The goal of this lab is to introduce the basics functions of Network Analysis in ArcMap. Sand mines transport their sand in a multitude of ways. Generally all of the sand produced in Wisconsin will have to travel by raiload to leave the state. Many mine sites have a direct access to rail transportation and do not truck the sand via public roadways. However, many of the mines in Wisconsin have to transport their sand a fair distance to reach the railroad terminal.
The Wisconsin Department of Transportation NW Region Planning Staff estimated when the sand mining industry hit full stride it could have the ability to haul approximately 40 million tons of sand a year out of the state of Wisconsin (Hart). The transportation of 40 million tons of sand to the terminals could have a significant impact on the local roadways.
Through the use of the Network Analysis function in ArcMap, I will use hypothetical value of 2.2 cents per mile to calculate the cost of additional maintenance to the roadways by county from sand transportation. We will also be using a arbitrary number of 50 trips per mine to the railway facility. Thus my findings will not be a true reflection of the cost but my methods could be used to calculate the true impact if the proper cost was available.
Methods
Preparation of the feature classes is needed before utilizing the Network Analysis tool. I will be using the mine data received from the Wisconsin DNR which was utilized in the previous lab. Not all of the mines in the data are actively producing or transporting sand. Many of the mines have rail loading stations directly at the mine site and will not be trucking any sand. Additionally, it is highly likely mines within 1.5 km of a railway will have had a spur rail built to transport their sand. I wrote a python script to select all of the active mines, without a rail loading station, and not withing 1.5 km of a railway. In the end I was left with 41 mine which fit my criteria.
I was provided a geodatabase for the lab exercise which contained a feature class of the rail terminals in Wisconsin I was instructed to use for the analysis. I added a street network dataset from ESRI street map USA which was also provided for me.
Utilizing model builder I created a model to calculate the cost of maintaining the roadways from sand transportation (Fig. 1). First I used the Make Closest Facility Layer tool and Add Locations with the mines as the incidents and the rail terminals as the facilities to set up my the network analysis. To actually run the analysis I added the Solve tool to determine the rail station with the shortest drive time from each mine. The next step was to use the Select Data and Copy Features tool to create a feature class from the calculated routes from the network analysis. The calculated route was in a GCS coordinate system which cannot be used accurately for measurement purposes. I brought in the Project tool to project the feature class in to NAD 1983 HARN Transverse Mercator feet to let me achieve accurate measurements and calculations. The next step was to use the Intersect tool to break the routes distance down by county. Since some counties had multiple routes I used the Summary Statistics tool to create a table with the total route distance broken down by each county. With the use of the Add Field and Calculate Field tools I created 2 new fields within the table. The first field I created converted the measurement of the distance from feet to miles. I multiplied the foot distance by 0.00018939 to give me the distance in miles. The second field was the dollar amount calculation of the impact cost of the trucking. The cost of maintaining the road networks was calculated by multiplying the number of trips to the railway station by 2 to account for the return trip to the mine, multiply that result by the miles of the route and finally multiply that figure by .022 (hypothetical cost of maintenance). The equation was displayed like the following in the tool: "2 * 50 * [Dist_Miles] *.022".
 |
| (Fig. 1) Model within ArcMap Model Builder for the creation of the network analysis tool and calculations. |
To better display the results I exported the final table with all of the calculations to an Excel file using the Table to Excel conversion tool within ArcMap. With the table in Excel I was able to create a graph to display the results.
 |
| (Fig. 2) Graphic display of increased maintenance cost of roads due to sand mine truck traffic. |
 |
| (Fig. 3) Additional roadway maintenance cost by county from sand transportation. |
Discussion
The total amount of money is a lot lower than I originally figured. I feel this has to do with the dollar figure we used to complete our calculations and the number of trips per mine. Even if the dollar figure was correct I can almost guarantee the number of trips is higher than 50 trips per year. I would venture to guess that on a good day the number of trips would be 50 per day. Even doubling the number of trips would greatly increase the dollar figure calculated.
The transportation model only used the railroad stations within Wisconsin. Due to an error in my methods early on I found a couple of the mines in the Western part of Wisconsin would save time if they took their sand to railroad stations in Minnesota. Had we utilized the stations in Minnesota this would have change the impact to specific counties in those areas.
Trempealeau county has the highest number of sand mines but does not have high maintenance cost. The cause is a centrally located rail facility which keeps the distance trucks have to travel down. I believe this is one reason why there are so many mines located in Trempealeau county.
The two counties in Northwestern Wisconsin show a cost but there is not a route displayed on the map. The network analysis took the fastest route to get to the rail facility. The majority of the route was in the state of Minnesota. The trucks only traveled a short distance to get out of the state, thus low maintenance cost for the county.
The analysis tool choose the fastest route to from the mine to the railroad. Just because the tool choose this route does not meant the trucks use the determined path. An actual route track from the mining companies would need to be obtained to calculate the true impact to the roads, along with the true dollar figures and number of trips per year.
Conclusion
The network analysis tool has a vast number of uses, and is fairly simple to use if you have a basic understanding of ArcMap. Calculating the shortest or fastest distance is useful but may not always be the route chosen by actual people or businesses. Businesses use this tool to everyday to save money by keeping the miles down on company vehicles thus saving on maintenance and fuel costs. Being the numerical values are hypothetical I cannot derive and true conclusion about the impacts sand mine transportation has on local roadways. There is no doubt in my mine semi transportation has a impact on the longevity of the roadways all across the planet.
Sources
Hart, M. V., Adams, T., & Schwartz, A. (2013). Transportation Impacts of Frac Sand Mining in the MAFC Region: Chippewa County Case Study. In Mid-America Freight Coalition. Retrieved November 11, 2015, from http://midamericafreight.org/wp-content/uploads/FracSandWhitePaperDRAFT.pdf
No comments:
Post a Comment