Network Analysis

Goals and Objectives

The goal of this exercise was to learn how and perform network analysis in a real life scenario. The example scenario we are considering the transportation of frac sand. We routed the sand from the mines to the nearest railroad terminal. Once that is done we learned how to estimate the number of trips the trucks will take and the cost this traffic will incur on the local roads. We then figured how much each county in Western Wisconsin would have to pay to maintain these roads. This is a relevant example because in the real world frac sand trucking has a significant impact on the local roads. 

Methods 

     The first step in this part of the lab was to bring in the streets network data set for the whole U.S. The next step was to bring in the rail terminals data set. Since we are only interested in the mines that move their sand by truck and rail I did a select by MODE_TYPE and did truck and rail mines. I then took that selection and made a feature class that only has the truck and rail terminals.
     The next step was to do some network analysis. I opened the network analyst window and added a new closest facility layer. I loaded my rail_terminals as the facilities and my mines as the incidents. I then ran a solve this gave the routes from my mines to the closest rail terminal. It appears on the map that there is only one truck on each route but if you select the route there are many records of trucks on each route.
     Next I began to build my model in model builder. I started by recreating the above described routes through use of the make closest facility layer and add locations tools. Just like above I add the solve tool to my model and then run the model. I then used the select data tool to extract my routes from the closest facility solver and save them in my goedatabase. To save them I used the copy features tool.
      Once I had all the routes to the closest rail terminals could then begin to find how much the truck are going to cost the county in road damage. The first thing I did was to find the distance the trucks are traveling. I added a field and called it Miles then I did a calculate field and divided the shape_length field in the route table by 1600. This gives the distance in Miles. Next I added another field called Cost. I took my Miles field and took it times 100 because the trucks make 50 trips. I multiply that by 2.2 cents and then divide that whole equation by 100 because there are 100 cents in a dollar.(See calculations below.) I now had totals for how much each trip cost. The next step is to find out how much each county spent. In order to do this I did a field join between the Wisconsin counties class and my routes class. Once those are joined the final step was to run a statistics summary on the Cost field. I summarized it by county names so it took all the costs for each county name and summed them. The chart in the results section in what that table looks like. Directly below is the model I made and ran to get my desired results.



Model Builder

[SHAPE_LENGTH]/1600 = (x)mi   Then I did.  ((x)mi *100)2.2)/100= cost per trip

Results

After the model is run the map below is the result I got. It shows all the mines we are concerned with in Western Wisconsin as well as the rail terminals. The map also shows all of the routes the trucks are taking from a mine to the nearest rail terminal. 





Final Results Map

The chart below shows the hypothetical cost that sand trucking would cost by county, These number are all made up for a an example, however you can see that there is a cost associated with the transportation of the sand. I would venture to guess that the true numbers for the cost to each county is in the thousands of dollars every year for road maintenance. We only figured the cost for 50 truck trips from each mine in a year when in the real world that can be done in a day. Who should pay to fix the roads? Should the county have to pay for this cost because they are in charge of maintaining the roads or should the sand companies pay for it because they are the reason the road is deteriorating faster than with normal traffic. If the mines have to pay for it, is that fare because there are mines that put the sand directly onto rail and wouldn't have to pay this "road tax". This is a question that has been raised and discussed in depth. It is one of many possible draw backs that people see about frac sand mining. Air quality concerns along these roads is also a topic of discussion. 

Cost by County

Conclusion

The point of this lab was not to look at pros and cons of frac sand mining it was to apply network analysis to a real life situation and understand the results. This is a valuable skill that is widely used in many situations. At a city, county, state, and world scale for emergency response, package delivery, every day use of your GPS to get from point A to point B and countless other situations. I really enjoyed learning this technique. It  was more of a hands on technique and seeing how it can be applied in the real world makes it more interesting and realistic to me instead of just crunching data numbers like some of the other techniques. 

Sources: ESRI Street Map USA