Applications

Application of SWReGAP Data to the Forest Stewardship Program’s Spatial Analysis Project in Utah

Lisa A. Langs 1, John H. Lowry 1 , Kevin Wells 2 , and R. Douglas Ramsey 1

1 Remote Sensing/GIS Laboratory, College of Natural Resources, Utah State University, Logan, Utah
2 Utah Department of Natural Resources, Division of Forestry, Fire, and State Lands, Salt Lake City, Utah

Background

Nearly 45% of the nation’s forests (354 million acres) currently fall within non-industrial private ownership, providing valuable timber resources, wildlife habitat, watershed protection, and recreational opportunities that benefit not only the landowner but society as a whole (USDA Forest Service 2005). Authorized by the Cooperative Forestry Assistance Act of 1978, the Forest Stewardship Program (FSP) was created to promote sustainable forest practices among the nation’s non-industrial private forest sector (USDA Forest Service 2005). State forestry agency partners provide technical assistance through the development of individual forest stewardship plans and financial incentives to willing landowners to encourage active management of their forested lands.

An important challenge however, faced by the FSP, is the ability to assess the effectiveness of existing stewardship plans and where future efforts would have the greatest impact relative to statewide objectives (WFLC 2004). A recent improvement to the FSP has been the development of the Spatial Analysis Project (SAP) and related decision-support tools (WFLC 2004). SAP involves a geospatial approach using a suite of common GIS data layers in a modeling environment that provides State foresters a standardized, yet flexible tool to; 1) monitor existing stewardship plans, 2) provide systematic statewide assessments of “priority” forests, and 3) account for the connectivity of FSP efforts in the context of the existing network of conservation lands (WFLC 2004). The Utah Division of Forestry, Fire, and State Lands (UDFFS) has long been a partner of the FSP and as part of the second roll-out of SAP, was recently requested to develop a SAP for Utah. With the timely completion of the Southwest Regional Gap Analysis Project (SWReGAP), a host of several newly created regional data sets for Utah, Arizona, Colorado, New Mexico, and Nevada, UDFFS decided to employ SWReGAP data in their SAP effort.

The Spatial Analysis Project for Utah

The primary objective of SAP is to identify specific locations of privately-owned forested lands rich in natural resources (e.g. a water source, threatened or endangered species), associated with minimal threats (e.g. low fire risk, minimal development potential), and adequately contribute to statewide conservation of forested areas (WFLC 2004). SAP functions as a FSP suitability analysis to locate areas with the greatest potential to benefit from FSP practices. UDFFS contracted the RS/GIS Laboratory at Utah State University to prepare the required data sets and develop the structure behind the SAP models. UDFFS will apply their expert opinion to adjust any parameters and decide on the final map output.

Data Needs & SWReGAP Data Applicability

Fourteen data layers are common to all SAPs (Table 1). Other data layers may be added to improve the model where appropriate. GIS data used for this project were assembled from a variety of sources including; UDFFS, Utah’s Automated Geographic Reference Center (AGRC), Utah Division of Wildlife Resources (UDWR), U.S. Census Bureau, U.S. Geological Survey National Hydrography Dataset (NHD), U.S. Geological Survey National Elevation Dataset (NED), and SWReGAP. SWReGAP provided several of the core data layers including; land cover, stewardship, and species richness (Table 1).

The first data layer created was an analysis mask (i.e. the area of interest). The analysis mask was created by intersecting SWReGAP forest classes with the private ownership class extracted from SWReGAP stewardship data, to identify privately-owned forested lands that could potentially benefit from FSP. All subsequent analyses were constrained by the analysis mask. From the land cover data, forest, riparian, and wetland classes were extracted to create three separate vegetation files (i.e. Forested areas, Riparian areas, and Wetlands, respectively). Forest patches were created by removing buffered roads from the forests data and eliminating “patches” of forest smaller than a specified unit area such as 1000 acres (4.05 km 2), for instance. Proximity to public land was created by extracting all publicly-owned lands and otherwise protected open space from SWReGAP stewardship data. A Euclidean distance function was used to generate a proximity index from public lands. It is assumed by FSP that private lands in closest proximity to public lands are of higher priority because they could augment existing open space and avoid piece-meal conservation strategies. Areas of high species diversity is not a common SAP data layer, but as an associated product of SWReGAP, species richness data were included in the SAP model as this provides additional information related to resource richness of a given area.

Table 1. Spatial data layers and data sources used for the Spatial Analysis Project in Utah.

Spatial Analysis Project Common Data Layers:

Data Source:

Forested areas

SWReGAP Land Cover

Riparian areas

SWReGAP Land Cover

Wetlands

SWReGAP Land Cover

Forest patches (road-less areas)

SWReGAP Land Cover/Utah Automated Geographic Reference Center (AGRC) roads

Proximity to public land (protected open space)

SWReGAP Stewardship

Analysis mask (privately-owned forests)

SWReGAP Land Cover/Stewardship

Areas of high species diversity*

SWReGAP Species Richness

(*Not a common SAP data layer.)

Priority watersheds

USGS National Hydrological Dataset

Slope

USGS National Elevation Dataset

Forest pests

UT Div. of Forestry, Fire, & State Lands

Public water supplies

Wildfire assessment

Existing FSP plans

T & E species

UT Div. of Wildlife Resources

Change in households (developing areas)

U.S. Census Bureau


FSP Suitability Analysis: Model Building

The FSP suitability model was created using ArcGIS 9 Spatial Analyst Extension and Model Builder (ESRI 2005). The model was designed to be flexible so input variables could be added or removed and parameters within data layers could be rescaled (i.e., recoded) by UDFFS depending on their specifications. Figure 1 is an overview of the FSP suitability model, which because of its graphical nature, allows the GIS analyst to see every initial data input (blue ovals) and intermediate calculation (yellow rectangles). The final column of intermediate output files (green ovals) are the input predictor variables for the Weighted Overlay tool, which executes the suitability analysis (Figure 1). The Weighted Overlay tool requires all input data to be in raster format and represent categorical data. The Weighted Overlay tool allows the analyst to; 1) set the relative importance that every input data layer has on the suitability analysis by assigning weights (or “percent of influence”), and 2) to scale (or “rank”) the categorical values within data layers (Figure 2). Figure 2 shows the interface of the Weighted Overlay tool where weights (% Influence) and scaled values are adjusted between and within input data layers, respectively. The RS/GIS lab assigned equal influence to every data layer in the preliminary model. Values within the data layers were scaled such that areas with “no data” were given the lowest value (i.e. scaled value of 1), and the single true value was given the highest value (i.e. scaled value of 12) to reduce bias between or within data layers. Scaled values were based on the default evaluation scale of 1-to-12-by-1, which is determined by the number of input data layers to the Weighted Overlay. Finally, the “overlay” procedure multiplies across all given weights and scaled values to produce a map of suitability (Figure 3). Figure 3 shows a preliminary map output of privately-owned forested lands with potential to benefit from the FSP in Utah.

Figure 1. FSP suitability graphical model developed using Model Builder (ESRI 2005) for UDFFS. All input data are on the left (blue ovals), followed by a series of intermediate data manipulations and calculations (yellow rectangles) and temporary output files (green ovals) that converge into the Weighted Overlay tool to derive the map output for the suitability analysis (final green oval).

 

 

Figure 2. The interface for the Weighted Overlay tool is used to assign weights (% Influence) between each input raster data file and to scale (or rank) the values within the data files. All input raster files received an equal percent of influence in the model. Field values of 1 (or 2) were given the highest scaled value (i.e. scaled value of 12) while areas of “no data” were given the lowest scaled value (i.e. scaled value of 1) based on the Evaluation scale of 1 to 12 by 1.

Map Products and Deliverables

All of the original data layers (Table 1) and customized graphical models (Figure 1) were provided to UDFFS in a geodatabase format (ESRI 2005). Graphical models provide an excellent record for tracking how alternative scenarios are derived. Additionally, the models are easily manipulated enabling rapid data exploration and display capabilities.

USFFS will generate several map products from SAP. The primary map product depicts areas with high, medium, and low potential to benefit from FSP planning efforts constrained to privately-owned forested lands (Figure 3). These types of maps provide valuable context for more intuitive decision-making regarding where to apply additional conservation efforts. They also depict to what degree the State’s existing stewardship tracts overlap with “priority” lands (i.e., areas with high potential to benefit from FSP), and whether a re-evaluation of the existing network of conservation plans is needed. Other map outputs from SAP depict areas of resource richness and resource threats constrained within privately-owned forested lands. Models used to create these maps can be adjusted in the same manner as described for the FSP Suitability model.

Figure 3. Example map output of privately-owned forested lands with potential to benefit from FSP in Utah (ranked as high, medium, or low potential). The red triangles represent locations where stewardship plans are currently in place. (This map was derived from a preliminary model prior to formal UDFFS analysis and is for illustrative purposes only.)

Summary

The FSP’s SAP provides states with a consistent methodology for conducting statewide assessments of privately-owned forested lands that could benefit from FSP efforts. SWReGAP data provided several core data layers for these analyses. The RS/GIS Laboratory at Utah State University prepared the required data sets and developed the graphical spatial models to provide UDFFS with decision-making tools that promote the sustainable management of our nation’s forests.

Literature Cited

ESRI, Inc. 2005. ESRI ArcGIS Desktop, Version 9.1. Redlands, CA.

USDA Forest Service. 2005. The Forest Stewardship Program: Helping Private Forest Landowners Develop Plans for the Sustainable Management of their Forest. Available ONLINE: http://www.fs.fed.us/spf/coop/programs/loa/fsp.shtml [as of 21 Apr. 2006].

Western Forestry Leadership Coalition (WFLC). 2004. Spatial Analysis Issue Brief #1. Available ONLINE: http://www.wflccenter.org/news_pdf/75_pdf.pdf [as of 21 Apr. 2006].

 

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