By the end of Lesson 5, you should be able to:
Lesson 5 will take 1 week to complete. Please refer to Canvas for specific timeframes, submission instructions, and due dates.
To finish this lesson, you must complete the assignments listed below. The details for each assignment are provided in the referenced section and in Canvas.
Assignment No. | Assignment Description | Section | Grade Component / Points |
---|---|---|---|
5-1 | Watch a webinar on using Network Analyst to perform network analysis in ArcGIS and answer some questions. | 5.1 | Lesson Topic / 15 |
5-2 | Complete Exercises 3 and 5 from ESRI’s Network Analyst tutorial and answer some questions. | 5.1 | Lesson Topic / 20 |
5-3 | Explore a state DOT and address some specific questions. | 5.2 | Transportation Organizations / 15 |
5-4 | Participate in a One-on-One video conference with a classmate, and submit a summary of the conversation. | 5.3 | Class Participation / 15 |
5-5 | Participate in this week’s webinar and submit a summary of what you learned. | 5.5 | Guest Webinar / 15 |
5-6 | Review the background material for next week’s webinar and respond to some questions. | 5.6 | Guest Webinar / 10 |
5-7 | Submit 3 - 5 questions for next week’s speaker. | 5.6 | Guest Webinar / 5 |
Network analysis can be used to solve many different transportation problems that would be very challenging to solve otherwise. A prerequisite to performing network analysis is that you have a network model. In ESRI’s terms, this is a network dataset. We walked through an exercise to construct a network dataset in the last lesson. Of course, it is not a requirement of network analysis that you construct your own network model. There are a number of commercially available network models you can use instead.
The types of problems which network analysis can be used to solve are quite varied. One common characteristic of the algorithms that power each is that they involve determining the cost of one or more routes through the network. The cost is most commonly based on time or distance, but you can define a cost attribute any way you want. For example, you might score each edge in the network based on its scenic value. You could then create a cost parameter based on the scenic score and use the solver to find the most scenic route.
ESRI provides 6 out-of-the-box network analyses as a part of Network Analyst. ESRI terms these network analyses “solvers.” The solvers are listed below along with a brief description of each:
The route solver determines the best route between two or more points. Most of us use this network analysis on a regular basis. Whenever you use Google Maps or a comparable service to get directions from one location to another the service is conducting a network analysis to determine the best, typically fastest, route. This solver can route any number of points according to a specified order (i.e., the traveling salesman problem) or the most efficient order.
This solver is used to determine the closest facility to a given location. The term facility can be a bit misleading. For example, this solver could be used to determine the closest ambulance to an accident scene. In this case, using ESRI’s terminology, the ambulances would be considered facilities.
The geographic region which can reach a designated facility in a certain period of time (or vice versa) is termed a service area. To determine the bounds of this area, you can use the Service Area Solver.
The OD cost matrix solver is generally used to determine the distances of the fastest routes between a set of origins and a set of destinations. Although the path between each origin and destination is often represented as a straight line, the route which corresponds to the time and distance costs between each pair of locations follows the street network.
The vehicle routing solver is typically used to determine the most efficient routes for a fleet of vehicles tasked with servicing a series of stops.
The location-allocation solver can be used to determine how effectively a facility site is servicing locations which have a need for its services. As such, it can be used to select the best location for a facility from a series of candidate locations.
Watch this video from ESRI’s 2010 User Conference [2] (71 minutes) which talks about conducting network analyses using the Network Analyst extension to ArcGIS. Address the following questions and submit your responses in the form of an M.S. Word document to Assignment 5-1 in Canvas.
In Assignment 4-2 you downloaded the ESRI ArcGIS Desktop Tutorial Data and completed Exercise 1 of ESRI’s ArcGIS Network Analyst Tutorial. For this assignment, you will complete Exercise 3 and Exercise 5. As you’re completing the exercises, address the following questions and submit your responses in the form of an M.S. Word document to Assignment 5-2 in Canvas.
This week, we’ll take some time to explore state Departments of Transportation (DOTs). All 50 states have a department of transportation and while there are many similarities between them, they can differ in both how they are organized and in the specific functions they perform. A convenient set of links for all 50 state DOTs [3] is maintained by the USDOT’s National Transportation Library.
The origins of most state DOTs trace back to the early 1900s. At that time they were commonly named State Highway Departments and, as the name implies, their focus was almost exclusively on highways. In the 100 or so years since then, their roles have evolved and the responsibilities have increased dramatically. Today, state DOTs typically operate or oversee all modes of transportation within the state and the scope of their functional responsibilities have grown from engineering and construction to include planning, safety, assessment and mitigation of project impacts on the environment and community resources, driver’s licensing and vehicle registration, permitting and providing technical support and oversight for local roads. A good summary of the roles and responsibilities of a state DOT is provided in Chapter 2 [4] of the National Cooperative Highway Research Program’s (NCHRP) Report No. 750 titled “Strategic Issues Facing Transportation, Volume 5: Preparing State Transportation Agencies for an Uncertain Energy Future [5] (2014).”
Given the extensive number of functions a state DOT is responsible for performing, there are a tremendous number of opportunities for applying spatial technologies, some of which we have looked at already (FHWA maintains a searchable compilation of state GIS-T projects [6]). Consequently, state DOTs have a substantial need for GIS expertise although the degree to which these needs are outsourced varies. GIS expertise within the DOT is often housed in their planning or information technology organizations. AASHTO maintains a list of GIS-T contacts [7] for each state.
Spend some time learning about a state DOT of your choice. You may want to begin by reviewing their website. Identify an interesting way the DOT is using spatial technologies. You might choose to review an existing project or GIS application the department uses. Also, do a little research to find out where in the organization structure GIS services and expertise are housed. Prepare a brief summary of what you learned which is no more than 300 words in length and submit it as an M.S. Word document to Assignment 5-3 in Canvas. Include a screenshot or two, if appropriate.
Criteria | Ratings | Pts | ||
---|---|---|---|---|
Followed Instructions | Excellent: Student carefully followed all instructions for the assignment. 4.0 pts |
Satisfactory: Student's submission exhibited some minor deviations from the instructions for the assignment. 2.5 pts |
Poor: Student's submission exhibited major deviations from the instructions for the assignment. 1.0 pts |
4.0 pts |
Content Quality | Excellent: Student's submittal fully addressed the topics of the assignment and demonstrated insight and thoughtful reflection on the part of the student. 7.0 pts |
Satisfactory: Student's submittal partially addressed the topics of the assignment and demonstrated some insight and thoughtful reflection on the part of the student. 5.0 pts |
Poor: Student's submittal did not address the topics of the assignment and demonstrated little or no insight or thoughtful reflection on the part of the student. 1.0 pts |
7.0 pts |
Writing Quality | Excellent: Student’s writing was organized, clear, and concise and was free from spelling and grammatical errors. 4.0 pts |
Satisfactory: Student’s writing exhibited some deficiencies in the area of organization, clarity, and conciseness and/or contained a few spelling or grammatical errors. 2.5 pts |
Poor: Student’s writing exhibited major deficiencies in the area of organization, clarity, and conciseness and/or contained many spelling or grammatical errors. 1.0 pts |
4.0 pts |
Total Points: 15.0 |
This week, you’ll have a one-on-one chat with one of your classmates as per the schedule you were provided in Week 1. The discussion should be at least 30 minutes in length. If it’s the first time you’ve chatted with each other, spend the majority of time getting to know each other. Otherwise, focus on discussing the lesson content.
Submit a brief summary of the conversation (no more than 300 words) as an M.S. Word document to Assignment 5-4 in Canvas. The summary you’ll submit is an individual assignment and is not intended to be a joint activity. If it’s the first time you’ve spoken with each other, your summary should primarily address what you learned about each other (e.g., what do you have in common?). Otherwise, your summary should focus on ideas and insights about the lesson content which came out of the conversation.
Criteria | Ratings | Pts | ||
---|---|---|---|---|
Followed Instructions | Excellent: Student carefully followed all instructions for the assignment. 4.0 pts |
Satisfactory: Student's submission exhibited some minor deviations from the instructions for the assignment. 2.5 pts |
Poor: Student's submission exhibited major deviations from the instructions for the assignment. 1.0 pts |
4.0 pts |
Content Quality | Excellent: Student's submittal reflected a conversation which was highly thoughtful and productive and provided substantial benefit in getting to know each other better and/or exploring lesson topics. 7.0 pts |
Satisfactory: Student's submittal reflected a conversation which was somewhat thoughtful and productive and provided some limited benefit in getting to know each other better and/or exploring lesson topics. 5.0 pts |
Poor: Student's submittal reflected a conversation which had little value in getting to know each other better and/or exploring lesson topics. 1.0 pts |
7.0 pts |
Writing Quality | Excellent: Student’s writing was organized, clear, and concise and was free from spelling and grammatical errors. 4.0 pts |
Satisfactory: Student’s writing exhibited some deficiencies in the area of organization, clarity, and conciseness and/or contained a few spelling or grammatical errors. 2.5 pts |
Poor: Student’s writing exhibited major deficiencies in the area of organization, clarity, and conciseness and/or contained many spelling or grammatical errors. 1.0 pts |
4.0 pts |
Total Points: 15.0 |
This week’s speaker is Mr. Frank DeSendi. For details about Frank’s current role and background, refer to Lesson 4. For the specific date and time of the webinar, please refer to Canvas. While you are expected to attend the webinar live, if at all possible, it is understood that in some cases work schedules and other conflicts may make it impossible to do so. If you will not be able to attend, please send me an e-mail ahead of time. I will make the recorded webinar available for you to review.
After attending the webinar, prepare a brief write-up (250 – 500 words) summarizing the session and submit it in M.S. Word format to Assignment 5-5 in Canvas. In your summary, address the following:
Criteria | Ratings | Pts | ||
---|---|---|---|---|
Followed Instructions | Excellent: Student carefully followed all instructions for the assignment. 4.0 pts |
Satisfactory: Student's submission exhibited some minor deviations from the instructions for the assignment. 2.5 pts |
Poor: Student's submission exhibited major deviations from the instructions for the assignment. 1.0 pts |
4.0 pts |
Content Quality | Excellent: The student's submittal demonstrated that the student paid close attention during the webinar and carefully reflected on the key topics which were covered. 7.0 pts |
Satisfactory: The student's submittal demonstrated that the student was somewhat attentive during the webinar and engaged in limited reflection on the key topics which were covered. 4.0 pts |
Poor: The student's submittal provided little or no evidence that the student paid careful attention during the webinar or reflected on the topics which were covered. 1.0 pts |
7.0 pts |
Writing Quality | Excellent: Student’s writing was organized, clear, and concise and was free from spelling and grammatical errors. 4.0 pts |
Satisfactory: Student’s writing exhibited some deficiencies in the area of organization, clarity, and conciseness and/or contained a few spelling or grammatical errors. 2.5 pts |
Poor: Student’s writing exhibited major deficiencies in the area of organization, clarity, and conciseness and/or contained many spelling or grammatical errors. 1.0 pts |
4.0 pts |
Total Points: 15.0 |
Next week, our guest speaker will be Mr. Bill Schuman. Bill is the Sr. Vice President of Project Delivery for Transcend Spatial Solutions. His responsibilities include project manager oversight, providing subject matter expertise for road inventory, asset management, linear referencing systems (LRS) and road data models, business operations, and guiding the company’s strategic direction. He has over 28 years of transportation and GIS experience. He is a recognized LRS and transportation data expert and has worked with state and local governments on IT strategic plans, spatially enabled database and data warehousing projects, LRS design and implementation projects, and many custom data maintenance and data presentation applications.
Bill holds a B.S. in Civil Engineering from the University of Wyoming and is a GIS Professional.
Transportation agencies capture a wide variety of information about their roadways in addition to information about assets or occurrences along their roadways. Some of these attributes relate to a specific location (e.g., crashes) while other attributes relate to a section of roadway (e.g., speed limit). Collectively, these point or linear attributes are referred to as events.
The large number of events which need to be associated with the geometry of the roadway creates a challenge due to the fact that they often change values at different locations. For example, the locations where speed limit changes occur generally doesn’t correspond to the points where changes in payment type, the number of lanes, or the condition of the roadway occur.
Consequently, if we were to attempt to segment the roadway in such a way to ensure all attributes were constant over the length of each segment we would wind up with a highly segmented roadway. Alternatively, if we were to create a separate linear feature class for each roadway attribute we would have a large number of feature classes which would need to be maintained. One solution to this problem is to separate the events data from the route geometry and maintain them in separate tables which relate to the route geometry according to the route name and a linear measure (for point events) or pair of measures (for linear events) which indicate the location of the event along the route.
There are many different ways one can locate an event along a route. For example, an event could be located according to its distance along the route in miles from the county line. Alternatively, the distance could be measured from the beginning of the route or some other established marker or datum. These different approaches are referred to as Linear Referencing Methods (LRMs).
Given the relationship between the events in the events table and the route features, GIS software can dynamically create feature classes for any specific event or combination of events. This process is known as dynamic segmentation. The standard set of geoprocessing tools can then be applied to these dynamically generated features just as they can be applied to a persistent feature class.
The entire system which an organization uses to allow for the separation of event data and dynamic generation of feature classes is known as a Linear Referencing System (LRS). LRSs have been used extensively with road networks but they are applicable to other types of linear networks as well including pipelines and hydrologic networks.
Read the article “A Comprehensive Process for Linear Referencing” (URISA Journal Vol. 19, No. 2, 2007) [9]. The article begins on page 41. After you have read the article, submit an M.S. Word document to Assignment 5-6 in Canvas which answers the following questions:
After reviewing the background material for next week’s webinar and the biography for next week’s speaker, come up with 3-5 questions which are clearly stated and are relevant to the webinar topics. Submit the questions to Assignment 5-7 in Canvas.
Criteria | Ratings | Points | ||
---|---|---|---|---|
Question Quality |
Excellent: Questions were clearly worded, demonstrated a thorough review of the background material and thoughtful reflection and insight on the part of the student.
5.0 pts
|
Satisfactory: Questions were somewhat clear, demonstrated some review of the background material and some reflection and insight on the part of the student.
3.0 pts
|
Poor: Questions were unclear and/or demonstrated little or no review of the background material and/or demonstrated little or no reflection and insight on the part of the student.
1.0 pts
|
5.0 pts |
Total Points: 5.0 |
In this lesson, we learned about network analysis and the broad set of transportation problems it can be used to address. We examined how network analysis is implemented in ESRI's Network Analyst extension to ArcMap and examined the 6 categories of network analysis or solvers which it provides. In addition, you had the chance to get some hands-on experience with a few of the solvers. You will have additional opportunities to apply these tools in upcoming lessons as well.
Our transportation organizations of the week were state DOTs. We reviewed some the key functions these organizations perform and looked at how their roles have changed over the past century. You also explored a state DOT of your choice and became familiar with an example of how they use spatial technologies.
In our weekly webinar we had the chance to interact with Mr. Frank DeSendi, the Manager of PennDOT's Geographic Information Division, and review how PennDOT utilizes spatial technology to help them identify potential impacts a transportation project could have on the environment.
In preparation for next week's webinar, we learned a bit about LRSs and dynamic segmentation, important topics in GIS-T which we will cover in more detail in next week's lesson. Finally, you had the opportunity to get to know one of your classmates a little better and share some of your ideas and questions about this week's lesson materials.
If there is anything in the Lesson 5 materials about which you would like to ask a question or provide a comment, submit a posting to the Lesson 5 Questions and Comments discussion in Canvas. Also, review others' postings to this discussion and respond if you have something to offer or if you are able to help.
Links
[1] http://desktop.arcgis.com/en/arcmap/10.4/extensions/network-analyst/types-of-network-analyses.htm#ESRI_SECTION1_DEAE22E63F944F6C958668B8C4AA96DA
[2] http://www.esri.com/videos/watch?videoid=92&isLegacy=true&title=network-analyst-_dash_-an-introduction
[3] http://ntl.bts.gov/tools/statedot.html
[4] https://www.nap.edu/read/22378/chapter/4
[5] https://www.nap.edu/catalog/22378/strategic-issues-facing-transportation-volume-5-preparing-state-transportation-agencies-for-an-uncertain-energy-future
[6] http://www.gis.fhwa.dot.gov/statepracs.asp
[7] http://www.gis-t.org/dot-contacts/
[8] http://resources.arcgis.com/en/help/main/10.1/index.html#//003900000001000000
[9] http://www.urisa.org/clientuploads/directory/Documents/Journal/Vol19No2.pdf