Forest Stewardship Spatial Analysis Project
Illinois Methodology
March, 2007
Project Summary
Administered by the U.S. Forest Service and implemented by State forestry agencies, the
Forest Stewardship Program encourages private forest land owners to manage their lands
using professionally prepared Forest Stewardship plans. These plans consider all
associated forest-related resources to meet landowner objectives including – but not
limited to – timber, wildlife, recreation, water, and aesthetics.
The Forest Stewardship Program’s Spatial Analysis Project (SAP) is a GIS-based process
through which participating states can identify those lands with the greatest potential for
Stewardship Program benefits, that is, those lands most suitable for inclusion in the
Program. Private land program and GIS staff from the four states involved in the pilot
SAP effort (Connecticut, Maryland, Massachusetts and Missouri), along with Forest
Service Stewardship Program and GIS staff selected 12 factors which help identify the
“Stewardship potential” of a given piece of land. Existing, readily available data layers
were selected to address each factor and an overlay analysis based on 30-meter by 30meter grid cells was then conducted to identify suitability.
Factors Defining Stewardship Potential and Datalayer Selection
Although states were encouraged to use additional layers to address any state-specific
issues or concerns, it was determined that the core 12 would suffice for the State of
Illinois. The factors were differentiated into two groups: resource potentials and resource
threats.
Resource potential factors:
ƒ Riparian Zones
ƒ Priority Watersheds
ƒ Forest Patch Size
ƒ Threatened and Endangered Species Habitat
ƒ Public Drinking Water Supply Sources
ƒ Private Forest Lands
ƒ Proximity to Public Lands
ƒ Wetlands
ƒ Topographic Slope
Resource threat factors:
ƒ Forest Health Risk
ƒ Development Threat
ƒ Wildfire Risk
Certain lands within any state are considered to be ineligible for inclusion in the Forest
Stewardship Program based on land use/land cover. These land use/land cover classes
include open water, urban, and publicly owned lands. A mask was created to exclude
these lands from the area of analysis.
Each state determined the relative importance of each of the 12 factors based on their
state-specific conditions. This determined the influence, or weight, each layer would
have in the analysis model.
The 12 layers were then combined in a GIS-based overlay analysis which took into
consideration the weight for each factor. The final product was a composite data layer
representing the Forest Stewardship Program potential of a given piece of land. A
“natural breaks” classification algorithm was used to break the values into high, medium
and low classes. The resulting dataset is shown below.
Map of Forest Stewardship Program potential in the State of Illinois.
The 12 Core Data Layers
Riparian Corridors: This layer is intended to
place importance on river and stream corridors
where buffers of forest or vegetative cover can have
a positive or restorative effect on water quality and
riverine ecosystems. The riparian corridors dataset
was created by buffering perennial rivers and
streams by 300' on each side of the feature and
intermittent streams by 100' on each side of the
feature.
Note: Artificial river paths (channel paths through
ponds and lakes) were removed from the dataset
prior to buffering.
Data source:
“Rivers” feature class from the ESRI U.S. Rivers
and Streams in the United States dataset; (1:24,000
scale).
Priority Watersheds: This data layer is intended to
place emphasis on landscapes that impact long-term
watershed function. Priority watersheds can be:
those that are impaired or deforested, but could be
measurably improved through planning and active
management, or those that are currently productive,
but somehow threatened.
Data source:
Watershed priorities for Illinois DNR as defined and
identified in the Clean Water Action Plan – Unified
Watershed Assessment and Watershed Restoration
Priorities for Illinois (1998).
http://www.epa.state.il.us/water/unified-watershedassessment/index.html
Wetlands: This data layer is intended to identify
wetlands where planning and management can
achieve a higher degree of protection for purposes
including water quality and wildlife habitat.
Data source:
Digital National Wetlands Inventory (NWI) data
originally compiled at 1:24,000 scale by the U.S.
Fish and Wildlife Service. NWI classes FO
(forested) and SS (scrub/shrub) were used.
Public Water Supply Areas: This data layer is
intended to place emphasis on areas of watersheds
that drain onto public drinking water supply intake
points.
Data source:
Watersheds of community public water supply inchannel reservoirs in Illinois.
Sally McConkey, sally@uiuc.edu
Phone: 217-333-5482
Private Forest: This data layer is intended to place
emphasis on eligible private lands with existing
forest cover. Five NLCD classes were used to
create a "forest" layer: deciduous forest, coniferous
forest, mixed forest & woodland, shrubland, and
woody wetlands (NLCD classes 41, 42, 43, 51, 91).
The analysis mask eliminates public land from
consideration.
Data source:
National Land Cover Database (NLCD 1992).
Forest Patches: This data layer is intended to
emphasize forest patches of ecologically and/or
economically viable size (50 ac.).
This layer consists of NLCD classes 41, 42, 43, 51,
and 91 erased with buffered road corridors. Buffer
widths are based on estimated travel speeds (65
mph roads were buffered 100' on each side, 30-55
mph roads were buffered 50').
Note: This layer includes private and public
forests so that private forest land that adjoins public
forest, and thus is part of a large, contiguous patch
of forestland, is not eliminated from consideration.
This ensures that when public lands are removed
with the analysis mask, private forests less than 50
acres in size will still get the additional weighting
associated with this layer even if they combine with
public forest to form a patch larger than 50 acres.
Data source:
Roads data were extracted from the StreetMap USA
data provided in the ESRI Data & Maps media kit
on the ESRI Data & Maps/StreetMap USA DVD.
Proximity to Protected Land: This data layer is
intended to place emphasis on areas in close
proximity to lands that are considered to be
permanently protected (and managed) and thus
contribute to a viably large, interconnected forest
landscape. This layer is based on the assumption
that public lands are in a permanently protected
status, and is intended to include private lands in a
permanently protected status (easements, or other).
Lands within a ½ mile buffer around protected
lands are included in this layer.
Data source:
Illinois Natural History Survey's 1:100,000 scale
Illinois Gap Analysis Stewardship layer, version
4.0, December 2003. For SAP, owner codes 7000
(private) and 8000 (water) are excluded.
Tari Tweddale
GIS/Remote Sensing Specialist
Illinois Natural History Survey
tweicher@uiuc.edu
217-265-0583
Threatened & Endangered Species: This data layer
is intended to identify areas that provide habitat for
threatened and endangered species. This data set
depicts the locations of endangered and threatened
species habitat, unique natural communities, and other
significant natural resources in Illinois, as reported to
the Natural Heritage Database (INHD) Program.
Data source:
Illinois Natural Heritage Database, Illinois
Department of Natural Resources
Tara Gibbs Kieninger, Database Admin.
ORC - Illinois Natural Heritage Database
Illinois Department of Natural Resources
tkieninger@dnrmail.state.il.us
217.782.2685
Topographic Slope: This layer is intended to serve
as a proxy for both forest timber or fiber
productivity potential and as an indicator of
operability. Slope was chosen as it is nationally
available proxy for timber or fiber productivity
because of its relationship to ease and feasibility for
forest harvesting operations.
Selected all areas within the state where slopes are >
5% (mostly agricultural land, where it is forested
there is less erosion concern), and < 40%
(inoperable with a skidder).
Data source:
National Elevation Dataset (USGS) 30-meter
Digital Elevation Model (DEM), 1:24,000 scale.
Forest Health: This data layer is intended to place
importance on areas where silvicultural treatments
can address significant risks to forest health.
The definition of risk is as follows: “The potential
that 25% or more of the standing live volume of
trees greater than 1'' in diameter will die over the
next 15 years, including background mortality”. The
1 km Forest Health Risk data set was resampled to
30 meter and then erased with a layer comprised of
the inverse of the forest layer developed for the
Forest Patches layer to confine the forest health risk
to only forested areas.
Data source:
National Insect and Disease Risk Map (NIDRM),
USDA Forest Service Forest Health Technology
Enterprise Team (FHTET).
Wildfire Assessment: This data layer is intended to
emphasize areas where planning and management are
likely to reduce a relatively high risk of wildfire.
The Northeastern Area Wildland - Urban Interface
Fire Analysis considers the risk of fire (potential for
ignition, based on 1990 pop. density), fire hazard
(potential to burn, based on fuels and topography),
and capability to protect the resources (distribution of
volunteer fire departments, by ZIP code). Wildfire
risk is classed into High, Moderately high, Moderate,
and Low. All areas where risk was determined to be
“High” or “Moderately high” were selected to form
the basis for this data layer.
Data source:
The Northeastern Area Wildland - Urban Interface
Fire Analysis: Northeastern Area, State and Private
Forestry.
Risk of Development: This data layer is intended to
emphasize areas that are projected to experience
increased housing development in the next 30 years.
Increased management of private forests can improve
the likelihood that these lands will remain forested
and continue to provide forest values such as timber,
wildlife habitat, and water quality. This layer is
particularly important in the wildland-urban
interface.
Based on updated housing density data (v4)
produced by Dr. David Theobald for the “Forests on
the Edge” study. These data were developed by
subtracting public lands and water from 2000 Census
block data and then calculating acres per house. For
SAP, 2030 projections were subtracted from 2000
density to determine areas under pressure from
development.
Data Source:
Housing Density Projections (Dr. David Theobald,
Colorado State University).
Analysis Extent
Analysis Mask: The analysis mask defines the area
within the analysis extent that will be considered
when performing an operation or function. For the
Illinois SAP analysis this includes all areas that are
not urban/developed, public ownership, or open
water.
Data sources:
USGS’s NLCD (1992) classes:
•
open water (11)
•
developed land (21, 22, 23)
•
barren land (31, 32)
IL GAP Stewardship data (public ownership classes)
Datalayer Weighting
The Illinois Forestry Development Council members attending the January 17, 2007
meeting in Champaign, IL voted on the relative importance of the above 12 data layers.
They were asked to assign numerical ranks to each layer in order of decreasing
importance, and the average score for each data layer was then converted to a percentage
to determine the amount of influence, or weight, each layer would have in the analysis
model.
Following the example of the state of Missouri, the averages of the ranking values were
subtracted from 12 in order to obtain inverse ranks. Each inverse rank was divided by the
sum of all inverse ranks, in order to obtain a decimal rank directly proportional to the
value of the assigned numerical ranks. Each of the decimal rank values were multiplied
by 100. The results are shown below.
Layer
Weight (%)
Private Forest
15.32
Riparian Corridors
12.73
Forest Patches
11.31
Wetlands
9.60
Priority Watersheds
9.09
Development Pressure
8.59
T&E Species
6.97
Drinking Water Supply
6.87
Proximity to Public Lands
6.67
Forest Health
6.46
Topographic Slope
5.45
Fire Risk
Percent (%) influence by layer.
.91
GIS Analysis
Each of the 12 layers used in the analysis had a grid cell size of 30 meters, and they were
all snapped to the mask layer. Every cell in each of the 12 layers were coded 0 or 1,
where cells not representing the layer in question were 0, and all cells that did represent
the layer were 1. For example, in the slope layer, all pixels with a slope >5% and <40%
were reclassed to 1, all other pixels were reclassed to 0.
Each raster layer was then multiplied by its weight so that each pixel took the value of its
weighting. To reduce computation time, actual weights were multiplied by 10,000 so that
all weights were integers. The raster layers were all reclassified to exhibit either the
value of their decimal ranking * 10,000, or zero in all cells. These binary layers were
summed using the Raster Calculator to create the composite SAP layer.
The next step was to remove lands ineligible for Stewardship, using the Analysis Mask
shown above. To do this, the analysis mask was recoded to values of NoData and 1, with
NoData areas ineligible for stewardship. This raster was then multiplied with the
Stewardship Potential raster, with the result being that NoData areas in the Analysis
Mask became NoData pixels in the Stewardship Potential raster.
Once we had a stewardship potential mask for areas eligible for stewardship, we used the
Natural Breaks classifier in ArcMap to classify Stewardship Potential into Low, Medium,
and High. The ranges are shown below. The raster was then reclassified the so that 0 =
no potential, 1=low potential, 2=medium potential, and 3=high potential.
Digitizing Existing Stewardship Plans
The second part of the SAP is the creation of a shapefile showing existing stewardship
plans in each state. The State of Illinois has committed to completing this part of the
SAP process in FY 2008.