 10% canopy cover. It was complemented with Warren Cohen's 1972-1995 Western Oregon Stand Replacement Disturbance Map. Boundaries were smoothed using the ArcGIS Clean Boundary tool. Patches of pixels were individualized with a Regiongroup command, and patches smaller than 10,000 pixels (900 ha) were removed (in essence, small forest patches were reclassified as non-forest, and vice-versa). Slope greater or equal to 50% were computed within resulting forested areas; in non-forest areas slopes greater or equal to 40 degrees were computed. These two slope grids were merged.
The 30-m DEM was used to extract elevations >= 2500m. Pixels corresponding to that criterion were reclassified as Rocky Mountain Alpine Bedrock and Scree. In the Blue Mountains ecoregion, forested pixels were reclassified to Rocky Mountain Cliff, Canyon and Massive Bedrock. All other landform/slope pixels were classified as Inter-Mountain Basins Cliff and Canyon.
2) Subalpine zone. The DEM was used to select areas higher than 2300 m. Jimmy Kagan examined the vegetation and land cover types and suggested reclassification values where needed.
3) Dunes In the southern mapping zone (Northern Basin and Range ecoregion), sandy soil polygons from SSURGO were used as proxis for dunes in Lakeview and Harney counties. In the Christmas Valley of Oregon, Jimmy Kagan refined Oregon's 2002 Gap Analysis dune polygon using vegetation attributes of the Lakeview BLM district's ESI data. The shapefiles were converted to grids.
4) Lava flows. Lava flows were only modeled in the southern mapping area (Northern Basin and Range ecoregion). Polygons labeled as lava were selected from the BLM ESI data (Burns and Lakeview) and from Oregon Gap analysis. The satellite image (Spring reflectance) was displayed in the background and used to refine the contours of the Gap polygons. Fifty points were randomly located inside each polygon using ArcGIS Hawth's Tool, resulting in 450 points. An additional 5000 points were randomly located outside of the lava flow polygons to use as negative points and a CART model was run (using Erdas Imagine and See5). The resulting predicted raster grid of lava flows was modified by removing any clump smaller or equal to 25 pixels in size.
5) Silver sagebrush Polygons of silver sagebrush were extracted from the BLM ESI data (Burns and Lakeview) and from Hart Mountain vegetation data, and converted to a grid. Because silver sagebrush was over-predicted in the original grid, areas not mapped as silver sagebrush by the BLM had to be reclassified. Where elevation was greater than 1830 m (6000'), silver sagebrush was recoded as mountain big sagebrush. Below, a shrub cover model was used to recode silver sagebrush as either big sagebrush steppe (if cover < 25%) or big sagebrush shrubland (if cover >= 25%).
6) Ash beds. In USGS zone 9, Oregon Gap Analysis polygons of ash beds and ORNHIC Element of Occurence polygons for rare plants growing on ash beds were used to identify ash on a satellite image (Spring reflectance). 601 points (in the south mapping area) and 489 points (in the center mapping area) were then haphazardly digitized on pixels with the proper reflectance for ash. A 10-km buffer was applied to these ash points and 5000 additional, negative points were randomly generated outside of the buffer in each mapping area, using ArcGIS Hawth's Tool. A CART model was run for each zone using Erdas Imagine and See5. Post-modeling modifications included removing ash beds in areas higher than 2000 m (were pixels were most likely snow) and in areas mapped as agriculture in the original grid.
7) Playas. A CART model was used to model the distribution of playas in the south and center mapping zones. In the south zone, playa polygon data were extracted from the BLM ESI data and 20 points were randomly placed with each using ArcGIS Hawth's Tool, resulting in 3660 playa points. An additional 10,000 points were randomly generated outside of the BLM playa polygons to use as negatives. In the center zone, 25 existing playas were identified using the Spring reflectance image and digitized on-screen. Twenty points were randomly generated inside each polygon and 5000 outside of the polygons for a total of 500 playa points and 5000 negative points. In both mapping areas, post-modeling processes consisted of removing playa pixels occurring on slopes steeper than 5 degrees, in areas classified as agriculture in the original grid, and manually eliminating obvious misclassifications (such as clouds, cloud shadows and roads). The CART model approach did not work well in USGS zone 9. Instead, known existing playas were identified using the Spring reflectance satellite image and digitized on-screen.
8) Scablands. A CART model was generated for zone 9 and the Blue Mountains (north and center mapping zones). Oregon NAIP imagery was used to visually identify scablands and 530 points were haphazardly digitized on-screen; these were complemented with field samples from Oregon and Washington Sagemap and with known locations of Balsamorhiza rosea. A total of 1912 presence poitns entered the mode. 15,000 seudo-absence points were generated using Hawth's Tool to randomly locate points, removing area within 1km of presence points as well as areas mapped as scablands in the original Sagemap grid.
9) Riparian vegetation. Riparian modeling was completed using a modification of methods previously described by ShrubMap (Process Step 1) in which all the CART models were restricted to within the landscape types directly adjacent to waterways. A total 4376 polygons [Crowe - 2970 (all riparian), ShrubMap - 1275 (null - 1232 and 43 - riparian), WANHP - 121 (all riparian)] where used to represent riparian and non-riparian types. Data points from WANHP were processed by buffering the sample point at 100 meters and clipping the stream arc that occurs with the buffer to define the sample. The Crowe data points were recorded by quarter section centroid and required that they first be processed by snapping the points to the nearest stream within 1000 meters. Points were then buffered at 100 meters and the buffer was used to clip all stream arcs within the buffer. ShrubMap sample points were primarily used to represent the null riparian occurrences and followed similiar methods for extracting stream segments. The riparian model methods used two additional independent predictor variables that are not previously described. The 1:24,000 streams where assembled for the extent of the study area and where supplemented for Idaho, and parts of Washington with 1:100,000 streams where the finer data was not available. All perennial and ephemeral streams were extracted from the overall extent and a distance to streams variable was generated from the subset. Upland land form types that have no direct occurrences of riparian types were masked out of the analysis. Following CART classification the model results were further restricted to regions directly adjacent to all stream types based upon the strahler stream order value (Order-Buffer, 0 or null-90m, 1-30m, 2-60m, 3-90m, 4-90m, 5-120m, 6-180m, 7-300m, 8-390m). The 1:100K streams used for Idaho and portions of Washington were given an null value buffer of 90 meters.
Source_Used_Citation_Abbreviation: z:\LOCALS~1\Temp\xml96.tmp
Process_Date: 20080312
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Jon Hak and Claudine Tobalske
Contact_Organization: ORNHIC
Contact_Voice_Telephone: 503-731-3070
Process_Step:
Process_Description:
FOREST GRID, ZONES 8 AND 9
A forest mask was generated using the NLCD 2001 Canopy Cover grid, selecting pixels with a canopy cover greater than 10%. This grid was complemented with Warren Cohen's 1972-1995 Western Oregon Stand Replacement Disturbance Map and similar data for the northeastern portion of the Blue Mountains (Robert Kennedy, unpubl. data).
1. Zone 8 and northern half of zone 9 (Blue Mountains ecoregion) 1.1. Non-riparian GNN: we developed a relational database containing regional forest inventory plots across all of Oregon and Washington. The plot database is to be used in several mapping projects, including mapping of Ecological Systems for map zones 2 and 7 for GAP. Primary plot data sources are: (1) Most recent periodic inventories of the Forest Inventory and Analysis (FIA) Program, Pacific Northwest Research Station, USDA Forest Service (nonfederal lands), that are currently contained in the FIA Integrated Database (IDB); (2) all intensification and remeasurement plots of the Current Vegetation Survey (R6-CVS), USDA Forest Service, Pacific Northwest Region (on National Forest lands); (3) full intensification of CVS plots installed by the Bureau of Land Management in western Oregon (BLM-CVS). 1.2. Riparian GNN: a GNN model including four riparian ESLF was originally generated (from plots of both riparian and non-riparian forest types), but the non-riparian GNN model describe above was ultimately preferred. However, in the Blue Mountains ecoregion, riparian ESLF were pulled from the riparian GNN model. The buffered stream mask (generated to model riparian in the original non-forest grid) was applied to limit riparian ESLF to the vicinity of streams. The resulting grid of forested riparian ESLF was burned on top of the non-riparian GNN grid.
2. Southern half of zone 9 Because of the lack of sampling points, the GNN model proved unreliable in that portion of zone 9. Instead, forest pixels were assigned to ESLF classes using the Landfire National Land Cover grid. Landfire was preferred to Idaho Gap because the Idaho Gap vegetation cover map was based on older Landsat images. Expert knowledge (J. Kagan) was used to reclass some Landfire ESLF to other classes.
Source_Used_Citation_Abbreviation: z:\LOCALS~1\Temp\xml7.tmp
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Janet Ohmann
Contact_Organization: LEMMA Team
Process_Step:
Process_Description:
ZONES 2 AND 7
This grid 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 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 GAP 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.
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Emilie Grossmann
Contact_Organization: LEMMA team
Process_Step:
Process_Description: The three grids were merged and clipped to the state of Oregon.
Source_Used_Citation_Abbreviation: z:\LOCALS~1\Temp\xml1E.tmp
Process_Step:
Process_Description:
Wetland Updates: The Oregon Wetlands Geodatabase was used to derive values for known under-represented landcover types. For most of Oregon, the Oregon Wetlands Geodatabase primarily consists of polygons from the National Wetland Inventory. The Cowardin classification codes were parsed and crosswalked to ESLF codes, using ancillary information such as ecoregion, elevation, soils (NRCS), and hydrography (primarily from National Hydrography Database). Updates to the GAP landcover were done only for select wetland types, and not for riparian areas. This update resulted in 6 wetland ESLF classes for the state of Oregon that were not in the previous Oregon GAP map.
The process replaced existing GAP landcover assignments with selected wetland types discussed above. Several known limitations: 1) For various reasons, polygons classified as "Westside Freshwater Marsh" were not included, likely resulting in an underestimation of their extent in western Oregon. 2) Queries were not available at the time to distinguish "9222 Arid Land Marsh (Freshwater)" from "9297 Alkaline Wetland". The former (9222) was chosen , resulting in a possible over-estimation of Arid Land Marsh and an under-estimation of Alkaline Wetland type. 3) The updating process: Pixels that were assigned a wetland cover type in the 2008 GAP landcover, and whose area was *not* designated a 'wetland' in the Oregon Wetlands Geodatabase, remain unchanged in this version. This results in an additive effect and a possible over-estimation of certain wetland cover types, wherever the original 2008 GAP landcover misclassified a pixel as 'wetland'. However, the Oregon Wetlands Geodatabase is not complete, and has known omissions, and some of the original wetland assignments may have identified areas that are not present in the Oregon Wetlands Geodatabase. No estimate was made of the possible over-estimation of certain types, but a cursory examination suggests that one wetland landcover type ("3179 Playa") may be over-represented in this version.
Source_Used_Citation_Abbreviation: Oregon Wetlands Geodatabase
Process_Date: 20100420
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: John Bauer
Contact_Organization: The Wetlands Conservancy
Contact_Position: GIS Analyst
Contact_Electronic_Mail_Address: john.bauer@wetlandsconservancy.org
Process_Step:
Process_Description:
The GAP map was also updated with two disjunct populations of white fir in eastern Oregon, one in Hart Mountain National Antelope Refuge and one in Steens Mountain National Recreation Area.
Process_Date: 20100420
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Matt Noone
Contact_Organization: Institute for Natural Resources
Contact_Electronic_Mail_Address: matt.noone@oregonstate.edu

Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Grid Cell
Row_Count: 18067
Column_Count: 27049
Vertical_Count: 1

Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Map_Projection:
Map_Projection_Name: Lambert Conformal Conic
Lambert_Conformal_Conic:
Standard_Parallel: 43.000000
Standard_Parallel: 45.500000
Longitude_of_Central_Meridian: -120.500000
Latitude_of_Projection_Origin: 41.750000
False_Easting: 1312335.958005
False_Northing: 0.000000
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Coordinate_Representation:
Abscissa_Resolution: 98.425197
Ordinate_Resolution: 98.425197
Planar_Distance_Units: international feet
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137.000000
Denominator_of_Flattening_Ratio: 298.257222

Entity_and_Attribute_Information:
Detailed_Description:
Entity_Type:
Entity_Type_Label: orveg10.vat
Attribute:
Attribute_Label: LCNAME
Attribute_Definition: Internal feature number.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: DISPLAY
Attribute_Definition: Internal feature number.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: GAPNAME
Attribute_Definition: Internal feature number.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: LC_CODE
Attribute_Definition: Internal feature number.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: VALUE
Attribute_Definition:
A unique value for each pixel class. This value does not correspond to a specific classification scheme.
Attribute_Definition_Source: N/A
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: Count
Attribute_Definition: Number of cells/pixels for each class.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain: Numbers that are automatically generated.
Attribute:
Attribute_Label: COUNT
Attribute_Definition: Internal feature number.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: GAP_ESLF
Attribute_Definition: Internal feature number.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: OR_ESLF
Attribute_Definition: Internal feature number.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: OR_NAMES
Attribute_Definition: Internal feature number.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: HABNAME
Attribute_Definition: Internal feature number.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: HABCODE
Attribute_Definition: Internal feature number.
Attribute_Definition_Source: ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Overview_Description:
Entity_and_Attribute_Overview:
The following fields are present in the dataset:
VALUE: unique identifier COUNT/HISTOGRAM: number of cells/pixels for each class GAPCODE: NatureServe's Ecological System Code, used by Northwest ReGap ORCODE: NatureServe's Ecological System Code, modified for Oregon OR_NAMES: text description of ORCODE. GAP_NAMES: text descriptin of GAPCODE. DISPLAY: concatenation of ORCODE and OR_NAMES, for display using the layer file oregon08_eslf.lyr.
Complete descriptions of each landcover class are available online, by entering the text description in <http://www.natureserve.org/explorer/servlet/NatureServe>.
Entity_and_Attribute_Detail_Citation:
NatureServe. 2005. International Ecological Classification Standard: Terrestrial Ecological Classifications. NatureServe Central Databases. Arlington, VA. U.S.A. Data current as of 20 September 2005.

Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: ORNHIC
Contact_Address:
Address_Type: mailing address
Address: 970 Lusk St
City: Boise
State_or_Province: Idaho
Postal_Code: 83706
Country: U.S.A.
Contact_Voice_Telephone: 503-731-3070 x 111
Contact_Electronic_Mail_Address: jimmy.kagan@oregonstate.edu
Resource_Description: Oregon landcover grid
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: ArcInfo GRID format (ESRI)
Format_Version_Number: Workstation ArcInfo 8.0.2
File_Decompression_Technique: Compression type *.zip. For windows use WinZip.
Transfer_Size: 133.361
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Fees: none

Metadata_Reference_Information:
Metadata_Date: 20110202
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Jimmy Kagan
Contact_Organization: ORNHIC
Contact_Position: Director
Contact_Address:
Address_Type: mailing and physical address
Address: 1322 SE Morrison Street
City: Portland
State_or_Province: Oregon
Postal_Code: 97214
Country: U.S.A.
Contact_Voice_Telephone: 503-731-3070 x 111
Contact_Electronic_Mail_Address: jimmy.kagan@oregonstate.edu
Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
Metadata_Time_Convention: local time
Metadata_Access_Constraints: none
Metadata_Use_Constraints: none
Metadata_Security_Information:
Metadata_Security_Classification_System: none
Metadata_Security_Classification: unclassified
Metadata_Security_Handling_Description: none
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile
Metadata_Extensions:
Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
Profile_Name: ESRI Metadata Profile

Generated by mp version 2.9.6 on Wed Feb 02 11:21:39 2011