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Land Assessment

 

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Chapter 4 - Methodology

Data Acquisition  |  GPS Ground Truth Data Acquisition  |  Image Preprocessing  |  Image Classification  |  Change Detection  |  1984 Land Use & Land Cover Map  |  Data Conversion  |  Land Assessment  |  Hardcopy Map Production

Land Assessment

Once the areas which had experienced forest to pasture conversion were delineated, an additional assessment of the land was undertaken to determine the wisdom of such land use practices. Specific data layers were incorporated in order to determine a baseline for land suitability as a result of its altered land use and land cover. The land suitability baseline incorporated 3 parameters: slope, erodibility, and land productivity (Prime Farmland Designation). These parameters were derived from specific data layers such as a 30 Meter Digital Elevation Model (DEM) and SSURGO Soils Data.

The slope map was derived from the 30 meter DEM in Arcview and converted from a raster format to vector polygons to coincide with the soils data. Three slope classes were designated:

     0 – 6 Degrees (Nearly Level to Gently Sloping)

     7 – 14 Degrees (Moderately to Steeply Sloping)

     > 14 Degrees (Excessive Slope)

These slope classes were derived from prior research concerning land use and land cover change in the Buffalo National River (Scott & Hofer, 1995). The slope classifications for Carroll County are presented in Map Foldout 4.2.

Map Foldout 4.2 (click to view full version)

The following two data layers were obtained from the SSURGO Soils Data. Such data is important and useful for the evaluation or prediction of suitabilities, limitations, or potentials of soils for a variety of uses. Soil survey data comprise a growing number of geographic information systems and models that deal with regional planning, erosion prediction, crop yields, and even modeling global change. Soil interpretations provide information on the likelihood that an area is suitable for a particular land use; and, thereby, they are valuable for screening areas for a planned use. The likelihood is normally expressed as a suitability or a limitation. As a result, alternative management decisions can be derived from soil behavior information (Vrana, 2000).

Generally, the preparation of soil survey data involves the following steps:

      (1) assembling information about the soils and the landscapes in which they occur,

      (2) modeling other necessary soil characteristics from the soil data,

      (3) deriving inferences, rules, and guides for predicting soil behavior under specific land uses, and (4) integrating these predictions into generalizations for the map unit (Vrana, 2000).

The first data layer obtained from the SSURGO soil survey data is the Highly Erodible Land (Mapunit HEL, Class Water) Classification. This data layer was created in order to identify areas on which erosion control efforts should be concentrated in a particular area of study. The definition is based upon erosion indexes derived from specific variables of the Universal Soil Loss Equation (Wischmeier & Smith, 1978) and the Wind Erosion Equation (Woodruff & Siddoway, 1965). The indexes are the quotient of tons of soil loss by erosion predicted for bare ground divided by the sustainable soil loss (T Factor) (U.S Dept. of Agriculture, 2000). The rating is based on an evalutation of the water erosion hazard of the components of the map unit. If all components are of a single class, that class applies, if not then a 2 (Potential Highly Erodible) is assigned (U.S. Dept. of Agriculture, 1995).

The Highly Erodible Land Categories are listed as follows:

      1: Highly Erodible Land

      2: Potentially Highly Erodible Land

      3: Not Highly Erodible Land

The Highly Erodible Land Classification for Carroll County is presented in Map Foldout 4.3.

Map Foldout 4.3 (click to view full version)

The prime farmland classification (Mapunit primfml) is the second dataset obtained from the SSURGO data. Soil surveys in agricultural areas identify the soil characteristics that determine the suitability and potential of soils for farming. Interpretations for farming involve placement of the soils in management groups (land capability system) and identification of the important soil properties that pertain to crop production, application of conservation practices, and other aspects of agriculture.

These other aspects of agriculture include: yield potential, susceptibility to erosion, depth to layers that restrict roots, available water capacity, saturated hydraulic conductivity, the annual pattern of soil-water states (including soil drainage class, inundation, and free water occurrence), qualities that describe tilth, limitations to use of equipment (including slope gradient and complexity, rock fragments, outcrops of bedrock, and extremes in consistence), salinity and sodium adsorption ratio, presence of toxic substances, deficiency of plant nutrients, capacity to retain and release plant nutrients, capacity to retain soluble substances that may cause pollution of ground water, capacity to absorb or deactivate pesticides, and pH as related to plant growth and need for liming (Vrana, 2000). The identification of these critical soil properties as related to resource management systems is crucial in the wise use of the land.

This system classifies soils for mechanized production of the more commonly cultivated field crops such as corn, small grains, cotton, hay, potatoes, and field grown vegetables. For this research, the cultivated field crop of focus is hay production for cattle feed. The following prime farmland classifications are derived based on the previous criteria of the map units.

     1: Not Prime Farmland

     2: All Areas Are Prime Farmland

     3: Only Drained Areas Are Prime Farmland

The Prime Farmland Classifications for Carroll County are presented in Map Foldout 4.4.

Map Foldout 4.4 (click to view full version)

The suitability baseline for land assessment was created in ArcView by cross-tabulation of each of the three baseline parameters overlain upon the land use and land cover change map. Essentially, three new data layers were created by this overlay operation:

      1: A slope classification of cleared forest areas

      2: An erodibility classification of cleared forest areas

      3: A land productivity classification (Prime Farmland) of cleared forest areas

Each of these new data layers are characterized by the classifications previously listed for each component of the land suitability baseline for areas classified by satellite imagery as cleared forest.

The Tabulate Areas analysis function in Arcview compares two active themes (data layers) and creates a table comparing the themes’ characteristics or classes. A total of three cross-tabulations were computed in order to compare all three data layers incorporated in the land suitability baseline. They are as follows:

     1: Slope & Erodibility of Cleared Forest Areas

     2: Slope & Land Productivity (Prime Farmland) of Cleared Forest Areas

     3: Land Productivity (Prime Farmland) & Erodibility of Cleared Forest Areas

The resulting tables and overall assessment of the forest to pasture converstion are presented in Chapter 5, Results and Analysis.