Instructor
Prof. Joseph Ferreira, Jr.
Meetings
Monday: Lab Preparations and Lab Exercises
Wednesday: Lecture
Undergraduates should enroll in 11.188; this subject will satisfy both the Department and the Institute lab requirement.
Graduate students should enroll in 11.520.
Note: The subjects 11.520 and 11.188 meet at the same time with nearly identical content.
Goals
This class uses lab exercises and a workshop setting to help students develop an in-depth understanding of the planning and public management uses of geographic information systems.
The goals are to help students:
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Acquire technical skills in the use of geographic information system (GIS) software and database management tools through:
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lab exercises and homework using small (but real) local datasets, and
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project work involving the shared use of larger datasets and the mixing and matching of data from different sources.
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Acquire qualitative methods skills by:
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gathering data and documents,
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analyzing information, and
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presenting results effectively.
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Investigate the potential and practicality of GIS technologies in a typical planning setting and evaluate possible applications.
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Understand basic principles underlying the growth of Web mapping, geospatial services, and location-aware computing.
The workshop teaches GIS techniques and basic database management at a level that extends somewhat beyond the thematic mapping and data manipulation skills included in the MCP core classes (viz. 11.204 and 11.220). Instead of focusing on one thematic map of a single variable, students will focus on more open-ended planning questions that invite spatial analysis but will:
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Require judgment and exploration to select relevant data and mapping techniques.
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Involve mixing and matching new, local data with extracts from official records (such as census data, parcel data and regional employment and population forecasts).
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Utilize spatial analysis techniques such as buffering, address matching, and overlays.
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Use other modeling and visualization techniques beyond thematic mapping.
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Raise questions about the skills, strategy, and organizational support needed to sustain such analytic capability within a variety of local and regional planning settings.
Prerequisites
The prerequisites for the course are:
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A working familiarity with personal computing, and spreadsheets.
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A basic familiarity with elementary data analysis (that most undergrads acquire via general Institute requirements, and most graduate students have already acquired via undergrad methods and analysis classes). Hence, 11.220 (Quantitative Reasoning I) is not a prerequisite.
Requirements
Students will be expected to complete weekly lab exercises plus three homework sets covering readings and basic GIS skills. Students will also complete one in-class test and a small project of the student's choosing that draws on the skills taught in the class. This project will be presented to the class in an oral presentation and a brief written report. The project should require about the same effort as one of the homework sets. Due dates for these requirements are given in the calendar. The GIS exercises will use ArcGIS software.
Grading
Course grading.
ACTIVITIES |
PERCENTAGES |
Lab Exercises (Collectively) |
25% |
Three Homework Sets (Collectively) |
30% |
In-class, Open-book Test |
20% |
Small Project |
20% |
Class Participation |
5% |
Lateness Policy
Turning in assignments promptly is important both for keeping current with the subject matter, which is cumulative, and to keep all students on a level playing field. Hence, we have adopted a strict policy towards credit for assignments that is turned in late. We will consider requests for extensions due to extenuating circumstances on a case-by-case basis, but please do not count on such requests being granted.
Lab exercises are typically due one week after the corresponding lab. A late lab exercise will be accepted up until one week after the original due date for a loss of one grade (e.g., a "check" becomes a "check-minus"). After that, late assignments will receive no credit and will not be accepted.
Late problem sets will have two points deducted for each day (including weekends and holidays) after the due date that it is turned in. Hence, a problem set turned in three days late would lose 6 points. If it would have earned 90 points if turned in on time, it would receive only 84 points under these conditions. Regardless, no problem sets will be accepted after the answers have been posted, typically two weeks after the initial due date.
Final project write-ups are due on the last day of classes. Write-ups turned in later will lose 5 points per day. No project write-ups will be accepted after one week past the last day of classes.
Texts
Ormsby, et al. Getting to Know ArcGIS Desktop. Redlands, CA: ESRI Press, 2001. ISBN: 1879102897.
Worboys, Michael F. GIS: A Computing Perspective. London, UK: Taylor & Francis, 1995. ISBN: 0748400656.
Monmonier, Mark. How to Lie with Maps, Second ed. Chicago, IL: University of Chicago Press, 1996. ISBN: 0226534200 (Hardcover). ISBN: 0226534219 (Paperback). (The 1991 first edition, ISBN: 0226534154, is also fine.)
Longley, Goodchild, Maguire, and Rhind. Geographic Information Systems and Science. Hoboken, NJ: John Wiley & Sons, 2001. ISBN: 0471892750.
Peng, and Tsou. Internet GIS. Hoboken, NJ: John Wiley & Sons, 2003. ISBN: 0471359238.
O'Sullivan, David, and David Unwin. Geographic Information Analysis. Hobokey, NJ: John Wiley & Sons, 2003. ISBN: 0471211761.
Calendar
Course calendar.
SES # |
TOPICS |
KEY DATES |
Lec 1 |
Introduction to the Class and GIS
GIS Principles and Methods
WinAthena Introduction (Required for Students who did not do CRN Computing Orientation) |
|
Lab 1 |
ArcGIS Basics (Introduction to ArcGIS, Paper Output) |
|
Lec 2 |
GIS Principles and Methods |
|
Lab 2 |
Thematic Mapping in ArcMap (Symbolization, Exploratory vs. Explanatory Mapping) |
Homework set 1 assigned |
Lec 3 |
Database Fundamentals (Relational Basics, Queries, Joins), Coordinate Systems, and Projections |
Lab exercise 1 due |
Lab 3 |
Database Operations in ArcGIS (Spatial Selection, Query Selection, Tabular Joins, Spatial Joins) |
Lab exercise 2 due |
Lec 4 |
More on Database Management: Introduction to SQL
Geodatabase
Handling One-to-Many Relationships |
|
Lab 4 |
Database Aggregation, SQL, and Charts |
Lab exercise 3 due |
Lec 5 |
Creating and Maintaining Geospatial Databases |
Homework set 1 due
Homework set 2 assigned |
Lec 6 |
Making Sense of the Census |
Lab exercise 4 due |
Lab 5 |
Obtaining and Using U.S. Census Data in ArcGIS |
|
Lec 7 |
Spatial Analysis I (Vector-based Methods) |
|
Lab 6 |
Vector Spatial Analysis (Buffers, Polygon Overlay, Area Allocation, Using ArcTools) |
Lab exercise 5 due |
Lec 8 |
Spatial Data Models and Spatial Analysis II (Raster, Network) |
Homework set 3 assigned |
Lab 7 |
Raster Spatial Analysis (Interpolation, Raster Operations, Spatial Analyst) |
Lab exercise 6 due |
Lec 9 |
Geocoding and Network Analysis Methods |
Homework set 2 (question 1) due |
Lab 8 |
Address Matching and Geocoding |
Homework set 2 (question 2) due
Lab exercise 7 due |
Lec 10 |
Introduction to Internet GIS |
Project proposal due |
Lab 9 |
ArcIMS (Optional) |
|
Lec 11 |
Project Work |
Homework set 3 due |
Lec 12 |
Test (In-class, Open-book) |
|
Lec 13-17 |
Project Work |
Lab exercise 8 due in Lec 13
Project title and abstract due in Lec 15 |
Lec 18-19 |
Brief Project Presentations |
Brief project presentations due in Lec 18
Project write-up due in Lec 19 |