Exercise 7: Network Analysis

Exercise 7: Network Analysis

Goal/Objective

The most controversial aspect of sand mining in West Central Wisconsin is the effects large trucks will have on local roads. The cost of road construction falls directly on the taxpayers in each county and not on the sand mining companies. Therefore, it is important to calculate to total cost of road maintenance that each county will have to pay for road upkeep. This exercise will help become familiar with some of the network analyst tools ArcMap has to offer and to give a rough estimate of the total cost each county will incur due to the transportation of sand.

Methods

The first step in the process was to write a python script to select mines that meet certain criteria. In this case we want mines that are active and are more than 1.5 km away from any railroad. After these mines were selected they were exported into the geodatabase. Next, we ran the network analyst tool to calculate routes, using ESRI Street Maps USA, from the sand mine to the closest rail terminal facility using the "New Closest Facility" function. After the routes were calculated we exported them into the geodatabase. Exporting the routes created a shapelength field which will be used to calculate distance. Next, we intersected the new routes feature class with county boundary feature class to get the total distance traveled per county. Finally, we used the predefined criteria of 100 trips per mine at 2.2 centers per mile to calculate the total cost each county would incur. Figure 1 below is the data flow model that describes the steps to calculate total cost per county.

Figure 1 Data flow model that shows the steps used to calculate total distance traveled and total cost per county.

Results

Figure 2 shows the routes that were created using the "New Closest Facility" function in the network analyst toolbar. Each mine was routed to the closest rail terminal.

Figure 2 Routes used to transport sand from mines to the closest rail terminal

Table 1 and Figure 3 show the total cost each county would incur if there were 50 truckloads of sand to the rail terminal at 2.2 centers per mile traveled. As you can see Chippewa County has the largest cost at 452.59 dollars. It is interesting to note that although Eau Claire County does not contain any sand mines they will still have a cost of 205.06 dollars.

Table 1 The total distance traveled by trucks in each and the total cost associated.

 

Figure 3 Map showing the total cost each county will incur due to sand transportation.

 

Conclusion

In conclusion, the total amount each county would have to spend to maintain roads is significantly lower than I originally thought it would be. However, this is a rough estimate because not every mine will be using the routes as specified. Some mines will ship their sand to other processing facilities in the area. Another factor that could lead to error is that not every mine will only ship 50 truckloads of sand. Some mines are significantly larger than other and will need more trucks to transport all the sand to the rail terminals. Also, the 2.2 cents per mile traveled may not be accurate. If this price per mile traveled is determined to be higher the cost per county will increase dramatically. Therefore, this lab was interesting to learn how to use different tools ArcMap has to offer, but the results may not necessarily be very accurate.