Raster Analysis of Frac Sand Mine Locations

Introduction

This assignment was the last step in a semester long project involving Frac Sand Mining in Wisconsin. In order to complete this assignment, multiple geoprocessing tools involving raster datasets needed to be used. Multiple models were built, including frac sand mine site suitability model, sand mine risk model and the final result is an overlay of both models to find the most ideal site for a frac sand mine. 

Goals and Objectives:

There were multiple datasets used in this assignment. Many of the data sets were already downloaded from a previous assignment in class. In order to find the most ideal site for a mine, five different raster datasets were analyzed. This included geology, land use land cover, distance from rail road terminals, water table depth, and a digital elevation model (DEM) of Trempealeau county to find the slope. The layers needed to create a risk model included streams, farmland, zoning, schools and proximity to wetlands.  All of these data sets were acquired from the Trempealeau County database used in exercise five, from earlier in the semester. 

Methods:

The first step in this assignment was to clip Trempealeau County by a smaller section. The purpose behind using a smaller section of the county was to speed up the time it took to geoprocess all of the results.  

Figure 1.1 Shows the first model used to create a model of suitable
areas for frac sand mining based on land use and land forms.

This first model (Figure 1.1) was used in order to find the most suitable location for implementing a new frac sand mine. Some of the features had to be projected and another had to be converted into a raster. Without all of these datasets converted to a raster file, the analysis would not have been able to take place. Once all the datasets were reclassified, raster calculator was needed in order to overlay all the results and find the most suitable location to implement a new mine. 

The figure below (Figure 2.1) shows the second model used to create a model showing where frac sand mines should not be implemented. This model used much of the same tools as the first model, but was slightly more extensive. 

Figure 2.1 Shows the model used to create a model of suitable areas for mining based on environmental and community impacts.

The final result of both models combined is shown below (Figure 3.1). 

Figure 3.1 Shows the two models put together.

In order to run all of the tools shown above, different criteria had to be developed. Multiple classes had to be developed in order to run raster calculator effectively at the end of the model. All of the values input into the table were up to the students and what they thought was appropriate. There could be multiple variations due to the open criteria presented to the students. The table that I created shows values that are fairly conservative. If a sand mine was to be created, it would be created in the most optimal location. Figure 4.1 (below) is a table showing the different classification for the criteria used in creating these different models.

Figure 4.1 A table showing the different criteria and parameters used in creating a suitability model for a frac sand mine. 

Results

The results from the data flow models were very interesting. The figures below show the results from the models. 

Figure 5.1 A map showing which areas are the most suitable for implementing a new sand mine based of of land use
and land forms.

Figure 5.1 (above) shows the results of areas where frac sand mining is suitable taking land use factors into consideration. The red color represents areas where the suitibility is exceptionally high. The yellow areas show areas that are the not the best, but could still used for frac sand mining. The green color shows areas that should not be used. Since the criteria that was used for this particular project tended to be strict, there are small amount of land that are highly suitable for mining without affecting many different things.

Figure 6.1 (below) shows the areas that are suitable for mining taking environmental factors into consideration. Green represents areas that could be used for mining. Yellow shows areas that would be suitable for mining if they needed more land. Red shows areas that should not be mined due to their possible impact on the environment.

Figure 6.1 A map showing the areas most suitable for a sand mine base on environmental and community factors.

Figure 7.1 (below) shows areas the are the best to implement a sand mine. This map is the result of overlaying not suitable sites, and suitable sites for a sand mine.  Red represents areas where frac sand mines should be implemented. Yellow shows areas that are average quality and green shows areas that should not be included for the possibility of a mine creation. 

Figure 7.1 A map showing the final results from the two model results overlaid.

There are many areas that are green, but not very many areas that are covered in red. Theoretically this would mean that mines should be created in limited areas. This is not always the case, and sometimes these mines are created in less than ideal locations. Without taking many different factors into consideration, the creation of a mine can cause great effects on a particular are.

Conclusions:

This assignment was the final segment in a semester long project. Although the numbers used in this exercise were generalized and theoretical, the procedure was the most important part. It gave the student exposure to working with raster data and allowed them to analyze the data in a real world application. Frac sand mining will continue to take place in the future, so these models are extremely important. Without taking many different factors into consideration, the creation of a mine can cause great effects on a particular area.

Sources:

Trempealeau County Geodatabase

ESRI Database