Ex 8 Raster Modeling

Raster Modeling

Goal and Objectives

     The goal of this final exercise is to use various geoprocessing tools, such as euchlidean distance, reclassify, raster calculator, filter, topo to raster interpolation, and viewshed, to create a suitability model and a risk model for sand mine locations. The suitability model will include factos such as geology, landcover, slope, distance to rail terminals, and depth of water table. The risk model includes factors such as distance from streams, farmland quality, distance from populated areas, distance from schools, and distance from designated wildlife areas. After the two models are created I will combine them using raster calculator and remove any areas that fall in exclusionary zones, such as residential areas. Finally, I will calculate a viewshed of cemeteries in the study area using a DEM to determine ares that are visible from cemeteries.

Methods

     The process of locating the best location for sand mines is broken down into two main steps. First I will create a suitability model which determines the best location from the perspective of sand mining companies. Suitability is classified as 3 for high suitablity, 2 for medium suitability and 1 for low suitability. Then I will create a risk model to determine locations that pose a significant threat to the general public and the environment. Risk is classified as 1 for high risk, 2 for medium risk, and 3 for low risk.

Suitability Modeling

Figure 1  Data flow model of the process used to determine suitable locations from the perspective of a sand mining company.

Figure 2 Factors that were used to create the suitability model and the ranks that were used to classify each criteria.

     Geology is an extremely important factor in determine where sand mines should be located (Figure 3). Since fracking operations need a very specific grain size it is important to place a mines in those areas. In this case the most desirable geologic formations in the Wonecon Formation and Jordan Formation (part of the Trempealeau Group). Therefore, these two geologic formations are classified as a 3 (high suitability). Considering the location of active mines I determined the Eau Claire Formation, Ancell Group, and Prairie de Chien Group also contain sands suitable for fracking operations, therefore they were classified as 2 (medium suitability). Finally, I noticed the Tunnel City Group only contained 1 mine in the area. Based on that information I classified this geologic formation as a 1 (low suitability). 

Figure 3 Map showing the suitability of geologic formations. 

     Landcover is also an important factor in determine suitability of sand mine locations (Figure 4). Areas that are heavily forested will require a significant amount of money to remove the vegetation while shrubland and barren lands will require little to no extra cost to remove vegetation. Therefore, I classified barren land, shrubland, and herbaceous land as having the highest suitability (rank of 3), forested land as medium suitability (rank of 2), and wetlands, developed areas, and open water is low suitability (rank of 1).

Figure 4 Suitability of landcover in Trempealeau County, WI based on the cost require to remove vegetation.

      Distance to rail terminals is also an important factor in assessing sand mine suitability (Figure 5). It will cost the sand mining company a lot less to export the sand if the mine is located closer to rail terminals. Using the Euclidean distance tool and natural breaks I determined the most suitable location was located within 8000 meters of a rail terminal (suitability of 3). Medium suitability (2) was located from 8000-16000 meters from rail terminals. Any location farther than 16000 meters from a rail terminal has low suitability (1).

Figure 5 Suitability ranks based on distance from rail terminals.

Slope is also an important factor in suitability (Figure 6). Areas that have more gradual slopes are easier and cheaper to work on. I calculated slope using the slope tool and a digital elevation model. I then ran a 3 cell by 3 cell low pass filter and reclassified areas with less than 9.8% slope as having high suitability (3), areas between 9.8% and 23.5% slope as having medium suitability (2), and areas that have greater than 23.5% slope as low suitability (1).

Figure 6 Areas with high slope are less desirable than areas with gradual slope.

     The last factor that will be taken into account in determining the most suitable areas for sand mining companies to open new mining operations is depth to water table (Figure 7). Since sand mines require a large amount of water in the processing of frac sands it is imprortant to be located in areas that have shallow water tables to reduce to cost of pumping. I began by downloading water table elevation data from the Wisconsin Geologic Survey website. This data had to be converted into raster format using the topo to raster tool. Then I had to convert the elevation from feet to meters. Finally, I subtracted the water table elevation raster from the digital elevation model to get the actual depth of the water table. I then reclassified the water table depth into 3 classes. Anywhere with a water table less than 10 meters has high suitability, between 10 and 30 meters is medium suitability, and anywhere with a water table depth of over 30 meters has low suitability.

Figure 7 Depth of water table is important in determining where sand mines should be located.

      Using the raster calculator tool we can add up the rankings of the previous 5 factors to give the overall suitability of sand mine locations from the perspective of a sand mine company (Figure 8). Notice that areas with higher depth to water table also have higher slope, more forested landcover, and less suitable geology.

Figure 8 Suitability of sand mine locations from the perspective of a sand mining company.

Risk Modeling

     The goal of the second part of this exercise is to create a risk model based on factors that will be affected by sand mines from the perspective of the community/environment. The most important factors that will be used in determining the risk model include distance from streams, quality of farmland, distance from populated areas, distance from schools, and distance from designated wildlife areas. Areas that have a high risk of being affected by sand mines are given a ranking of 1 and low risk areas are given a ranking of 3.



Figure 9 Data flow showing steps used to create the risk model

Figure 10 Most important risk factors and how they are ranked.

     A very important factor in determining the location of sand mines is the risk imposed on streams. Sand mines could lead to an increase in sediment load in streams which could be detrimental to stream health. Therefore, it is imperative to keep sand mines at a safe distance from streams. Risk ranks were determined using natural breaks of Euclidean distance from streams. The highest risk (1) is located from 0-637 meters from streams. Medium risk (2) is located between 637-1928 meters from the stream. Finally, the lowest risk (3) is located 1928+ meters from streams.

Figure 11 Distance from streams plays an important factor in determining possible sand mine locations that have the least risk to the environment.

Another important factor in determining sand mine suitability is the risk to prime farmland. Since Wisconsin uses a significant amount of cropland to provide feed for livestock and for many other uses it is important to protect prime farmland. Therefore, areas that contain prime farmland have the highest risk factor, while areas that are not prime farmland have the lowest risk. Areas that could possibly become prime farmland if drained have a medium risk value (Figure 12).

Figure 12 Risk associated with quality of farmland.

      Distance from residential areas is another important factor. Since there is a lot of noise and dust caused by sand mining operations it is important to keep sand mines at a safe distance. Therefore, less than 640 meters from any populated area has a high risk factor, between 640 and 3049 meters is considered medium risk, and anywhere over 3049 meters away from populated areas is considered low risk (Figure 13).

Figure 13 Risk associated with distance from populated areas.

      Similarly to populated areas, dust and noise can impose significant risk to school zones. Therfore, it is important to keep sand mines away from schools. Using the sites feature class I selected schools and exported them into the geodatabase. Then, using Euclidean distance to set up a buffer around each school I determined areas that pose the least risk to schools. Areas within 1343 meters of schools have a high risk, areas between 1343 and 2329 meters from schools have a medium risk, and areas over 2329 meters from schools have low risk to school children (Figure 14).

Figure 14 Risk of sand mines to schools

     Lastly, I find it importnt to keep sand mines away from designated wildlife areas to reduce disturbances to important wildlife. Therefore, I used Euclidean distance to create bufferes around designated wildlife areas and reclassified the buffers based on risk to the wildlife. Any area within 1500 meters poses a high risk to the wildlife, areas between 1500 and 3000 meters away pose medium risk, and areas over 3000 meters pose low risk (Figure 15).

Figure 15 Risk to designated wildlife areas

     Using raster calculator we add up the 5 factors above to determine overall risk (Figure 16). Areas with higher risk are less desirable for sand mine locations while areas will low risk are better locations for sand mines.

Figure 16 Overall risk on people and the environment from sand mining

Overlay

     Finally, in order to determine the overall suitability of sand mine we use raster calculator to add the suitability model with the risk model (Figure 17). 

Figure 17 Best locations for sand mines based on suitability and risk.

    

     We must also note that developed areas and open water must be excluded from the suitability model. In order to do this we reclassify landcover based on a pass/fail grade. Areas that are developed or are open water fail and are given a 0 for suitability since sand mines cannot possibly be located there. Any other area is given a 1 since sand mines can be located there. We use raster calculator to multiply the Final Suitability (Figure 17) to the Excluded Landcover raster (Figure 18) to give the Overall Suitability (Figure 19).



Figure 18 Any areas where mines cannot possibly be located, such as cities or lakes, are given a failing grade of 0 while areas were sand mines could be located are given a passing grade of 1.



Results and Discussion

     As you can see from Figure 19 there are a lot of suitable areas for sand mine locations. The northwester portion of the study area has the largest area of suitable land available.

     

Figure 19 Overall best locations for sand mines. Red areas are the least suitable for sand mine locations.

      Other factors could also play a role in determining sand mine locations. For instance, it would not be a good idea to have sand mines located where they are visible to cemeteries or other ceremonial sites. To exclude these areas we develop a viewshed using the location of cemeteries and the Digital Elevation Model of the area. 

Figure 20 Viewshed of cemeteries in the study area.

Conclusion 

     As you can see from Figure 19, there are plenty of viable locations for sand mines to be located. In order to determine the best possible location one must consider several different factors and determine which of those factors are the most important. On the other hand, some factors are going to be ignored when determining the location of sand mines. For example, nobody wants sand mines to be visible from cemeteries but there are more important factors such as stream health or risk to schools and other populated areas.