Spring 2021 SYLLABUS

INSTRUCTOR

Prof. Joseph Ferreira, Jr., Room 9-219, jf@mit.edu
Virtual Office hours: Thursday 10:45 - 12:15

COURSE STAFF

Teaching Assistant: Rounaq Basu, rounaq@mit.edu
Virtual Office hours : TBA

MEETINGS

Monday: Lab prep and Lab exercises 2:30- 5:00 pm1
[Lab prep and start of exercise are the key parts. Students can leave for other classes beginning at 4 and finish the exercises later on their own.]

Additional supervised lab time (with no new material): Friday, most likely 12:30 pm-2:00 pm )

Wednesday: 2:30- 4:00 pm

Website: Lab exercises, lecture notes, and other class materials for both 11.188 and the 11.205+11.520 modules are available in the one class locker at: http://web.mit.edu/11.188. In addition, lab, homework exercises, and some readings will be available via Stellar at: http://stellar.mit.edu/S/course/11/sp21/11.188.

CREDITS

11.188 is an undergraduate subject that will satisfy both the Department and the Institute lab requirement and earns 3-6-3 units of undergraduate credit.

11.205 and 11.520 are graduate subjects and 11.205 satisfies the GIS and Spatial Analysis requirement of the MCP degree program.

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:

• Learn spatial analysis methods and acquire technical skills in the use of geographic information system (GIS) software and database management tools through
• • lab exercises and homework using small (but real) local datasets, and
  • project work involving the shared use of larger datasets and the mixing and matching of data from different sources.
• Acquire qualitative methods skills by:
• • gathering data and documentation
  • analyzing information, and
  • presenting results effectively.
• Investigate the potential and practicality of GIS technologies in a typical planning setting and evaluate possible applications.

• Understand basic principles underlying the growth of web mapping, geospatial services, and location-aware computing.

The first half of the semester covers basic thematic mapping and the buffering and overlay operations (using vector and raster data) that are involved in basic 'site suitability' assessments. The content meets the 'spatial analysis' requirement for the MCP degree and includes a bit more database management (using Postgresql) than is covered in the Fall version of 11.205. The second half of the semester includes additional work with web mapping and application programming interfaces (APIs) for location-tagged data, plus a small, individual project that exercises the concepts and tools learned earlier in the semester.

We try to teach GIS methods and techniques with some attention to open-ended planning questions that invite spatial analysis but will

• Require judgment and exploration to select relevant data and mapping techniques;
• Involve mixing and matching new, local data with extracts from official records(such as census data, parcel data and regional employment and population forecasts);
• Utilize spatial analysis techniques such as buffering, address matching, and overlays;
• Use other modeling and visualization techniques beyond thematic mapping (e.g., map mashups);
• Raise questions about the skills, strategy, and organizational support needed to sustain such analytic capability within a variety of local regional planning settings.

CLASS OVERVIEW

PREREQUISITES

The prerequisites for the course are:

• A working familiarity with personal computing, spreadsheets, and the MIT Athena and CRON computing environments.
• 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. The MCP subject, 11.220 (Quantitative Reasoning I), is a suitable analytic prerequisite for graduate students.

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 schedule below. The GIS exercises will use open source QGIS software.

GRADING

Content	11.205	11.520	11.188
Five Lab Exercises (collectively)	30%		15%
Two Homework Sets (collectively)	32%		16%
In-Class, Open-Book Test	32%		16%
Third Homework & last 2 labs		44%	22%
Small Project		50%	25%
Class Participation	6%	6%	6%

Please include your name and Athena username on all assignments, tests, etc., including those turned in electronically. We need this information to identify your work easily.

LATENESS POLICY

All assignments with be submitted online using the Stellar website for the class. 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 are 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 (weekends and holidays count for a single day ) that it is turned in after the due date. 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, after two weeks, no problem sets will be accepted if you have not yet contacted any of the teaching staff.

Final project write-ups are due on the last day of classes, May 19. Write-ups turned in after Friday, May 21 will lose 5 points. No project write-ups will be accepted after Tuesday, May 25.

ACADEMIC INTEGRITY

Plagiarism and cheating are both academic crimes. For this class, it is helpful and okay to discuss lab exercises and problem sets (but not tests) with other classmates, but the results and discussion that you turn in should be your own work and not anything copied from another person or paper. Never (1) turn in an assignment that you did not write yourself, (2) turn in an assignment for this class that you previously turned in for another class, or (3) cheat on an exam. If you do so, it may result in a failing grade for the class, and possibly even suspension from the college. Please see me if you have any questions about what constitutes plagiarism. Anyone caught cheating on an exam will be reported to the provost in line with recognized university procedures.

Since the entire class is remote rather than 'in-class', you may find it difficult to identify partners to discuss class material and work on exercises.  You are welcome to use the 'pset partners' program developed by folks in the MIT math department to find potential partners.  Here is the link to use their online tool: https://psetpartners.mit.edu

TEXTS

There is no required-purchase text. Most readings will be available online.  Other, restricted access readings, will be available from the Stellar website for the class. A few  books are recommended (but not required).

Books marked with an asterisk (*) will have some or all portions available for restricted access on the Stellar class website.  Those with two asterisks (**) provide an introduction to ArcGIS software and applications.  We will use QGIS open source software for class exercises, but ArcGIS (from vendor, ESRI) is the most commonly used professional GIS software used by planning agencies and is available to all MIT students.  After learning QGIS, it will be easy to develop proficiency with ArcGIS and that may be useful for acquiring internships and urban planning jobs.  Should you wish to purchase books for GIS and spatial analysis reference, they are available from online retailers such esripress.esri.com, amazon.com, barnesandnoble.com ,Wiley, and from various used book sites.

• (*) Bolstad, Paul. GIS Fundamentals: A first Text on Geographic Information Systems, Sixth Edition, XanEdu Publishing, 2019. ISBN-13 : 978-1-59399-552-2 (paperback, 764 pages). The paperback is $39 at Amazon.
• (*) D'Ignazio, Catherine & Lauren F. Klein. Data Feminism, MIT Press, 2020,
  
• (*) Longley, Goodchild, Maguire and Rhind, Geographic Information Systems and Science, Third Edition, 2010. ISBN: 978-0-470-72144-5. Available for ~$100 from Wiley. The earlier edition from 2001 (ISBN: 0-471-89275-0) is adequate, and is in the Library.
• (*) OSullivan, David, and David Unwin, Geographic Information Analysis, 2nd edition, John Wiley Sons, New Jersey (2010) ISBN: 978-0-470-28857-3. (Available for ~$115 from Wiley. The earlier 2003 edition (ISBN: 0471211761)(in Library) is adequate.
• NCGIA Core Curriculum in GIScience: online on U. of California eScholarship website: http://escholarship.org/uc/item/3g1217wg?query=ncgia%20giscience#page-1
• Monmonier, Mark. How to Lie with Maps. Second Edition. Chicago: University of Chicago Press, 1996. Hardcover: ISBN 0-226-53420-0. Paperback: ISBN 0-226-53421-9. The paperback is now under $15 at Amazon. (The 1991 first edition, ISBN 0-226-53415-4, is also fine.)
• Williams, Sarah, Data Action: (2020) Using Data for Public Good. MIT Press, Cambridge, MA USA.
• (**) Arctur, David and Michael Zeiler, Designing Geodatabases: Case Studies in GIS Data Modeling, ESRI Press, Redlands, CA, 2004, ISBN: 9781589480216 (Available for ~$28 from Amazon.)
• (**) Zeiler, Modeling our world: the ESRI guide to geodatabase design. 2010 ESRI Press.ISBN: 9781589482784 (Available for ~$29 from Amazon.)

SCHEDULE

Lecture Wed., Feb. 17	Introduction to the class, GIS basics and data models, and QGIS software setup Readings: Paul A. Longley, Michael F. Goodchild, David Maguire, David W. Rhind, Geographical Information Systems and Science. Fifth Edition, Chapter 1. pp. 1-32 [on Stellar] Catherine D'Ignazio & Lauren F. Klein. Data Feminism, "Chapter 1: the Power Chapter." pp. 21-49 [on Stellar] Harley, John Brian. “The Map as Biography: Thoughts on Ordnance Survey Map, Six-Inch Sheet Devonshire CIX, SE, Newton Abbot.” The Map Collector 41 (1987): 18–20. [on Stellar] Monmonier, Chapter 3: "Map Generalization: Little White Lies and Lots of Them." Outline of NCGIS online 'core GIS curriculum': http://escholarship.org/uc/item/3g1217wg?query=ncgia%20giscience#page-1
Lab #1 Mon.,  Feb 22	Lab 1: Thematic Mapping in QGIS (symbolization and exploratory vs. explanatory mapping) plus basic database operations (spatial selection and query selection) Reading: Paul Bolstad. GIS Fundamentals: A first text on geographic information systems.  "Chapter 2: Data Models." XanEdu, Sixth edition. 2020.pp. 50-75 only [on Stellar] QGIS online resources A gentle introduction to GIS: https://docs.qgis.org/3.10/en/docs/gentle_gis_introduction/index.html QGIS User Guide: https://docs.qgis.org/3.10/en/docs/user_manual/ QGIS Training Manual: https://docs.qgis.org/3.10/en/docs/training_manual/index.html
Lecture Wed., Feb. 24	GIS Data Manipulation and Querying and Coordinate Systems Homework Set 1 posted online Reading: Paul Bolstad, GIS Fundamentals, Chapter 3, “Geodesy, Datums, Projections, and Coordinate Systems.”  p. 87-136 [on Stellar] Ferreira, J. Jr., 1990. "Database Management Tools for Planning", Journal of the American Planning Association, Winter, pp.78-84. [on Stellar] Optional Reading: Zeiler, Modeling our world, Ch. 4 & 5 Longley et al, Chapter 7: "Geographic Modeling," pp. 152-172.
Lab #2 Mon., March 1	Lab 2: Database Aggregation, SQL, and Charts Lab Exercise 1 due Reading: Longley et al, Chapter 9: "Creating and Maintaining Geospatial Databases." pp.194-216. QGIS Documentation (GIS intro), Ch 10 (Working with Projections) [on Stellar]
Lecture Wed., March 3	Making Sense of the Census Homework Set 2 distributed Reading: MacDonald, Heather and Alan Peters. Urban Policy and the Census. Redlands, CA: Esri Press. 2011. “Chapter 1: Introduction to the US Census” and “Chapter 2: Mapping Continuous Measures: The ACS.” pp. 1-17, 26-32. [on Stellar] Schlossberg, Marc. "GIS, the US Census and Neighbourhood Scale Analysis," Planning, Practice & Research, Vol. 18, No 2-3, pp. 246-217, May-Aug. 2003. Monmonier, Chapter 10 (Chapter 9 in the first edition): "Data Maps: Making Nonsense of the Census." Bernstein, Mira, and Moon Duchin. “A Formula Goes to Court: Partisan Gerrymandering and the Efficiency Gap.” Notices of the American Mathematical Society 64, no. 09 (2017): 1020–24. https://doi.org/10.1090/noti1573.
Lab #3 Tuesday, March 9	<<< Monday schedule on Tuesday, March 10 >>> Lab 3: Working with 2010 Census Data Lab Exercise 2 due References 2010 US Census homepage: https://www.census.gov/programs-surveys/decennial-census/decade.2010.html American Community Survey: https://www.census.gov/main/www/cen2000.html Inter-university Consortium for Political and Social research (ICPSR) via MIT Libraries: https://libguides.mit.edu/socscidata/general
Lecture Wed, March 10	Spatial Analysis (Vector Analysis). Homework Set 1 due (extended to Friday, 12:30 pm, March 12) Homework Set 2 distributed Reading: Longley et al, Chapter 7: "Spatial Data Analysis," pp. 290-317. [on Stellar]
Lab #4 Mon., March 15	Lab 4: Vector Spatial Analysis (buffers, polygon overlay, area allocation) Lab Exercise 3 due Reading: QGIS Documentation (GIS intro), Ch 10 (Vector Spatial Analysis) [on Stellar]
Lecture Wed., March 17	Spatial Data Models and Spatial Analysis II (Raster) Homework Set 2 (Part 1) due (extended to 12:30 pm, Friday March 19) Reading: Law (Part 6, chapters 18,19)
Lecture Wed., March 24	GIS applications - Guest Lecture Lab Exercise 4 due Reading: to be distributed
Friday, March 26	Homework Set 2 (Part 2) due Homework Set 3 distributed
Lab Monday, March 29	online Test (in lab, open book)
Lab #5 Wed., March 31	Lab #5 Raster Spatial Analysis (Interpolation, Raster Operations) <<< End of 11.205 >>>
Friday, April 2	<<< end of half-semester, 11.205 >>>
Lab #5 (cont'd) Mon., April 5	<<< Start of 11.520 >>> Finish Lab #5 + Guest Lecture Reading: to be distributed Homework Set 3 distributed Preliminary Project Proposal due
Lecture Wed., April 7	Introduction to Web mapping & Webscraping with R Lab Exercise 5 due  Reading: Williams, Sarah, Data Action: (2020) Using Data for Public Good. MIT Press, Cambridge, MA USA. Ch. 1 (Big Data for Cities is not New) & Ch. 6 (Data as a Public Good).
Lab #6 Mon., April 12	Lab 6: Web-scraping location-tagged data using R Reading: to be distributed
Lecture Wed., April 14	GIS Data Creation, Advanced Raster Operations, and Model Building Homework Set 3 due Reading: Longley et al, Chapter 10: "The GeoWeb," pp. 217-236. [on Stellar]
Mon., April 19	<< Patriot's Day, Holiday >>
Lecture Wed., April 21	Networks and Geoprocessing Lab Exercise #6 part 1 due Reading: to be distributed
Lecture Mon., April 26	Project Work Revised Project Proposal due Lab Exercise #6 part 2 due
Lecture Wed., April 28	Tips on Project Presentation and Writeup, plus Project Work Lab Exercise 8 due Reading: Notes by Cherie Abbanat, DUSP Writing Specialist, on "Creating Your 11.188/11.520 Presentation and Report"
Lab Mon., May 3	Project Work Project Proposal Feedback
Lab Wed., May 5	Project Work
Lab Mon., May 10	Project Work
Lecture Wed., May 12	Project work & Presentation Preparation
Mon., May 17	Project presentations
Wed., May 19	Project presentations

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Last modified on February 26, 2021 [jf]