Forest Stewardship Spatial Analysis Project
Methodology Report for West Virginia
March 2006
Contact Info:
Dan Kincaid
Assistant State Forester
WV Division of Forestry
1900 Kanawha Blvd., East
Charleston, WV 25305-0180
(304)558-2788
dkincaid@wvforestry.com
Shawn Grushecky
Assistant Director- Appalachian Hardwood Center
West Virginia University
Division of Forestry and Natural Resources
PO Box 6125
Morgantown, WV 26506-6125
304-293-2941 ext. 2413
sgrushec@wvu.edu
Dave McGill
Extension Specialist
Forest Resource Management
West Virginia University
Division of Forestry and Natural Resources
PO Box 6125
Morgantown, WV 26506-6125
304-293-2941 ext. 2474
dmcgill@wvu.edu
Steve Harouff
GIS Analyst- Appalachian Hardwood Center
West Virginia University
Division of Forestry and Natural Resources
PO Box 6125
Morgantown, WV 26506-6125
304-293-2941 ext. 2451
Steve.harouff@mail.wvu.edu
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Executive Summary:
The National Forest Stewardship Program (FSP) Spatial Analysis Project (SAP) was developed to evaluate the
impact the FSP has had since inception and to identify areas where future FSP efforts should be concentrated.
Using GIS the SAP focuses on two main objectives: a suitability analysis using 13 statewide layers weighted by
rankings from the WV Stewardship committee and a historical spatial database of nearly 4,000 current
stewardship plan properties so that current Stewardship efforts to date can be assessed.
The data collection process for nearly 4000 WV Stewardship plans began in the summer of 2004 and final
analysis was completed in January of 2006. Collecting and digitizing FSP plan maps was the critical component
of this analyses and required the majority of the time and effort devoted to this project. Of the FSP plans
collected from state offices, 3,903 were digitized and used in the final analyses. The remaining plans were not
able to be digitized as maps were not available or too poorly drawn to be located.
Analysis Results:
Stewardship Capable Lands for West Virginia:
Approximately 13.2 million acres of land in West Virginia are capable of being considered for the Forest
Stewardship program
Nearly 11.5 million acres of total capable lands are forested
Existing Stewardship plan acres total 634,694 acres which is roughly 4.81% of total capable lands in
West Virginia
Stewardship Potential in West Virginia:
Within the 13.2 million acres of Stewardship capable lands 47.2% are considered high stewardship
potential. This is roughly 6.2 million acres and based on the13 weighted suitability analysis layers
38.4% have medium stewardship potential representing 5.1 million acres
14.42% would be considered low stewardship potential at roughly 1.9 million acres
Discussion:
West Virginia’s 15.5 million acres of land area, which includes 1.3 million acres of public lands not considered
for stewardship, has a very high percentage of Stewardship Capable Lands (Figure 1). When public lands are
removed, approximately 90% of West Virginia’s total land area would be considered as having Stewardship
potential for both forested and non-forested lands. Currently 4.8% of this area is under stewardship, leaving
enormous potential for growth of the FSP program in WV. Current stewardship lands are spread fairly evenly
ranging from 4.1% - 5.0% when looking at the high, medium and low potential lands. Roughly 5.0% of high
stewardship capable lands are currently under the Forest Stewardship program. These results indicate that West
Virginia could focus the FSP on critical areas, especially in the southern region of the state.
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Figure 1: Final Analysis Map #1- Potential for Forest Stewardship Program Benefits for West Virginia
Part 1. Suitability Analysis
The SAP statewide suitability analysis is comprised of the 13 common data layers as well as an analysis mask
layer which will be discussed in further detail.
Factors of Influence and Datalayer Development:
The four pilot states decided upon 12 factors that play a key role in influencing the suitability of land for Forests
Stewardship. West Virginia also added a 13th layer; growth-drain of timber resources. They were evaluated on 2
basic qualities; Threat to Resources and Resource Potential.
Factors posing Threats to Resource Conservation:
Wildfire Assessment
Risk of Insects/Pests
Risk of Development (change in census block households)
Factors with Resource Potential:
Private Forested Lands
Wetlands
Growth-Drain
Forest Patches
Riparian corridors
Threatened & Endangered Species
Proximity to Publicly Protected Lands
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Slopes
Public Water Supply Areas
Priority Watersheds – EPA’s listed 303d impaired waters
The 13 analysis layers were created and collected from statewide agencies or created in-house (Figure 2). The
layers were all converted to a raster grid of 30 meters and each cell was classified as either 1or 0 for either
meeting or not meeting layer presence. Each layer was weighted and combined to determine areas of low,
medium or high stewardship potential. In addition, an analysis mask was developed to exclude areas that were
not suitable for Stewardship. These included open water, urban areas, coal mining permit areas and public
lands. Metadata meeting FGDC standards were created for each analysis layer.
Figure 2: Analysis Layers used for the Suitability analysis
1. Analysis Mask:
Model Builder in ArcGIS was used to create the analysis mask (Figure 3). It is a grid created by classifying
cells meeting the criteria for the analysis mask as NoData (Null cells) while the rest of the grid extent holds
values of 1. The mask is composed of areas of surface water, mining areas, urban, and public lands, all of which
have no stewardship potential. When used as a background layer within the model environment, as well as when
treated as a datalayer, the mask has the effect of excluding cells in any datalayer that coincide with the analysis
mask’s null cells. The analysis mask was the first layer created with model builder, as it serves as the
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environment output extent, snap raster, cell size, and mask for the final analysis maps. A West Virginia state
boundary shapefile was used as the analysis output extent for the analysis mask and the 13 analysis layers. This
will ensure analysis takes place only within state boundaries and that all datalayer grids will line up with each
other during final analysis.
Figure 3: Model Builder Model for Analysis mask
Data layers used for the mask came from surface water and urbanized areas that were queried from the NLCD’s
categories 11, 12, 21, 22, 23 31 and 32 and received a NoData values while all other classes received a value of
1. Public lands and mining permit vector layers were converted to a raster grid and cells were classified
NoData. A weighted overlay combines these areas suitable for stewardship while remaining areas are classified
as NoData resulting in the analysis mask (Grid name = MaskFinal) (Figure 4).
Figure 4: Analysis Mask for West Virginia
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Resource Threats:
2. Wildfire Assessment:
This data layer defines those areas with a high potential for wildland fires in West Virginia. A composite map
from the West Virginia Division of Forestry rating WV counties for wildland fire risk was used as the source for
this fire layer. The county ratings were derived by assigning weights to each county based on four categories;
Hazard, Values, Risk and Protection. Each category was further broken down into sub categories which were
also weighted. Weights for protection and its sub-categories were given negative values to represent a reduction
in the threat of wildfires. All values were added for each county and counties with composite values in the top
three composite rankings were consider for the WV Stewardship (SAP). The composite ranking was converted
to a 30 meter grid and counties falling into top three categories were classified as 1 while remaining counties
were classified as 0 (Final grid name = NewFinalFire).
3. Risk of Insects/Pests:
This datalayer defines areas of West Virginia that have had insect infestations for 3 or more years in the past 10
years. It is derived from separate shapefiles from INTECS International Inc, for the USDA Forest Service, FHP,
FHTET for years 1999-2003. These data were merged to show areas of forest insect pests within West Virginia.
Merged shapefiles were then converted to 30 meter raster. The raster was classified as 0 for no occurrence and 1
for occurrence (Final grid name = FinalPests).
4. Risk of Development (change in census block households):
This data layer defines areas in West Virginia with less than 20% change in the number of households per acre
from 1990 to 2000. West Virginia census data for 1990 and 2000 were provided by Anne Steketee of the USDA
Forest Service. Data included number of housing units per acre for each census block. Percent change in the
number of households over the selected blocks between 1990 and 2000 was calculated for each block. (Note:
The 2000 and 1990 census block group maps were derived from different sources for West Virginia and not all
census blocks were the same polygons and thus did not align. Some blocks were defined as different numbers
and shapes. The relationship table provided by the U.S. Census was used to identify non overlapping census
blocks from 1990 to 2000. The non-matching census blocks were unioned and percent change was calculated
based on 1990 and 2000 unions.) Resulting shapefiles were merged and then converted to 30 meter raster where
cells of less than 20% change were classified as 1 and the rest as 0 (Final grid name = FinalPerChg).
Resource Potential:
5. Private Forested Lands:
This datalayer describes forested land in West Virginia that is not within the extent of the Analysis Mask. Using
the analysis mask as the extent output mask NLCD data was queried for forested values of 41, 42, 43, and 91
and reclassified to 1 and 0 (Final grid name = NewFinalPvt1).
6. Wetlands:
This data layer was provided by the West Virginia Division of Natural Resources and defines areas designated
as wetland soils or as wetland marsh systems. National Wetlands Inventory classes "forested" and "scrub/shrub"
classes were selected from the National Wetlands Inventory dataset then converted to 30 meter GRID format.
The classes were combined to create a statewide single-class layer and classified as 1 or 0 (Final grid name =
NewFinalWet2).
7. Forest Patches:
Model builder was used to create this layer and forest related information in this study was obtained from
MRLC data. The original land cover data set was produced as part of a cooperative project between the USGS
and the USEPA to produce a consistent, land cover data layer for the conterminous US based on 30-meter
Landsat Thematic Mapper (TM) data. National Land Cover Datalayer (NLCD) was developed from TM data
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acquired by the Multi-Resolution Land Characterization (MRLC) Consortium. The Forest Patches Cover layer
was derived from the NLCD layer for West Virginia by agglomerating areas of the following NLCD Land
Cover Classes: Forested Uplands (Deciduous-41, Evergreen-42, and Mixed-43), Wetlands (Woody-91,
Emergent Herbaceous-92).
This forested land however is not truly contiguous land, but rather fragmented into discrete ‘patches’ by roads,
highways and utility right of ways and has a direct effect on the feasibility, or lack thereof, of forest Stewardship
and management of such areas. A further consideration, once patches have been identified, is their size for
effective Stewardship. A patch size of 1000 acres or 4,046,862 m2 (square map units) was determined to be an
appropriate size for a state-wide analysis.
Roads and utility right of ways were used as the primary guide for patch identification. Statewide forested areas
were fragmented into smaller patches using buffered roads and utility right of ways. Orthophotos suggest that
roads and utility right of ways are on average 100ft wide, so a 50ft buffer distance was used on road and utility
vector layers (Figure 5). Buffered vector layers were then converted to raster and
Figure 5: Model builder steps for creating Forest Patches analysis layer
subtracted from the forested areas to create a layer of forest patches. The resulting patches were then classified
by size using the Region Group tool and Zonal Geometry tool. Patches of 1000 acres and higher were then
selected and classified 1/0 to create the final forest patch layer (Final grid name = Patch1000ac
8. Riparian Corridors:
This raster data layer was created by the West Virginia Division of Natural Resources which shows areas in
proximity to streams and open water riverine systems and was derived by buffering selected line and polygon
hydrography features to show 100 meter riparian corridors. The resulting layer was then converted to 30 meter
grid and classified 1/0 (Final grid name = RiparianFinal)
9. Threatened & Endangered Species:
This data layer shows areas in proximity to threatened or endangered species or blocks of land considered as a
unique or important habitat type and were derived from the West Virginia Division of Natural Resources
Natural Heritage Program database. All threatened and endangered species from the WVDNR Natural Heritage
database were selected and buffered 2640 ft. and converted to a 30 meter grid and classified 1/0 (Final grid
name = NewTandEFinal).
10. Proximity to Publicly Protected Lands:
This raster layer defines areas in proximity to Public lands. All public land vector layers were merged and
boundaries were buffered by ½ mile. The resulting vector layer was then converted to a 30 meter grid with an
analysis mask so that only those areas within ½ mile of public lands boundaries were chosen and then classified
1/0 (Final grid name = FinalProximity).
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11. Topographic Slope:
This raster data layer describes areas of West Virginia where slope is more than 5% and less than 40%.
Percentage slope was derived from 30 meter Digital Elevation Model (DEM) raster files using the Spatial
Analyst Slope tool (online source: http://ned.usgs.gov). Resulting grid cells were reclassified 1 for values
between 5-40 and 0 for all remaining values (Final grid name = Slopes5-40).
12. Public Water Supply Sources:
Public water supply vector data layer was provided by the West Virginia Department of Health and Human
Resources which defines point source locations for public drinking water supplies. The vector layer was
buffered by one mile and converted to a 30 meter grid and reclassified 1/0. The public drinking water supply
source datalayer is a restricted dataset and will not be distributed with the SAP deliverables (Final grid name =
FinalPubWater).
13. Priority watersheds:
Priority watersheds for West Virginia was determined using the EPA 303d impaired watershed list (Online
Source: http://www.wvdep.org/item.cfm?ssid=11&ss1id=720). Watersheds listed as impaired at the 12 digit
HUC or subwatershed level within West Virginia were selected as priority watersheds. The vector layer was
converted to a 30 meter grid and 303d impaired 12 digit HUCs were classified as 1 and the remaining as 0 (Final
grid name = PriorityFinal).
14. Growth-Drain:
Growth-Drain of timber resources for West Virginia was determined using the USDA Forest Service Forest
Industry and Analysis data (Online Source: http://www.fia.fs.fed.us/). The ratio of timber resource growth to
timber removal was calculated at the county level. Ratios above 1 represent counties that are growing more
timber than what is harvested. Ratios less than 1 are counties where removal outpaces growth. WV County
vector layer was converted to a 30 meter grid and counties with ratios of 1 or less were classified as 1 and the
rest as 0 (Final grid name = Growthdrain).
The Overlay Model
Model Builder:
ArcGis Model Builder was used for the final overlay model suitability analysis (Figure 6). The Model spatially
combines, by addition, the 13 different datalayers, each weighted according to their importance to overall
Stewardship Potential. After weights are assigned to each layer (see section on data layer weighting process) an
arithmetic overlay was used to combine these 13 layers plus the analysis mask. The analysis mask, which has a
multiplier value of one, will force the analysis to occur only in areas capable of Stewardship potential. The
environment settings for the overlay model (found in model properties) were set by checking Output Extent
under General Settings and Cell Size and Mask under Raster Analysis Settings. Once checked the Values button
is selected to open Environment Settings and then the Analysis Mask layer is chosen for Output Extent, Cell
size, Snap Raster, and Mask. This will force analysis to occur only in Stewardship capable lands and insure that
all data layers overlay appropriately.
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Figure 6: The Overlay Analysis Model
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Data Layer Weighting Process:
The overlay analysis used for defining stewardship potential was created based on twelve state-wide analysis
layers that were weighted based on rankings by the WV Stewardship Committee (Table 1). Rankings were
determined on a scale of 1 to 13 with 1 being of high importance while a ranking of 13 represents a layer of low
importance. Weights were averaged and converted to “mean weights”, to create a “straight rank.” The
reciprocal of the “straight rank” was calculated and normalized to produce the final “normalized weight” used in
the analysis overlay.
Table 1: Rankings from the WV Stewardship Committee to establish weights for suitability analysis layers
Data Layer
Overlay Weighting Scheme Rank Scale
Mean
Straight
Rank
Normalized
Values from 1 to 13 (1is the highest weight, 13 the lowest)
Weight
Rank
Reciprocal
Weights
T/E SPECIES
13
13
12
11
11
9
8
4
10
13
7
11
12
3
7
9.60
13
0.0769
2.4%
SLOPE
PROXIMITY TO
PUBLIC LANDS
GROWTH/DRAIN
OF TIMBER
4
7
9
12
7
13
13
12
8
11
12
12
11
10
3
9.60
12
0.0833
2.6%
7
12
7
1
10
11
11
10
12
8
4
6
13
13
12
9.13
11
0.0909
2.9%
10
4
13
13
5
4
6
13
4
3
13
13
2
5
5
7.53
10
0.1000
3.1%
WETLANDS
5
6
10
5
9
6
9
2
11
12
5
9
10
4
8
7.40
9
0.1111
3.5%
WATERSHEDS
3
11
6
4
13
8
12
7
7
7
9
5
3
6
4
7.00
8
0.1250
3.9%
FIRE
FOREST
PATCHES
RIPARIAN
AREAS
PUBLIC WATER
SUPPLY
RISK OF
DEVELOPMENT
11
10
4
7
12
1
2
8
5
2
1
10
7
11
9
6.67
7
0.1429
4.5%
8
8
3
2
3
10
10
6
6
10
11
2
4
8
6
6.47
6
0.1667
5.2%
1
2
8
10
1
7
7
3
9
9
6
4
9
9
11
6.40
5
0.2000
6.3%
2
9
11
3
4
5
1
11
2
6
10
6
6
1
13
6.00
4
0.2500
7.9%
6
3
3
6
2
12
4
5
13
5
3
3
5
7
2
5.27
3
0.3333
10.5%
INSECTS
12
5
2
9
8
2
3
1
3
1
2
8
8
2
10
5.07
2
0.5000
15.7%
PRIVATE
9
1
1
8
6
3
5
9
1
4
8
1
1
12
1
4.67
1
1.0000
31.4%
The weighting process shifts the suitability analysis in favor of layers with higher importance, as determined by
the committee, to preserve the varying degrees of influence on Stewardship Potential, relative to one another.
Private forest lands were determined to be the layer with the highest influence while slope and threatened and
endangered species habitat had the least influence on stewardship potential, according to stewardship committee
rankings. Once weights were established, each data layer was multiplied by its respective weight of influence.
Datalayers were then added together in the final analysis returning values from 0 - 0.96; those values closest to 1
represent areas with higher stewardship potential.
Results:
Once the Overlay model was implemented, the resulting Stewardship potential layer cell values were
reclassified using the Natural Breaks classification algorithm to determine areas of low, medium, and high
stewardship potential. Actual cell values ranged from 0 (71,595 cells out of a possible 59,387,209 cells) and
0.96 (5 cells) (Table 2). The 0 cells indicate areas where none of the analysis layer values were present but still
stewardship capable. These 0 cells represent areas of low stewardship potential. The 0.96 cell values represent
high stewardship potential. These are areas that fell within nearly all layers meeting their respective criteria.
There were no cells that fell within all layers.
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Table 2: Stewardship potential cell values reclassified using the Natural Breaks Classification Algorithm
Natural Breaks
Cell Count
Reclassified to:
Representing:
0 - .30
8,563,502
1
Low Stewardship Potential
.31 - .51
22,773,265
2
Medium Stewardship Potential
.52 - .96
28,050,442
3
High Stewardship Potential
Area calculations were done by using the Tabulate Area tool and exporting the data to Microsoft Excel to be
calculated and converted to acres (Tables 3-4).
Table 3: Captured from Analysis Map #1 showing results for Stewardship Capable Lands in West Virginia
Stewardship
Potential
Stewardship Capable Lands
Forest
Non-Forest
Total
% of Total
Acres
% of total For. Acres % of total non-For. Acres
High
6,237,971
55.19%
303
Medium
4,940,588
43.71%
124,373
Low
124,372
1.10%
Total:
11,302,931
6,238,274
47.23%
6.53%
5,064,961
38.35%
93.45%
1,904,490
14.42%
0.02%
1,780,118
1,904,794
13,207,725
Table 4: Captured from Analysis Map #2 showing results of existing Stewardship Plans in West Virginia
Stewardship Potential
Acres
Capable of
Stewardship:
Low
Medium
High
1,904,490
5,064,961
6,238,274
Total:
13,207,725
Plan (acres):
Stewardship
Stew.Plan vs.
Acres Capable
of Stewardship (%):
77,776
253,856
303,062
4.08%
5.01%
4.86%
634,694
4.81%
Part 2. Existing Stewardship Plan Digitizing
The second component to the Stewardship Spatial Analysis Project involved the collection and digitizing of
existing stewardship plans in West Virginia. With nearly 4,000 existing Stewardship Plans, this portion of the
project was the most time consuming. All of the West Virginia DOF county and district offices were visited to
collect copies of existing stewardship plans. This proved to be a difficult task since each office had a different
way of filing the plans and many plans were missing maps. Many of the plans had to have maps recreated by
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foresters in order to be mapped (Figure 7). Eventually 3,926 plans were point mapped resulting in 3,903 actual
property maps (polygons). The remaining 23 were not included either because of poor maps or the lack of
mapping data.
Figure 7: Example of a map used to locate
Stewardship plans
Figure 8: Custom tool created to speed up
digitizing and attributing
Plans were heads up digitized into a shapefile using a custom tool we had developed to give each plan a unique
id (Figure 8-9). This would allow attribute information from plan point files to be tied back into each polygon.
Point locations contained attributes information such as: OWNER, ADDRESS, PLANWRITER, ACREAGE,
UTM LOCATION, and UNIQUE. The unique id fields allowed attribute information to be tied to the respective
Stewardship plan polygon (Figure 10).
Metadata:
Metadata were produced for each analysis layer as well as final analysis layers. The FGDC metadata editor in
ArcCatalog was used to meet Federal Geographic Data Committee (FGDC) standards.
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Figure 9: Screen capture showing heads-up digitizing using custom tool
Figure 10: Stewardship plan point attribute table containing plan information
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Analysis and Resulting Map Products:
The suitability analysis product for this project was accompanied by six detailed analysis maps detailing specific
and/or regional issues associated with the Forest Stewardship program. All analyses were done using a 30 meter
grid system. Resulting analysis layers were added to existing ArcMap templates (.mxt files) created by Tom
Luther, GIS Specialist for the Northeastern Area, State & Private Forestry USDA Forest Service. All maps were
then exported to PDF files for easy distribution.
Map #1: Potential for Forest Stewardship Program Benefits
This map details areas with stewardship potential for West Virginia. The map contains tables
identifying stewardship potential acres with percent totals for both forested and non-forested
lands based on low, medium or high stewardship potential. Also listed are the 13 analysis layers
and their respective weights used to create the suitability layer. This layer was created by taking
the 13 weighted analysis layers and combining them with an analysis mask to define areas with
forest stewardship potential. The resulting cell values range from 0 to 0.96 and are re-classed into
low, medium or high stewardship potential based on the Natural Breaks Classification algorithm.
The resulting stewardship potential areas were calculated using the Tabulate Area tool using the
analysis mask to define the zones and the stewardship potential grid defined each value (1-low, 2medium, or 3-high). The data were then exported to Microsoft Excel to be calculated and
converted to acres. Resulting calculations were added back into the map and shown in tables as
potential stewardship acres for each of the three categories for both forested and non-forested
areas of West Virginia. The analysis mask legend found in the template was changed from
Analysis Mask to Areas without Stewardship Potential as this shows areas where the analysis will
not occur.
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Map #2: Potential for Forest Stewardship Program Benefits and Existing Stewardship Plans
Map#2 details areas with stewardship potential and existing Stewardship plans for West
Virginia. This map also identifies stewardship potential acres with percent totals for both
forested and non-forested lands based on low, medium or high stewardship potential.
Stewardship potential is based on existing plans and their respective percentages of capable
lands. This layer was created by taking 13 weighted analysis layers with the same extent and cell
size and combining them with an analysis mask to define areas with forest stewardship potential.
The resulting cell values from 0 to 0.96 are re-classed into low, medium or high stewardship
potential based on the Natural Breaks Classification Algorithm. Existing plans are added as a 30
meter raster and classified based on where they exist with regards to low, medium or high
stewardship potential. Area calculations for potential and existing stewardship areas were
calculated using the Tabulate Area tool using the existing plans to define the zones while the
stewardship potential grid defined each value (1-low, 2-medium, or 3-high). The data were then
exported to Microsoft Excel to be calculated and converted to acres. Resulting calculations were
added back into the map and shown in tables as potential stewardship acres for each of the three
categories for both forested and non-forested areas and existing stewardship acreage with
percentages compared to stewardship capable lands. The analysis mask legend found in the
template was changed from Analysis Mask to Areas without Stewardship Potential as this shows
areas where the analysis will not occur.
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Map #3: Forest Stewardship Potential on Private Forest Lands and Existing Stewardship Plans
Map #3 shows areas with stewardship potential on private forest lands in West Virginia. This
map also identifies stewardship potential acres with percent totals for private forest lands based
on low, medium or high stewardship potential as well as existing plans and their respective
percentages on private forested lands. This layer was created by adding NLCD forested values
(41, 42, 43, 51, and 91) to the stewardship potential layer to determine stewardship potential on
private forest lands. Existing plans were added as a 30 meter raster and classified based on where
they exist in relation to low, medium or high stewardship potential on private forested lands.
This map also compares existing plans with private forested capable lands. Data found in the
table for potential and existing private forest stewardship areas were calculated using the
Tabulate Area tool using the private forest lands to define the zones for potential stewardship
lands. The stewardship potential private forested grid defined each value as 1-low, 2-medium, or
3-high. For existing Stewardship Plan areas on private forest land, existing plans define the
zones and the potential private forested grid defined each value. The data were then exported to
Microsoft Excel to be calculated and converted to acres. Resulting calculations were added back
into the map and shown in tables as potential private forested stewardship acres for each of the
three categories and existing stewardship private forest land acreage with percentages compared
to private forested stewardship capable lands. The analysis mask legend found in the template
was changed to non-forested to more accurately represent the mask areas of the map.
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Map #4: Resource Richness
Map #4 shows areas of resource potential for the Forest Stewardship Program of West Virginia.
This layer was created by only including analysis layers considered resources to the (FSP). These
resource layers and their respective weights from the suitability analysis were normalized to
match the 0 to 1 scale of the suitability analysis. The resulting aggregate layer was then classified
Low, Medium, and High based on the Natural Breaks Classification Algorithm with 0 values
excluded.
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Map #5: Resource Threats
Map #5 defines areas considered resource threats to the Forest Stewardship Program (FSP) in
West Virginia. This layer was created by only considering analysis layers that were threats to the
(FSP). These threat layers and their respective weights from the suitability analysis were
normalized to match the 0 to 1 scale of the suitability analysis. The resulting aggregate layer was
then classified as Low, Medium, and High based on the Natural Breaks Classification Algorithm
with 0 values excluded.
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Map #6: Forest Stewardship Potential on Non-Forested – Non-Developed Lands and Existing Stewardship
Plans
Map #6 defines areas with stewardship potential on non-forested and non-developed lands for
West Virginia. This layer was created by adding NLCD non-forested non-developed values (31,
33, 81, 82, 85 and 92) to the stewardship potential layer to determine stewardship potential only
on non-developed and non-forested lands. Existing plans were added as a 30 meter raster and
classified based on where they exist with regards to Low, Medium and High stewardship
potential for non-developed and non-forested capable lands. This map also compares existing
plans with non-forested non-developed capable lands. Data found in the table for potential and
existing non-forested and non-developed stewardship areas were calculated using the Tabulate
Area tool using the non-forested and non-developed layer to define the zones for potential
stewardship lands while the stewardship potential grid defined each value (1-low, 2-medium, or
3-high). For existing stewardship plan areas on non-forested and non-developed land, existing
plans define the zones and stewardship potential grid defined for each value. The data were then
exported to Microsoft Excel to be calculated and converted to acres. Resulting calculations were
added back into the map and shown in tables as stewardship capable acres on non-forested and
non-developed for each of the three categories. Likewise, existing stewardship acreage on nonforested and non-developed lands with percentages compared to on non-forested and nondeveloped stewardship capable lands are shown in the table.
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Map #7: Regional Analysis of Potential for Forest Stewardship program Benefits for WVDOF regions 1, 2, and
3 and Existing Stewardship Plans
Map #7 shows areas with stewardship potential for the new West Virginia Division of Forestry
Administrative Regions. This map also identifies stewardship potential acres with percent totals
for both forested and non-forested lands based on low, medium or high stewardship potential for
each region. Also listed are the 13 analysis layers and their respective weights. This layer was
created by taking the 13 weighted analysis layers with the same extent and cell size and
combining them with an analysis mask to define areas with forest stewardship potential. The
resulting cell values from 0 to 0.96 were re-classed into low, medium or high stewardship
potential based on the Natural Breaks Classification Algorithm. These results were further broken
down into the three West Virginia Division of Forestry regions with statistics on potential and
existing stewardship acres and respective percentages for the regions. The resulting stewardship
potential areas were calculated using the Tabulate Area tool using the Analysis mask to define
the zones and the stewardship potential grid defined each value (1-low, 2-medium, or 3-high).
The data were then exported to Microsoft Excel to be calculated and converted to acres.
Resulting calculations were added back into the map and shown in tables as potential stewardship
acres for each of the three categories for both forested and non-forested areas of West Virginia.
The analysis mask legend found in the template was changed from Analysis Mask to Areas
without Stewardship Potential to reflect areas where the analysis will not occur.
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