Forest Stewardship Analysis Project – Pilot Overlay Study: Methodology for the U.S.
Virgin Islands
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Project Summary
Base Layers and Computing
Factors of Influence and Data Layer Development
Private Forest Lands
Wetlands
Forest Patches
Riparian Areas
Proximity to Public Lands
Slopes
Watersheds
Private Forest Mask
Non-forest Non-developed Mask
The Overlay Model
Model Overview
Data Aggregation
Weighting
Numbering System
Web Site Development
Site Purpose
State Participation
Project Summary
The Spatial Analysis Project (SAP) has as one its objectives the creation of datasets for
states that highlight sites where there would be potential benefit from, or suitability for
inclusion within, the Forest Stewardship Program. Such layers could assist Sate Forestry
agencies with the identification of potential sites and help the US Forest Service assess
the effectiveness of its programs. As stated by the Missouri participant, 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 program and GIS
staff, identified 12 factors which help identify the “Stewardship potential” of a given
piece of land. The pilot states worked together to develop layer source materials,
common and available for each state, designed to lead to this final set. The factors were
then separated into two groups, resource potential and resource threats, and later
combined using weighted rankings within a GIS model to create the final analysis maps.
Factors of Influence and Data Layer Development
The U.S. Virgin Islands pre-existing spatial data is sorely lacking and needs much
development. Data is not currently shared between agencies. Although the goal was to
utilize 12 data layers in the analysis, only six were available for the analysis, with the
main emphasis on existing forest cover layers. Other factors for the overall analysis are
the differences in area between the islands of St. Thomas and St. John.
There is existing information for the following datalayers: Private Forested Lands,
Wetlands, Forest Patches, Riparian Corridors, Proximity to Publicly Protected Lands, and
Slopes. Datalayers were not available for the following: Forest Health, Priority
Watersheds, Threatened and Endangered Species, Threat of Development, or Fire. There
are no large forested areas in the Virgin Islands such that forest pests become an
important topic. All watersheds in the Virgin Islands are important, so there are no
priority watersheds per se. There are only a few animal and plant species that are on the
federal list of Threatened and Endangered Species, and no data exists on their locations in
the Virgin Islands. All of the privately owned land areas in the Virgin Islands are under
threat of development, thus there is no need for a separate map for this category of risk.
Finally, there is no fire hazard information as fires are few and generally occur in
scrubland rather than in forested areas in the Virgin Islands.
Private Forested Lands: This datalayer describes forested land in the Virgin Islands that
are not within the extent of the Analysis Mask. The forested land coverage was derived
by querying fields from the Rapid Environmental Assessment Layer (UVI-CDC 2000).
Connecticut did not use scrub areas due to correlation to power lines. This is not the case
in the Virgin Islands and all forest types were used.
Wetlands: This layer shows wetland areas in the Virgin Islands. Statewide coverage was
derived from the wetland layer from IRF and VI CDC (2002)
Forest Patches (5 acres): The source of the Forested related information in the pilot
study has been the REA data. Our forest cover layer was derived from the REA layer for
the Virgin Islands by selecting forest land cover classes. Applications used were
ArcView 9.2 Spatial Analyst and ArcMap. The Virgin Islands created the patches in
vector format. Forest features were reselected from the REA and dissolved based on the
forest attribute leaving patches of forested areas. X tools for ArcGIS was used to create
the acreage of the patches and patches greater than 5 acres were selected. Five acres were
selected based on the previous minimum size of a forest stewardship property in the
Virgin Islands (recently changed to 3 acres). The data was merged with the outlines of all
three islands and then transformed into a raster format. This layer was transformed to a
raster based on forest values then re-classed to 1/0, forested or non-forested. Roads layers
were not used in the analysis due to problems of density in which case most of the data
would not be selected.
Riparian Corridors: This raster data layer shows 50 foot riparian corridors
encompassing gut features from the Digital Raster Graphics (DRG) quad based hydro
data set from the CDC 2002. Areas near or touching stream features are given a weighted
value within the model. All linear streams were selected from the vector data set and
buffered to 50 feet on either side (a distance settled on by current law from USVI
Department of Natural Resources). The results were a buffered dataset which was then
converted to a 30 meter Grid format consisting of a 1/0 relationship – within buffer equal
to one, all other areas equal to zero.
Proximity to Publicly Protected Lands: This raster layer represents areas touching or in
proximity to existing public (protected) lands. The public protected areas were provided
by the VI Department of Agriculture and National Park System Data. The scale of
publicly available information is too small and does not include small areas of public
protection. This vector layer was then buffered to 500 feet. The buffer provides a
mathematical tool for measuring proximity to the protected resource. The centers were
removed and the resulting buffered layers converted to 1/0 grid layers. These were then
combined into one final dataset consisting of the buffers around publicly protected lands.
Slopes: This raster data layer describes areas of the Virgin Islands where the slope is
more than 15% and less than 30%. Percentage slope was derived from a statewide NED
30 meter Digital Elevation Model (DEM) raster file using the Spatial Analyst ‘Surface
Analysis’ tool. The final slope layer was then queried to the desired slope range of 15%
to 30% slope, providing a 1/0 Grid dataset.
Analysis Mask: The analysis mask represents urban, open water, and protected public
lands. Features in this layer are considered outside the areas where the private
stewardship will be applied; to be removed from the full analysis. Urban and open water
features were selected from the REA data set. Geographic Consulting provided pond
areas for St. Croix. Protected public lands were selected from the NPS and DEP public
lands data sets and known parcels. Unlike the proximity to protected lands layer, where
the interests are natural resource features, public schools, cemeteries, and park features
were included in this mask. These are areas outside of the stewardship program. As a
layer the mask features were assigned a value of 1, all others a value of zero. During
model applications the 1 was converted to Null, canceling all calculations in those
areas, thus removing them from the final summaries.
Private Forest Analysis Layer: Part of the final analysis is a layer depicting potential
Stewardship: high, medium, low analysis (HML) on private lands with existing forests.
During the model analysis the Private Forested Lands layer was given a priority coding
and combined within the model to create the final HML layer. In this analysis the private
layer acts as an inverse mask, all features outside the layer assigned a value of Null, those
within a 1. Multiplying this layer with the final HML layer creates an HML layer
depicting these private forested lands (no agriculture or municipal lands).
Non-forest – Non-developed Mask (NFND): As an inverse to the Private Forest
Analysis, there was in interest in summarizing the total potential stewardship analysis
over lands that were not forested but still have potential for stewardship activity. This
layer depicts the mask used for this final summary by selecting Agricultural lands
(opposite of forest selection) and non-urban features (those not included in full analysis
mask) from the REA dataset. The mask features were assigned a value of 1, all others
a value of 0. Multiplying this layer with the final HML data layer creates an HML layer
depicting stewardship potential outside the forested areas.
The Overlay Model
Model builder was used to apply weighted values and output the raster. Using weighted
sum and applying values from 1 to 3 based on committee importance.
Data Aggregation – Each of the 7 layers was assigned its multiplier (weighted values)
then combined through simple spatial addition within model builder. The resulting
output layer contained values from 0 to 14, the maximum for the given layers and overlay
patterns for this Virgin Islands model. If all layers were weighted as 3 and overlaid
directly the possible maximum would be 21. For the final three level outputs the values
had to be grouped according to the natural breaks technique. The result was the final
analysis map with values designated as low, medium, and high priority. A mask was then
used to remove lands considered outside the stewardship program designation (urban
area, open water, public lands).
In addition to the primary layers, the forested lands that had earlier been separated as a
unique layer were used as a mask overlay to summarize and display only those priority
areas covered by lands where trees currently exist. While Stewardship is viable and
encouraged on non-forested lands having potential for growing trees, those lands with
existing forested systems should be identified for their immediate forest benefits and
resource protection.
Weighting –The Virgin Islands procedures for weighting ended up more qualitative than
the quantitative (fractional) techniques used by Massachusetts and Missouri. Like the
other States, our Forest Stewardship Coordinating Committee reviewed the list of data
layers for priority considerations, ranking them according to the techniques described by
Massachusetts. The result was a fractional list of weights for each layer. The conclusion
was to summarize the high, medium, low evaluation into weighted values of 3, 2, or 1 for
each layer. With each layer assigned its ranking the layers were then added together to
create a final map - resulting in values of 0 for no data to 14 for the maximum recorded
summary (if all layers were assigned the value of 3 the theoretical maximum would be 3
x 7 or 21). For the final output map these were then grouped into the high, medium, low
categories using natural breaks to reclassify the raster into 1, 2 or 3 values to represent
HML values.
Credits
The layout and content flow for this report was based on the structure of the methodology
report from Connecticut and Colorado. Supplemental information on the project
summary was borrowed from the Connecticut Report. The material content was
authored and edited by Russell Slatton, private consultant of Geographic Consulting, and
Marilyn Chakroff, Forest Stewardship Coordinator, VI Department of Agriculture.