Lab 7 Network Analysis

The goal of this lab is to become familiar with the process of network analysis. In this scenario, students will be evaluating the impact of frac sand transportation on local roads. Students will be calculating routes from sand mines to the nearest railroad terminals and calculating the impact cost for these trips.


Methods


Data for this lab: ESRI street map USA (used for network dataset)

Routes for the frac sand transportation were calculated using a closest facilities network layer. This layer calculates the nearest facility (rail terminal) from the incident (sand mines). Once the routes were created, routes needed to be separated by county in order to calculate the impact cost. The model below uses the clip tool to separate each county's routes from the closest facilities layer.

The model is using the closest facility layer as the input feature and each individual county as the clipping feature. This produces a line feature for each county. By using the measuring tool, the mileage of each county's routes can be calculated for the impact cost analysis.

Route Length by County

Barron County - 16.778 mi
Chippewa County - 28.082 mi
Eau Claire County - 21.792 mi
Trempealeau County - 25.123 mi
Jackson County - 5.483 mi

The lab has students assume that each sand mine takes 50 trips per year to the rail terminal and then back to the mine. Also, the hypothetical costs per truck mile is assumed to be 2.2 cents.

The equation that I used to calculate impact cost can be found below.

Mileage x 100 x 2.2 / 100 = Impact Cost



Results

Impact Cost

Barron County - $36.91
Chippewa County - $61.78
Eau Claire County - $47.94
Trempealeau County - $55.27
Jackson County - $12.06

After conducting network analysis on the impact of frac sand transportation, Chippewa County is impacted the most. Even though Chippewa County has two sand mines which are located closest to the rail terminal, the sand mine located in Barron County is responsible for most of the transportation through Chippewa County. If the Barron County sand mine trucks are responsible for most of the impact cost of Chippewa County, should Barron County also be responsible for paying that impact cost? Would it be reasonable for the Barron County trucks to take alternating routes through Dunn County instead of only using Chippewa County roads? Eau Claire County has the third highest impact cost, and that county doesn't even contain a sand mine! Frac sand mining affects not only the environment, but also local government, the economy, and local roads.

Data Downloading, Interoperability, and Working with Projections

Goals and Objectives

The goal of this exercise is to become acquainted with the process of downloading data from various internet sources, importing the data into ArcGIS, joining data, projecting data from these sources into one coordinate system and constructing a geodatabase to store and edit the data.

Methods

Data for this lab was obtained through many different web services, such as the USGS National Atlas, the USGS National Map Viewer, USDA services, and many others. A shapefile of US railroads was downloaded from the National Atlas data and documentation service. The USGS National Map Viewer was used in order to obtain both NLCD 2006 Land Cover Data and a National Elevation Dataset (1/3 arc Second) for Trempealeau County, Wisconsin. The USDA Geospatial Gateway was accessed in order to acquire Land Cover Cropland Data for the state of Wisconsin. By using the USDA NRCS Web Soil Survey, SSURGO data was downloaded and retrieved with the help of Microsoft Access. All the different data layers can be viewed at once in the map below.

 

 

 

 

 

 

 

 

 

Exercise 6: Geocoding Fac Sand Mines in Northwestern Wisconsin

Goals and Objectives

The goal of this lab is to become acquainted with the process of geocoding. Geocoding is a geographic technique which finds latitude and longitude coordinates from other geographic data, ZIP codes, street addresses, or PLSS. Students will use ArcMap as the geocoder in order to complete this task. Students will be supplied with a table containing address data for frac sand mines in Northwestern Wisconsin. However, these addresses are incomplete and will require some research in order to locate the mine on an aerial image.

Methods

The first objective in the lab has the student download a file geodatabase for Trempealeau County, Wisconsin. After this data has been explored, we will also download a spreadsheet containing recent locations for frac sand mines in Wisconsin. Upon opening the spreadsheet, it becomes apparent that the formatting of these addresses is not consistent. Some addresses only contain town names, some only contain highway names, and others are left completely blank. It is our goal to research these mines and fill in the table as best as possible in order for geocoding to work successfully.  

The four vital pieces of information we need for geocoding are the facility address, city, zip code, and state. Once this information has been gathered we can begin the geocoding process. One method of geocoding automatically guesses the correct location by using the four vital pieces of information while the other method allows the user to manually place each point instead. Since we have a table that is almost complete with address data, we will let the software guess based on the information we have provided. ArcMap allows us to import our table and apply the geocoding wizard to use certain fields for address location. The geocoding wizard will then return a shapefile with possible candidates for each mine from the original table. If everything works properly, each point should be placed at each property.

 

 

Errors are common during this step, and require that the points be manually placed instead. With the help of an aerial image, manually placing address points can be very accurate once the location and general appearance of the target is known.

 

 

Once all mines were properly located by geocoding, all students submitted their results in the form of a shapefile. Each student’s mines were then merged with eachother to display all the geocoded results from the class. A point distance tool was used to generate a table measuring the distance between each of the mine locations in relation to the rest of the class.

Results

 

 

 

 

 

Discussion

Errors that occurred in this lab are both inherent and operational. Since geographic data is only a representation of the real world, all data is collected, generalized and then symbolized. Taking data from the surface of a spheroid and attempting to translate it onto a 2D surface will never be perfect.  No matter what instruments or procedures are used during data collection, inherent errors will occur naturally. Operational errors occur because of mistakes made by the instruments, processes, or the operator. Slight imperfections in data collection, human bias, table digitizing, and data entry are all considered as operational errors. Errors that resulted in the distances in the point table can mostly be categorized into operational errors. The geocoding tool relied on the user for complete address data in order to find the correct location on the map. The correct placement of each geocoded point relied on the user for confirmation. If the location of a point is not near the target location then it is the fault of the user, not the nature of the geographic data. The best way to investigate which points are correct or incorrect would be to display them over an aerial image and view where some of the locations were placed. Mines are easy to spot using aerial imagery, and google searches can be used to acquire more information regarding the name and address of the mine.

Conclusion

Geocoding is a powerful tool when appropriate data is supplied. With the help of a fully normalized address table, geocoding services within mapping software can pinpoint the locations of the target entities. Operational errors are inevitable, proven by the varied data points supplied by the class.

Intro to Frac Sand Mining

Hydraulic fracturing, or fracking, is the process of using a highly pressured liquid to fracture rock. Sand and water are blasted at high pressure down a wellbore in order to cause oil or other precious resources to surface and become usable. The desired sand is mostly quartz and extremely hard, which makes it great for expanding small cracks in bedrock and replacing the resources after they surface. Due to the unique geological landscape that was created by glaciers, Central and Western Wisconsin have some of the best sandstone formations in the United States. Both the creation of jobs and destruction of natural resources make frac sand mining a controversial issue in Wisconsin.

The mining of frac sand has a number of environmental impacts that affect the life and landscape around us. Before the frac sand is blasted, it must be handled and processed at a facility. This can cause the air to be polluted with harmful dust particles that can travel long distances. Sand mines also come into contact with water frequently, which raises the hazards for Wisconsin’s precious freshwater features. Altering riverbeds can change deposition characteristics and increase erosion, which could ultimately damage aquatic habitats.

It is possible to closely examine and explore the, efficiency, cost and overall impacts of frac sand mining by using GIS.

Sources

http://wisconsingeologicalsurvey.org/pdfs/frac-sand-factsheet.pdf

http://dnr.wi.gov/topic/Mines/documents/SilicaSandMiningFinal.pdf