Map of the Farmland Values Project Study Area, which includes Buncombe, Haywood, Henderson and Madison Counties in WNC.

Map of elevation in the study area, on top of a hillshade derived from a USGS 30m Digital Elevation model (DEM).

Derived from a 1 km Landscan population dataset, published by ties all cells as rural or urban based on pohe Oak Ridge National Laboratory (ORNL). This grid classifpulation per square mile.

Our farmland layer includes all parcels enrolled in their county's Present Use Value (PUV) program as of January 2009 and allareas with Land Use/Land Cover classes (USGS 2001) that indicate the presence of farming (crops, pasture, erc.).

Parcels enrolled in Buncombe County's Present Use Value (PUV) tax program. Dataset includes separate classes for Agriculture, Horticulture, and Forestry (January 2009).

Parcels enrolled in Haywood County's Present Use Value (PUV) tax program (January 2009). Data is broken down into six categories (A, F, H, AF, AH, FH) to show parcels that fall into more than one use category.

Parcels enrolled in Madison County's Present Use Value (PUV) tax program for Agriculture, Horticulture, or Forestry (January 2009). All uses are represented in one category (A-F-H).

Important places identified in a FVP community mapping activity. Participants used Google Earth to locate important places and rank them on a 1-5 scale for scenic and cultural value.

Hotspots of scenic and cultural value, based on a nearest neighbor hierarchical spatial clustering analysis of the point data collected in the FVP community mapping activity.

Proportional Circles are based on scenic values (1-5) assigned by participants of community mapping activity. Larger circles represent higher scenic value.

Proportional Circles are based on cultural values (1-5) assigned by participants of community mapping activity. Larger circles represent higher cultural value.

Slope data derived from USGS Digital Elevation Model (DEM).

Aspect data derived from USGS Digital Elevation Model (DEM).

Soil Survey conducted by the Natural Resources Conservation Service (NRCS) in each of the four counties. Buncombe County is used as an example here.

USGS 2001 Land Use/Land Cover data derived from satellite imagery for the National Land Cover Database (NLCD) and classified into landcover types. 14 land cover types are present in our study area.

Population data is derived from Oak Ridge National Laboratory's (ORNL) 2003 LandScan 1 km. dataset. Values are converted to population per square mile.

Cadastral data is maintained by each county. Each parcel is linked to an database which stores information about each parcel, including ownership, acreage, and property value. Haywood County is shown here as an example.

Places identified as having scenic and/or cultural value in a community mapping activity. Participants used Google Earth to locate important places and rank them on a 1-5 scale for scenic and cultural value.

Generated from a soil survey conducted by the Natural Resources Conservation Service (NRCS) in combination with slope and aspect from the USGS DEM. Soils with the least potential for agriculture (shallow, well drained soil in areas with steep slope) are given a value of 1 in the TVAL-Farm model, and soils with the highest potential for agriculture (deep, loamy soils with gradual slope) are given the highest value of 5.

USGS Landuse/Landcover types are assigned a ranking of 1-5 for the TVAL-Farm model, with 1 representing lands that have a low likelihood of development (or are already developed) and 5 representing lands under the greatest development pressure.

LandScan population data is classified it into five population density categories for the TVAL-Farm model, ranging from least dense (Wildland) to most dense (Urban). Lands in the Wildland-Urban Interface are subject to the highest development pressure and are assigned a value of 5 in our model. Rural and Wildland areas are assigned values of 4 and 3, respectively, while suburban and urban areas are assigned values of 2 and 1.

Land value is derived from tax parcel data published by each county in our study area (September 2008). The assessed value of each parcel was interpolated to a grid file format and classified in 5 groups for the TVAL-Farm model. Land with a value of 5 is the least expensive (and thus, the most vulnerable to development). The most expensive land is assigned a value of 1.

Grid file derived from point data collected in a FVP community mapping activity (2008). Respondents assigned a value of 1 to areas with the lowest scenic value, and a value of 5 to areas with the highest scenic value. Rankings were converted to a continuous surface for the TVAL_Farm model using the IDW (inverse distance weighted) method. 5 represents the highest scenic values.

Grid file derived from point data collected in a community mapping activity (2008). Respondents assigned a value of 1 to areas with the lowest cultural value, and a value of 5 to areas with the highest cultural value. Rankings were converted to a continuous surface for the TVAL_Farm model using the IDW (inverse distance weighted) method. 5 represents the highest cultural values.

The traditional LESA model includes the following variables (our example shows them weighted equally):

Land Use/Land Cover 25%
Ag. Soils Potential 25%
Population 25%
Land Value 25%

The Farmland Values Project's scenic value layer is added to the traditional LESA model in the following weighting scheme:

Land Use/Land Cover 15%
Ag. Soils Potential 15%
Population 15%
Land Value 15%
Scenic Value 40%

The Farmland Values Project's cultural value layer is added to the traditional LESA model in the following weighting scheme:

Land Use/Land Cover 15%
Ag. Soils Potential 15%
Population 15%
Land Value 15%
Cultural Value 40%

Adding both the scenic and cultural value layers to the tradtional LESA model produces the TVAL-FARM model. This example shows all layers weighted equally:

Land Use/Land Cover 16%
Ag. Soils Potential 16%
Population 16%
Land Value 16%
Scenic Value 18%
Cultural Value 18%

A variation on the TVAL-FARM model where the weighting scheme reflects the preferences of FVP survey respondents (according to the Rank Importance question of our 2007 survey):

Land Use/Land Cover 9%
Ag. Soils Potential 37%
Population 9%
Land Value 9%
Scenic Value 18%
Cultural Value 18%

A variation on the TVAL-FARM model where the weighting scheme reflects the preferences of FVP survey respondents (according to the Choice Model section of our 2007 survey):

Land Use/Land Cover 11%
Ag. Soils Potential 23%
Population 11%
Land Value 11%
Scenic Value 22%
Cultural Value 22%