Tue, Thu 18:00-19:50 Cramer Hall 409 (Tuesdays) and 469
(Thursdays)
Course webpage: http://web.pdx.edu/~jduh/courses/geog482s09
Instructor: Geoffrey
Duh (email: jduh@pdx.edu)
Office: Cramer Hall 424J
Phone: (503)725-3159
Office hours: Tue, Thu 2-3:30pm or by appointment
Course emailing list: geog4_582@lists.pdx.edu
Course Objectives
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.
·
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. Students are expected to actively contribute to each class
period. To facilitate an interactive
discussion, students will lead journal article discussion during the semester
for which they will receive a grade. The discussion leaders must do three
things. First, they must thoroughly read the reading and write a
1-2 page critique/synopsis. The synopsis part should highlight the main
points of the reading and the critique part should identify strengths and
weaknesses of the reading. Second, they 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, they are
responsible for leading the classroom discussion along with the instructor. The
discussion schedule will be posted after Lab 1 is completed. 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. Below is a list of common remote sensing procedures for ERDAS Imagine. Use them to refresh your skills with Imagine if necessary. They are listed in the order of their relevance to this course.
·
Advanced Classification
and Accuracy Assessment
·
Making Maps from
Satellite Imagery
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.
Click here for the information on the
requests for academic accommodation and the policy on academic honesty.
(Pdf files are available in I:\Students\Instructors\Geoffrey_Duh\GEOG4582\Readings)
|
Week |
Tuesday
(Lecture/Seminar) |
Thursday (Lab/Project) |
|
1 Mar 31/ Apr 2 |
Course Overview & Review of Digital Image Analysis (Slides) Lab 1. Journal articles search (Due on April 9 before class) (10 points) |
Review of Digital Image Analysis |
|
2 Apr 7/9 |
Remote Sensing Applications (NASA Online Tutorial Section 3: vegetation Applications) (Slides) |
Lab 2. Knowledge-based classification (Due on Apr 23) (20 points) (Slides) |
|
3 Apr 14/16 |
Change Detection ( |
Lab 2. |
|
4 Apr 21/23 |
GIS in Action conference (assignment) |
Project Outline Due Lab 3. Radiometric normalization (Due on Apr 30) (15 points) (Slides) |
|
5 Apr 28/30 |
Lab 4. Change vector analysis (Due on May 7) (15 points) |
|
|
6 May 5/7 |
Lab 5. Advanced classifier (Due on May 21) (20 points) (Slides) |
|
|
7 May 12/14 |
Lab 5. |
|
|
8 May 19/21 |
||
|
9 May 26/28 |
Students work on their project |
|
|
10 Jun 2/4 |
Object-Based Image Classification |
|
|
Jun 9 19:30-21:20 |
Project presentations (during scheduled exam
time) PORTFOLIO
DUE before class |
|