Syllabus for GTECH 705
Spatial Analysis
Fall 2006
Th
5:35 – 8:15 PM
Instructor: Jochen Albrecht Class room: Hunter
N1022
Office: Hunter N1030 Office hours:
by appointment
(via email)
E-Mail: intro2gis@gmail.com Phone: (212)
772-5265
Course
Overview:
This course provides an
overview to a number of techniques aimed at the analysis of spatial data. We will study local and
neighborhood level methods, regionalized variables, and the modifiable area
unit problem. While most techniques have a geographic origin, we will address
all geo-spatially relevant methods, including geophysical, landscape
ecological, epidemiological, and regional science approaches. As this is a
graduate course, the bulk of the content will come from you, the student. The role of the instructor is mostly to provide
structure and guidance. On the practical side, students will be introduced to five
different software packages. Each student conducts an individual software
project that relates to spatial analysis. The choice of software package is up
to the respective student. The application area (field) is to be chosen by the
student, who in turn is responsible for gathering the necessary data.
Textbook: There is no required textbook. A small list of books
relevant to this course will be discussed during our first session. Reading
material for each session will be made available in advance through the course BlackBoard site. In addition, every student will receive
pointers to specific readings for their assigned methods session. Recommended
books are:
Ripley, 1988 Statistical Inference for Spatial Processes
Longley and Batty, 1996 Spatial Analysis: modeling in a GIS
environment
Fotheringham
et al., 2000 Quantitative Geography
Mitchell, 2005 The ESRI Guide to GIS Analysis Volume
2: Spatial Measurements and Statistics
Schabenberger and Gotway, 2005 Statistical
Methods for Spatial Data Analysis
Wang, 2006 Quantitative Methods and Applications in GIS
Pre- and co-requisites: GTECH 702 (advised), and
permission of the instructor.
Policies:
Attendance is crucial. Given that the class-learning
environment is active learning, meaning that most of the student performance is
practical assignments rather than tests, adherence to protocols and the course
timetable is very important. Lateness in arriving at class, both lectures and
laboratory/discussion sections will not be tolerated. Active involvement in the
course is evidenced in part by undertaking the mechanics of the practical
assignments systematically, and learning the tools by hours of practice. In so
doing the tools soon come to be seen as a means to an end, rather than the end
itself. For example, you will make many maps, and may get caught up in this
creative activity, but remember that the maps are being made for particular
scientific purposes. Class participation includes timely attendance at
laboratory sessions, participation in organized class discussions,
accomplishments of in-class tasks, accomplishment of the preliminary assignment
on time, and participation in the map poster display (if this is a part of the
course this semester). Remember that a good part of your grade depends on class
participation.
Plagiarism is simply not acceptable. Helping other students
on use of the software is encouraged. However, do not help other students
answer questions from the labs. Many of the problems have a "sample"
problem, which includes the answer. The best way to help your fellow students
is to work the sample problem. If a sample problem is not available, create an
exercise similar to the problem in the lab and solve that problem. You can't actually learn this material
unless you do the work yourself. Therefore, do not share your calculations
or measurements with other students. You must do your own work (and it is easy to see when students copy work from
other students). Students with labs showing copied work can receive failing
grades.
Special accommodations for persons with disabilities are provided upon request.
Please see the instructor if you feel the need for them.
Lab policies are described in detail in http://everest.hunter.cuny.edu/~tbw/spars/rules.html
Assignments are to be submitted
electronically via BlackBoard. I expect assignments,
big and small, to be submitted by announced dates. I may give grace periods
(maximum of a few days) if logistical problems arise. It is in your best
interests to keep up with the work and meet deadlines for assignments.
Following Hunter policies, incomplete grades and time extensions are not an
option. There are no "extra-credit" assignments. Unless otherwise
instructed, you will submit assignments in electronic form. For all labs, you
are expected to show all the work you did in order to complete the assignment.
It is more important how you did the
work, than whether you got the right answer. Partial credit will be given for
good work but incorrect results.
Criteria
for evaluation:
Evaluation
of academic performance is based on the preparation and presentation of your
own session, a methods report, your lab exercises, your software project and your
participation according to the following breakdown:
Method presentation 15%
Method write-up 15%
Lab exercises 30%
Software project 30%
Participation 10%
Numeric scores will be used
throughout the semester. The course letter grade will be determined only at the
end of the semester, although guidance as to letter grade standing will be
given along the way.
All labs exercises are designed
for a 4-hour period and start with an introduction during a Friday session. You
are free to stay beyond the Friday instruction period or finish the exercises
at your own leisure. As you are graduate students, you can use our computer
labs at any time outside of the posted instruction times for other courses. It
is your responsibility to manage your time to conduct both the labs as well as
project work during the hours that the lab room is accessible. Of course, you
are free to work at home as much you want – if you can arrange for access to
the software that you need.
Each student conducts an
individual semester-long software project that involves the quantitative
analysis of a substantial geographical problem. There are no requirements with
respect to what software the student uses. In a similar vein, the application
area (field) is to be chosen by the student, who is also responsible for
gathering the necessary data. Basically, you can choose whatever topic you
want, provided it has to do with geographical
analysis; the stress is on both words! It is your responsibility to find a
suitable project, which will have to be accepted by the instructor. A few
ready-made projects are available but experience shows that motivation
increases when students take pride in their own project.
Schedule (subject to change):
Session #
|
Date |
Topic |
BlackBoard |
|
1 |
Aug 31 |
Introduction, syllabus, rules |
Syllabus |
|
2 |
Sep 7 |
Visual data exploration theory |
Bailey
& Gatrell Ch 3 |
|
3 |
Sep 14 |
Descriptive spatial statistics |
tbd |
|
4 |
Sep 21 |
Point pattern analysis |
tbd |
|
5 |
Sep 28 |
Landscape
ecological measures |
tbd |
|
6 |
Oct 5 |
Regression review; autocorrelation |
|
|
7 |
Oct 12 |
Residuals and GWR |
tbd |
|
8 |
Oct 19 |
Spatial
regression |
tbd |
|
9 |
Oct 26 |
Bayes and
Markov |
|
|
10 |
Nov 2 |
Spatial
interaction modeling |
tbd |
|
11 |
Nov 9 |
Geostatistics |
|
|
12 |
Nov 16 |
GeoComputation |
tbd |
|
13 |
Nov 30 |
Comparison
of software packages |
|
|
14 |
Dec 7 |
Presentation
of projects |
tbd |
It is the
student’s responsibility to regularly check the course website on BlackBoard to become aware of changes to the schedule or
other announcements.
Instructor expectations
Hunter College
This
is a place where students come to learn. It’s a place where knowledge is
developed and hopefully it’s a place where students can see and participate in
its development. Unlike previous schooling you don't have to be here, so we'll
assume that you want to be here and that you are here to actively seek
knowledge and skills.
With
assumptions that you are (a) here of your own free will and (b) are actively
seeking to gain knowledge and skills, there is only one fuzzy area (for some) -
how to succeed! It’s really quite simple: have fun. If you are enjoying what
you are doing, you will succeed; if you are taking subjects or studying in a
particular program and not enjoying it, you are unlikely to be successful.
A
few words on success and enjoyment. Success is not just measured by your grade
(but passing does help!), it is also measured by how you feel about what you
are doing. You are the only person who can really judge whether you are
successful - have you met your own expectations? Enjoyment does not necessarily
mean stress free living (although maybe it is for some!). Taking only subjects
that you were told were "easy" doesn't guarantee enjoyment; some of
us require a challenge in life! Again, only you are in a position to determine
what you find enjoyable.
A
final thought on what a university is: this is also a place where faculty comes
to learn...
GTECH 705 Spatial Analysis
Students: to be successful you should be taking this subject
because you want to take it, not because someone told you that you need to take
it and you must be actively seeking knowledge and skills. This subject is a
good participation "sport", but it’s not a really good spectator
event. You need to be proactive, be able to try something new, look at things
from a new (spatial) perspective, ask questions, read read read. You need to
know when to take a break, get some fresh air, rest your eyes (a Buddhist
philosophy is quite useful...). Attend the lectures and practical sessions.
when your absence is unavoidable, make sure you catch up on what was missed.
Plan your week as best as possible and make the commitment to spend the amount
of time needed for you to be successful. get a study partner or three, if this
works for you.
Faculty: to be successful, I need to know that I've "made
a difference" to at least some of my students, i.e., they feel successful.
I'll provide a coherent subject structure, I'll deliver the best lecture
possible on the day, and pointers to resources where possible and my tutors and
I will provide sound practical instruction and practice our listening skills so
that we can understand what difficulties you may be having, so that we can
resolve them. Furthermore, we are available and approachable; ask questions in
lectures, labs and at other times; use our office hours or make appointments to
see us. Faculty have shown disappointing prowess at extra-sensory perception,
please help us out!
We
often lecture in subjects we are considered to have some expertise in; we are
therefore fairly interested in the subject matter. We too are students in that
we are continuing to learn new things in our areas of expertise and sometimes
we are the ones who develop new knowledge in our areas of expertise!
Theory
vs. practice: in lectures I try to
provide an overview of the most important knowledge, but this never replaces
the reading material. sometimes lectures and readings will cover the same
ground, but often, the best that can be done in some fourteen sessions is to
provide just a "flavor" of the subject matter, something to whet your
appetite, something to set the context for your readings.
Finally...
The
reason for this page of amateur pop psychology is two fold: (a) first I hope
that prospective students take this subject for the right reasons (i.e. they
believe that they will enjoy it) and are in the right frame of mind to be
successful and (b) second, I hope that with a little mutual empathy the
learning experience can be made better for both student and teacher. If we are
not having fun, we are both doing something wrong!
I wish
us a lot of fun in this course,
