3. DATA

Data:

A. Land Use/Land Cover

B. Soils

C. Hydrology

D. County Digital Orthophotos

E. Digital Elevation Model

F. County Boundary

G. Estimated Territorial Jurisdictions

H. Streets

I. Floodplain

Sources:

A. Land Use/Land Cover- GeoCommunity

B. Soils- National Resources Conservation Services

C. Hydrology- Capital Area Planning Council (CAPCO)

D. County Digital Orthophotos- City of Georgetown

E. Digital Elevation Model- Texas Natural Resources Information System (TNRIS)

F. County Boundary- National Resources Conservation Services

G. Estimated Territorial Jurisdictions (ETJ)

H. Streets- City of Leander

I. Floodplain- FEMA

Data Quality:

A. Land Use/Land Cover- This data set is out of date but it is the only one available to the public. It was created as a general classification with very little detail. The lack of quality and detail of this data set serves as motivation for this project.

B. Soils- This data set is of high quality. The attribute information associated with this data is extremely valuable for analysis. This soil survey is classified with great detail allowing for a detailed analysis.

C. Hydrology- This data set is accurate and from a reliable source.

D. County Digital Orthophotos- This data set is of high quality. These are aerial photos from the City of Georgetown GIS department. The photos were taken in 2002 so the data is relatively up to date. The resolution is two feet making it an excellent source for visualization.

E. Digital Elevation Model- This data is accurate and from a reliable source.

F. County Boundary- This data set is accurate and from a reliable source.

G. Estimated Territorial Jurisdiction- This data varies between secondary data and primary data. The larger cities had ETJ’s available while the smaller cities had to be calculated using a formula. The formula is as follows: An area of half a mile from the city limit for cities with less than 5,000 inhabitants. An area of one mile from the city limit, for cities of 5,000 but less than 25,000 inhabitants. An area of two miles from the city limit, for cities of 25,000 but less than 50,000 inhabitants. An area of three and a half miles from the city limit, for cities of 50,000 but less than 100,000 inhabitants. Finally, an area of five miles from the city limit, for cities with 100,000 or more inhabitants. This formula was taken from http://www.capitol.state.tx.us/statutes/lg.toc.htm under the ETJ heading. This method is a rough estimate of the ETJ and is not as precise as the actual ETJ boundary defined by the city.

H. Streets Layer- This data set is very accurate. It was provided by a representative of the City of Leander GIS department. These data were updated in September of 2004 so they are up to date. When compared to digital orthophotos the streets matched up with great accuracy.

I. Floodplain- This data is accurate and from a reliable source.

3.1 Urban Development

The data used for urban development suitability were land use land cover, roads, soils and floodplains. All the selected data for the entire project was transformed into a common projection in ArcCatalog. According to Roger Tomlinson, a GIS scientist who wrote “Thinking about GIS”, projection change functions allow you to alter the map projection being used to display a data set (Tomlinson, 2003). The projection chosen for this research is North American Datum 1983 Universal Transverse Mercator Zone 14 North coordinate system. The Universal Transverse Mercator is a family of coordinate system optimized for 60 north-south zones around the globe so that it has minimal distortion within a single zone (Price, 2004). It is implied that all the data used and further mentioned in this paper have a common projection that we assigned.

We obtained the land cover/land use shapefile data from webgis.com website. The Land Use and Land Cover (LULC) data files describe the vegetation, water, natural surface and cultural features on the land surface. The United States Geological Survey (USGS) provides these data sets and associated maps as a part of its National Mapping Program. The LULC mapping program is designed so that standard topographic maps of a scale of 1:250,000 can be used for compilation and organization of the land use and land cover data. The LULC dataset was used for vector analysis. The quality of this dataset was very good.

The road data was acquired from the Environmental Systems Research Institute (ESRI) as a shapefile. The quality of this dataset was very good as all the major roads in Williamson County were included. In the first part of the analysis, road datum was used in vector format in order to obtain a buffer further explained in the methods section below. In addition, map information about a recently approved new toll roads construction in Williamson County such as State Highway 130 was obtained from Texas Toll Ways of Texas Department of Transportation. We digitized this new road map adding the road data in order to consider both existing and future major roads. This created new attributes for this dataset as a result we compiled new metadata.

Soil data was captured in vector format as a shapefile from the Soil Survey Geographic (SSURGO) database website and compiled by USDA - Natural Resources Conservation Service. The quality of the data was excellent as all soil units are present in the attribute table. The map extent for a Soil Survey Geographic (SSURGO) dataset is a soil survey area, which may consist of a county, multiple counties, or parts of multiple counties. A SSURGO dataset consists of map data, attribute data, and metadata. SSURGO map data are available in modified Digital Line Graph (DLG-3) optional, Arc interchange file and shapefile formats. Attribute data are distributed in ASCII format with DLG-3 map files and in Arc interchange format with Arc interchange map files. Metadata are in ASCII format.

The floodplain data was obtained and compiled by FEMA. The dataset came in vector format as a shapefile. The data also contains information of the 100-year flood history for Williamson County. The quality of the data is very good in that the entire attributes table for this dataset show that the floodplain areas of Williamson County require mandatory flood insurance purchase requirements.

3.2 Agriculture

The soils data from the National Resources Conservation Services and Table 5 and Table 6 from the Soil Survey of Williamson County, Texas were the only data used in the analysis of agriculture suitability in Williamson County. The soils data was created from extensive analysis from the National Resources Conservation Services. When conducting an agriculture suitability analysis, many properties must be considered to assess the land’s capabilities for agriculture. The soils data was categorized by soil units. Soil units are assigned based on numerous properties. The properties that were assessed were as follows:

• Grain Size- Measured by diameter of grains
• Depth- Measurement of soils depth into the ground
• Infiltration- The downward entry of water into the immediate surface of soil
• Permeability- Ability of soil to transmit water or air (Rate of downward movement when soil is saturated)
• Slope- Degree of ascent or descent of land
• Runoff- The precipitation discharged into stream channels
• Erosion- The wearing away of the land by water, wind, ice, or other geologic agents
• Water Capacity- Quantity of water the soil is capable of storing for use by plants
• Texture- Percentage of sand, silt, or clay
• Soil Reaction- Amount of alkalinity or acidity in the soil (ph value)
• Shrink-swell potential- Potential for volume change in a soil with the gain or loss of moisture
• Organic Matter- Plant and animal residue in the soil at various stages of decomposition
• Bed Rock- The solid rock that underlies the soil and other unconsolidated material or that is exposed at the surface
• Climate- Seasonal weather patterns
• Flooding- The temporary inundation of an area
• Parent Material- The unconsolidated organic and mineral material in which soil forms

Understanding the soil codes and their relationship to these properties was the key to using the analysis that went into creating the data. Estimated yields per acre for cotton, grain sorghum, pasture, and rangeland were used in conjunction with the soils data to perform the analysis.

3.3 Recreation

The purpose of our study is not to break down the county by each of the recreation types but to show all areas of the county that are suitable for any type of recreation. Based on the table in the Soil Survey, we came up with a standard to rate each of the soils by recreation type. All of the soil types were classified from one to three by how suitable each soil is for each of the recreation types, with a rating of one meaning the soil slightly affects the recreation type and three meaning the soil severely limits that type of recreation. The results were then averaged for each soil type and those types scoring higher than two were excluded as being too expensive to amend for a multi-use recreation development 2 (see table 2). A multi-use recreation area would support each of the recreation types listed in the table below.

Table 2 – Suitable Soils

Note: These soils scored less than two when averaged across the recreation types. Fifteen soil types were selected based on these criteria.

Our intent is to show total recreation suitability for the county so multi-use facilities can be designed. Factors determining the usefulness of each soil type for recreation are based on how expensive the soils are to properly amend for general recreation use. Also considered was the fact that an area suited for hiking trails may be very steep and rocky, hence it gets a low amendment requirement score. However, the same area may be totally unsuitable for one of the other recreation types, giving it a high overall score and rendering it unsuitable for general recreation development.

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