Forest Stewardship Spatial Analysis Project
Ohio Methodology
November, 2006
Project Summary
One purpose of the Spatial Analysis Project (SAP) is to create a data layer for a
state that represents levels of potential benefit from, or suitability for inclusion in,
the Forest Stewardship Program as delivered by state forestry agencies and the
U.S. Forest Service. The SAP is fundamentally a GIS-based analysis aimed at
identifying the most suitable private lands for FSP consideration. The modeling
approach used in Ohio employs a weighted overlay analysis using ArcGIS 9.1
Model Builder, and utilizes many standard GIS datasets for the state..
The factors were differentiated into two groups: resource potential and resource
threats. The resource potential factors include:
Riparian Zones
Priority Watersheds
Forest Patch Size
Natural Heritage Data
Public Drinking Water Supply Sources
Private Forest Lands
Proximity to Public Lands
Wetlands
Topographic Slope
The resource threat factors include:
Forest Health
Development Level
Wildfire Assessment
Certain lands within any state are not eligible for inclusion in the Forest
Stewardship program. Land use / land cover factors which identify these areas
are open water, urban areas and publicly owned lands. A mask was created to
exclude these areas from the analysis. Once the 11 factors were identified, the
relative importance of each of the criteria based on their state-specific conditions
was determined. Ohio Department of Natural Resources, Division of Forestry
staff and the Ohio Forest Stewardship Committee ranked the criteria and an
average weight was calculated for each. The 11 layers were then combined in a
GIS overlay analysis which took into account the weight for each factor. The final
product was a single data layer which represents the suitability of the land for
inclusion in the Forest Stewardship Program.
There were three main phases to the Ohio SAP: database development, data
layer ranking, and spatial overlay modeling.
Database Development – this task involved the collection, evaluation and
processing of the thematic data layers needed to conduct the SAP assessment
for Ohio. The basic data products used to derive the thematic layers for the Ohio
SAP are given in Table 1.
Table 1: Source Data for Ohio SAP
Data Layer
Source*
Scale
Wildfire assessment
Grid analysis on land
cover and DEM
30 meter
Forest patches
MRLC
TM 30
meter
Proximity to public
land
Protected Lands
1:24000
Threatened and
DEP—Heritage database 1:24000
endangered species
Change in
households
USFS, Census block data
30-meter
grid
Forest pests
USFS
1:24000
Wetlands
DEP/NRCS or USGS
1:24000
Riparian areas
Derived from DEP hydro
streams
1:24000
DEP—Aquifer protection
Public water supplies wells and surface water
quality layer
1:24000
Slope
Statewide NED DEM
layer, USGS
30 meter
Priority watersheds
HUC from USGS
1:100000
Analysis mask
(urban, open water,
public lands)
MRLC and DEP data sets 30 meter
Data Layer Definitions
All map files imported, transformed and created by the Ohio SAP were projected
to a common standard coordinate system (NAD 1983 UTM Zone 17N). Vector
files where projected using the Transverse Mercator projection and Raster files
were created using a 30 meter cell size. All raster files were coded using the 0/1
convention for raster-based thematic data.
Riparian Zones: Riparian zones were derived from
the Ohio Streams shape files as defined by the
streams of the US from
(http://nationalatlas.gov/atlasftp.html?openChapter
s=chpwater#chpwater ) and
(http://arcdata.esri.com/data/tiger2000/tiger_statel
ayer.cm?sfips=39 ). Riparian zones were created
by buffering (100 meters each side) of the
perennial streams from the streams layer. The
buffers are shown on the map at left. This threshold was
the minimum set that could be extract based on the
minimum mapping unit and resolution of the data set as a
function of scale.
Priority Watersheds: These watersheds are
considered priorities for various reasons.
Priority watersheds in Ohio were determined
by using the 2002 Percent of Impaired
Waters data produced by the EPA
(http://www.epa.gov/waters/data/downloads.h
tml). The sixth hydrological unit level
(subwatershed) was used based on the
Forest Stewardship Spatial Analysis Project
Methodology Report for Colorado December
2005. The subwatershed layer was thus reclassified based on EPA Percent
Impaired Waters data: 1= any % impairment and 0 for no % impairment.
Forest Patches: All forest cover used in this
project was extracted from the Ohio GAP and
MRLC data sets. Forest areas where selected
based on land cover class and the selected sets
saved Forest polygons based on a 150 acre
threshold were used to determine minimum
patch size. This threshold was selected due to
the constraints imposed by the spatial resolution
of the data. Values below this minimum
generated significant problems with sliver and spurious polygons which would
severely reduce the fidelity of this data layer.
Threatened and Endangered Species: This layer
was derived from the Ohio Department of Natural
Resources, Division of Natural Areas and Preserves
Natural Heritage database. Polygons with either
threatened or endangered species were selected
and the selected set was then converted to a raster
format.
Public Drinking Water Supply Areas: Using
shapefiles obtain from the Ohio EPA Public
Water Supply Systems dataset, point data
locations of public aquifer protection wells and
surface water intake zones were used to create
two initial layers: a 500 meter buffer
surrounding wells and 100 meter buffer
surrounding surface intakes. These layers
were subject to a union overlay to form a single
layer and converted to raster format.
Proximity to Public Lands: This file was derived
from 3 shapefiles: Ohio Department of Natural
Resources (ODNR) lands, USFS Wayne National
Forest Lands and non-ODNR lands. All public land
ownership was created by merging these
individual agency files and then buffering the
polygons by 10,000 meters. The public land
polygons were then subtracted from the buffer
layer to form the map shown at right.
Wetlands: Digital National Wetlands Inventory
shapefiles originally compiled at 1:24,000 scale by
the U.S. Fish and Wildlife Service together with the
Ohio GAP land cover data set were used as the
source for this layer. Wetland areas were selected
from these layers, and a union overlay was
employed to merge the sets together. This final
shapefile was converted to raster format for further
analysis.
Topographic Slope: A statewide 30 meter
Digital Elevation Model (1:24,000 scale
source) from the National Elevation Dataset
(USGS) was used to select areas where
slope is between 5% and 40%. Percentage
slope was derived from the Ohio 30 meter
Digital Elevation Model (DEM) raster file
using the Spatial Analyst “Surface Analysis”
tool, at a cell size of 30 and named
SlopePer30. A complete merged DEM of the
state of Ohio was downloaded from the Ohio metadata explorer. This grid was
then reclassified to a value of 1 for slope between 0-12%, 2 for slope between
12-24% and 3 for slope 24%-↑.
Forest Health: Forest Health/Forest Pests data
layers were obtained directly from the ODNRDivision of Forestry and transformed into the map
datum and projection system used for the Ohio
SAP and converted to raster format.
Developing Areas: Based on U.S. Census
Bureau 1990 and 2000 data, census block
group data for change in households for 1990
and 2000 (http://www.census.gov/ ), and
census Ohio block group shapefiles for 1990
and 2000
(http://arcdata.esri.com/data/tiger2000/tiger_s
tatelayer.cfm?sfips=39 ) were downloaded.
Census block group polygons from 1990 and
2000 were unioned to deal with differing
census geography boundaries and the number of households was calculated.
The change in number of households from 1990 to 2000 was then calculated.
Wildfire Assessment: This GIS layer was
obtained directly from the ODNR- Division of
Forestry and transformed into the map datum
and projection system used for the Ohio SAP
and converted to raster format
Analysis Mask: The analysis mask
contains the areas not considered in the
analysis: urban/developed areas, publicly
owned lands, and open water. This file
was created through the reclassification of
the Ohio GAP land cover file, eliminated
land cover categories to be excluded (0)
from analysis. Land covers to include
were reclassified as 1. This initial mask
was then subject to Boolean overlay (
multiplied) with the public land layer to
complete the final masking layer.
Data Layer Ranking – this task will focuses on the application of ODNRDivision of Forestry layer weights and criteria to the SAP data layers. Of the
eleven criteria identified as contributing to the potential Stewardship Program
benefit of a given piece of ground, some will likely be more important than others.
To account for differing levels of importance Ohio Department of Natural
Resources, Division of Forestry staff ( n = 22 ) ranked the 11 criteria. Staff was
asked to rank each factor from 1 to 11, with 1 being the most important. In
addition a value of influence (weight) or importance was assigned to each
variable (Table 2).
Table 2: Criteria Ranking and Weighting
Criteria
Rank
Forest Patch Size
1
Riparian Corridor
2
Priority Watershed
3
Forest Pests
4
Public Water Supply
5
Change in Household
6
Wetlands
7
T & E Species
8
Proximity to Public Land
9
Slope
10
Fire Risk
11
Weight/ % Influence
17.1
14.5
12.3
10.1
9.2
9.1
7.5
6.9
6.4
4.3
2.0
Spatial Overlay Modeling – this task centered on the GIS treatment of the SAP
data layers following a “suitability assessment” methodology. Using the standard
SAP procedure, data layers were multiplied by their criteria weights and
mathematically overlayed to produce a composite SAP layer for Ohio. The
analysis process employed the ArcGIS 9.1 ModelBuilder function to develop the
derivative map products required for this step in the Ohio SAP. Typically
operations required reclassification, simple addition, and Boolean overlay.
However in producing the composite state Stewardship Potential map the
method of Weighted Overlay was used.
Weighted Overlay overlays several rasters using a common measurement scale
and weights each according to its importance. Each value class in an input raster
is assigned a new value based on an evaluation scale and these new values are
reclassifications of the original input raster values. Each input raster is weighted
according to its importance, or its percent influence. The weight is a relative
percentage, and the sum of the percent influence weights must equal 100
percent. The model developed to product the Ohio Stewardship Potential map is
shown in Figure 1.
Figure 1: ModelBuilder design used to produce Ohio Stewardship Potential Map.