GEOG 482L: Principles of Geographic Information Science Fall 2011
Time: Tues / Thur 12:30-1:50
Lab: Thur 2:00-3:50
Location: AHF B57A (access through AHF B55)
Instructor: Dr. Andrew Curtis
Office: 448B Kaprielian Hall
Office Hours: Tuesday and Thursday 11:15-12:15, or by appointment
Phone: 626 429 9476
Email: ajcurtis@usc.edu
Course Syllabus
General Focus
Many academic topics are inherently spatial – both in terms of the physical processes,
and the human implications. Hurricane tracks, the location of fault lines, how tornadoes
are generated – these are patterns or processes that have or leave spatial footprints. Where
people live in relation to potential hazards or the societal impact left after a disaster can
again be described in terms of spatial patterns. Within these patterns are human places,
cultures, and interactions. As geographers we have the technologies and spatial skills to
map, predict, and ultimately understand these landscapes. This course will investigate one
of the major geospatial tools we have at our disposal
This class has two objectives; to present an overview of the conceptual aspects of GIS
and provide students with a working knowledge of ArcGIS software.
Any student requesting academic accommodations based on a disability is required to
register with Disability Services and Programs (DSP) each semester. A letter of
verification for approved accommodations can be obtained from DSP, and it should be
delivered to me early in the semester. DSP is located in STU 301 and is open 8:30 to 5:00
pm, Monday through Friday (740-0776; study@usc.edu).
Statement of Purpose
Each class will consist of a mixture of spatial topics followed by software instruction based on
the previous conceptual discussion. This will be a fluid process that allows students to
understand why a topic is important, and then immediately act on that topic. The lab section will
consist of a hands-on practical session that will polish your GIS skills. A learning objective of
this class is that you will become competent with the software, and develop a spatial science
understanding of why you would use a GIS. In other words, you will learn enough to support
your research, or that of others, or even to find employment.
Each student is encouraged to work with a friend.
Readings:
All students are expected to read the academic papers that will accompany each week’s topic. In
addition, you might find the following useful (the publishers’ blurb):
GIS Tutorial 1: Basic Workbook, Fourth Edition meets a growing demand for effective GIS
training by providing tutorials and assignments that teach you how to collect data, create maps,
and perform spatial analysis. Presented in a step-by-step format, the book can be adapted to your
specific needs, whether these involve learning GIS in a classroom or using the book for
independent study. Updated for ArcGIS 10, this workbook demonstrates a range of GIS
functionality, from querying interactive maps to running geoprocessing tools, and it introduces
ArcGIS extensions for advanced analysis. Reader-friendly exercises make GIS Tutorial 1 the
perfect choice for beginners. Also included is a fully functioning 180-day trial version of ArcGIS
10 software on DVD and CD of data for working through the exercises. ESRI press ISBN:
9781589482593
Tues, Aug 23: Introduction to the course / to GIS
Current applications
Examples of previous final projects
Getting started with Arc
Tues, Aug 30: Introduction to GIS concepts continued
Spatial analysis and visualization
Types of analysis – finding hotspots, using overlays, field approaches with a PDA
Data sources: GIS registered maps, air photos, transportation networks, political and
socioeconomic data
Vector and Raster differences
GIS as a tool box – how to ask GIS questions and collect the right data
Basic functions in the map window
Querying
Symbology
Dynamic linking between tables and maps
The importance of Meta Data
Tues, Sep 6: Introduction to GIS concepts continued
Spatial Data
Points, lines, polygons
Why use a GIS? – various societal examples
Stages of problem solving
Geographic Information Science
Querying, selecting and saving
Summarizing attributes
Creating new attributes
Joining tables
Point-in-polygon
Exercise 1 – Creating a Choropleth map
Tues, Sep 13: Basic Cartography
Mental maps / data maps / virtual maps
Differences between cartographers
Role of maps – descriptive / analytical / pragmatic
Cartographic pitfalls
What should your map contain
Multivariate data display
Qualitative vs. quantitative (displaying points, lines, areas)
Symbol placement
Critiquing published maps
Thematic display – equal count, equal interval, equal area, standard deviation, natural
breaks
Why do we normalize?
Symbology
Class types and breaks
Normalizing data (different ways)
Layout functions
Exporting your map to other packages
Making your map look “nice”
Tues, Sep 20: – Exercise 1 and Test 1
Defending your map to the class
In class test 1
Tues, Sep 27: – Spatial Analysis 1
Solving problems with a GIS
Exploratory analysis / confirmatory analysis
Spatial sampling -- points, lines, areas
Spatial sample field examples
Labeling features – label placement
Importing XY coordinates
Changing Data frame properties
Coordinate systems explained
Adding new data frames
Tues, Oct 4: – Spatial Analysis 2
Key spatial terms: distance decay, spatial interaction, diffusion
Spatial patterns
GIS questions for points, lines, areas
Methods of cluster detection
Visualizing data to find patterns – John Snow
Examples – reducing African American Infant Mortality in Baton Rouge
Mass graves in Bosnia
Finding and Bringing in scanned maps
Heads-up digitizing points
Tues, Oct 11: – Georegistering and History
Historical applications of GIS
Example: Yellow Fever in New Orleans
Georegistering images
Geocoding – examples from the social sciences
Creating your own social spatial dataset
How geocoding works
Georegistering images in Arc
Heads-up digitizing points
Geocoding in Arc
Tues, Oct 18: – Exercise 2 and Test 2
Spatial Filter (DMAP) exercise
Tues, Oct 25: – Points and polygons
MAUP
Contextual models
Different spatial aggregations (census block to zip codes)
Problems with predefined aggregations
Neighborhood level analysis
Finding geospatial data on the web – atlas, ESRI, geography network, census.gov
Useful manipulations:
Extracting coordinates
Finding centroids
Adding XY data to points
Finding centroids
Tues, Nov 1: – Projections & Buffering & Contouring / Exercise Three
Different projection schemes
Explaining UTM coordinates
Using buffering as an analytical tool
Interpolation / extrapolation
Combining contouring and overlay
How contouring works: triangulation / IDW
Exercise three – Geocoding accuracy, confidentiality and density surfaces.
Changing projections and coordinate systems
Importing air photos
Buffering points, lines and areas
Using IDW in Arc – spatial analysis, variable or fixed
Interpolating IDW to contours
Improving the contour surface – query, color, proportional symbols
Tues, Nov 8: – Density analysis
Density analysis to find hotspots
Kernel density – how it works
Combining density, contours, and standard deviation classification
Densities of lines
Exercise 3 – Hotspots and contours
Running KDA in Arc
The importance of Meta Data
Projections / coordinates revisited
Tues, Nov 15: Overspill
Tues, Nov 22: – In-class time for project work
Tues, Nov 29: – Presentation of final projects
Final exam
Grading
There will be three in-class software based exams. These will consist of techniques you have
been taught in class. The final exam will also include theoretical questions based from class
readings and lectures. There will be three exercises and a final research project which you will
present to the class at the end of the course. Students may work in groups except for on the inclass tests. During these tests any and all documentation (class notes, texts) are permissible – just
no talking.
There will be no “extra credit” – if you don’t come to class early in the semester, or if you
don’t hand in satisfactory work, be prepared to live with those consequences. If you have a
particular problem during the semester, I will always work with you at that time, not later
in retrospect. Treat this like a Stats class….if you miss a week, it is hard to catch up…
Therefore :
3 in-class tests
Final exam
3 labs
1 research project
30%
10%
30%
30%
Grade Distribution:
A = > 94
C = 74-77.9
A- = 91-93.9 B+ = 88-90.9 B = 84-87.9
C- = 71-73.9 D+ = 68-70.9 D = 64-67.9
B- = 81-83.9 C+ = 78-80.9
D- = 61-63.9 F = < 61
Please note that you: (1) are strongly encouraged to keep a copy of all materials submitted for
grading; and (2) you must obtain at least a D grade (≥ 61%) on the final exam in order to pass the
course as a whole.
Deadlines
Deadlines will be set in lecture / lab. These will be non-negotiable. For every day an exercise is
handed in late, it will be graded down by 20%. After 5 days – you have lost all possible points.
Obviously emergencies are handled on a case-by-case basis. Please contact me with any
problems you may encounter as soon as you are aware of them. If you have to miss an exam (by
prior agreement with me) the multiple choice exam will be replaced by an essay exam covering
similar material.
For more information on academic integrity please refer to the following:
The Trojan Integrity Guide can be found at http://www.usc.edu/studentaffairs/SJACS/forms/tio.pdf. The Undergraduate Guide for Avoiding Plagiarism can be found at
http://www.usc.edu/student-affairs/SJACS/forms/tig.pdf.
I believe this class should be interesting and fun for a lot of people. If you put in the time and
work hard, I will do my best to make it a valuable experience for you.