Tue Thu 14:00-15:50 Cramer Hall 409 (Tuesdays) and 469
(Thursdays)
Course webpage: http://web.pdx.edu/~jduh/courses/geog482s07
Instructor:
Office: Cramer Hall 424J
Phone: (503)725-3159
Office hours: M 1-3, W 1-2, or by appointment
Course emailing list: geog4_582@lists.pdx.edu
This course focuses on advanced satellite image classification methods that can be used for thematic information extraction as well as digital change detection methods for measuring land use/ land cover change. The course includes computer exercises in advanced classification methods (e.g., Fuzzy and decision tree classification), radiometric normalization, and change detection using leading satellite image processing software packages including ERDAS Imagine and IDRISI Andes.
The course readings are a series of papers that will be
distributed by the instructor as well as digital documents. The course will be
taught in a seminar format. Each student will pick
and read several journal papers and be a discussion leader to review and
criticize these papers. The optional textbook can be used as a reference book
for term project.
Optional textbook: Jensen, J. R. 2005. Introductory
Digital Image Processing (3rd edition). Prentice Hall.
Discussion/Article Critique-
Synopsis 40%
Labs 30%
Project/Portfolio
30%
(There
will be no exams in this course!)
Attendance to this course is mandatory. If you miss
more than two class periods then you will be penalized five percent of your
final grade per absence. PLEASE DO NOT MISS CLASS. You are expected to take
part in the discussions and if you are not in class then you cannot. If you are
repeatedly late you will be given an absence.
Discussion/ Article
Critique- Synopsis (40%)
The course will be taught in a seminar format, which means that students are not passive members of the class. Each student is expected to actively contribute to each class period. To facilitate an interactive discussion each student will lead journal article discussion once during the semester for which they will receive a grade. The discussion leader must do three things. First, s/he must thoroughly read the readings and write a 1-2 page critique/synopsis. The synopsis part should highlight the main points of the readings and the critique part should identify strengths and weaknesses of the readings. Second, this person should develop 4 discussion questions. These questions, as well as the critique/synopsis, should be typed with answers and given to the instructor one day before the class (i.e., Monday by 5 pm). Third, this person is responsible for leading the classroom discussion along with the instructor. It is important that everyone in the class take part in these discussions. Therefore, class attendance and participation are mandatory.
You will conduct labs that will help you learn the methods necessary to do a
project. The practical exercises provide a way to acquire skills using
ERDAS Imagine and IDRISI Andes (i.e., Version 15) and to apply the course
concepts to real data. The lab manual (ERDAS Tour Guide) and ERDAS Field Guide
are available in Acrobat pdf format in the I:\Students\Instructors\Geoffrey_Duh\ERDAS
Imagine folder.
A satellite remote sensing project is required for all students. You can follow this link to find public remotely sensed data for your project. The project is intended to provide a deeper understanding of image classification and/or change detection through experience. You must submit an outline of your project in the 4th week and present the project during a scheduled time at the end of the term. Every project presentation must include the following sections: an Introduction, Data, Methods, Results, and Conclusions. At the end of the course you must hand in a portfolio of all of your lab work and project (including a digital copy of their powerpoint ppt). The portfolio should present the highlights of your labs and project. You must compile a one-page synopsis and a one-page images/pictures/maps for each lab (except for Lab 1) and a two-page (maximum) synopsis and a two-page (maximum) pictures for your project. These documents should be bound or stapled together with a cover page showing your name, course information, and date.
To be finalized after students submit the lists of journal papers they choose.
|
Week |
Tuesday
(Lecture/Seminar) |
Thursday (Lab/Project) |
|
1 Apr 3/5 |
Syllabus Lab 1. Journal articles search (Due by noon pm April 9) (10 points) |
Course Overview & Review of Digital Image Analysis (Slides) |
|
2 Apr 10/12 |
Remote Sensing Applications (NASA Online Tutorial Section 3: vegetation Applications) (Slides) |
Lab 2. Knowledge-based classification (Due by 2pm Apr 26) (20 points) (Slides) |
|
3 Apr 17/19 |
GIS in Action conference (Instructions) |
Lab 2. |
|
4 Apr 24/26 |
Change Detection ( Project Outline Due |
Lab 3. Radiometric normalization (Due by 2pm May 3) (15 points) (Slides) |
|
5 May 1/3 |
Lab 4. Change vector analysis (Due by 2pm May 10) (15 points) |
|
|
6 May 8/10 |
Kevin Martin, City of Multispectral and LiDAR remote sensing for vegetation mapping |
Lab 5. Advanced classifier (Due by 2pm May 24) (20 points) (Slides) |
|
7 May 15/17 |
Lab 3. |
|
|
8 May 22/24 |
||
|
9 May 29/31 |
Students work on their project |
|
|
10 Jun 5/7 |
Students work on their project |
|
|
Jun 11 (Monday) 10:15 – 1:15 |
Project presentations (during scheduled exam
time) PORTFOLIO
DUE by 5pm |
|