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SOUTH DAKOTA
SCHOOL OF MINES
& TECHNOLOGY
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RETIRED SYLLABUS, ATM 620 [Spring 2002]: Remote Sensing for Research - 2
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ATM 620
Satellite Remote Sensing - 2
"A Graduate Research Seminar Course in Remote Sensing"
Institute of Atmospheric Sciences
South Dakota School of Mines
Rapid City, South Dakota
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Who Where When
Available on Reserve
Schowengertdt, Remote Sensing: Models and Methods for Image Processing
Turcotte, Fractals and Chaos in Geology and Geophysics (2nd ed)
Kidder and Vonder Haar, Satellite Meteorology: An Introduction.
Sabins,
Remote Sensing: Principles and Interpretation.
Richards, Remote Sensing Digital Image Analysis : An Introduction
Schott, Remote Sensing, The Image Chain Approach
Quattorchi and Goodchild, Scale in Remote Sensing and GIS.
Stephens,
Remote Sensing of the Lower Atmosphere
Kalnay, Atmospheric Modeling, Data Assimilation and Predictability
Overview
Continuing from ATM 520, graduate students will continue to explore the principles and practices of remote sensing. However, where 520 presents a survey of methods (as well as IDL programming), 620 students will focus on a research topic near and dear to the individual student. Though the students are not expected to integrate their projects into their theses, they are encouraged to find ways to complement their work with remote sensing, image processing techniques, data analysis, etc.
The students are also expected to share their research (or other remote sensing topic of interest) with the class by giving seminars (the number of which is determined by enrolment and interests) and participating in group research discussions. Intermixed with the seminars will be special topics lectures by the professor and guest lectures.
Professor and Guest Lectures
Spectral Analysis
Scale Issues in Remote Sensing
Fractal Analysis
Microwave Remote Sensing
Remote Sensing and Model Integration
Remote Sensing and GIS Integration
Laboratories and Round Table Discussions
620's lab period will be split between discussions of the students projects, hands-on applications of methods discussed in class, and the opportunity for students to demonstrate their seminar material to their associates.
Grading
One Half Paper and Bulding Materials (e.g., Status Reports)
One Half Seminar
Course Materials:
Support Materials and Assignments
Machine/Human Compatibility and Related Items
All IDL/ENVI-licensed machines should be suitable for all users. Developing complications to the monitors and equipment that degrade functionality, performance, user comfort, etc. should be brought to the attentions of the IAS sysadmin and myself ASAP. The sooner it's reported the sooner it's fixed/replaced.
Specific physical issues to the individual, machine related or otherwise, should be brought explicitly to my attention and that of campus ADA Coordinator & Dean of Students before class proceeds.
Program of Study
This course is a seminar/research class (bordering on an independent study on
the remote sensing topic of your choice). Nonetheless, as it is a group class there
remains some structure. You'll be reporting on your research to your cohorts and professor. You'll also
be attending special topics lectures and presenting a few yourself.
Research
There are no exams in this course (there is also only one coursework
exam question for ATM 6/720). However, you are expected to produce a quality,
well-written scientific paper by the close of the course based on your research.
You will choose the topic area and prosecute the problem through the semester.
To evaluate your progress every two weeks, you'll turn in a summary of the past
fortnight's work. This will be preceded by a brief summary of where you were two
weeks ago, and where you plan on being two weeks from the submission of the report.
(This is for your benefit as well as mine.) Your first mission is to formally select
a topic (as many of you have). However, I may be requesting that you reduce the scope
of your project so as to better the chances of a deliverable come semester's end when
you will be thrilling your cohorts after titillating them all semester by providing a
final seminar on your project. You have the freedom to use the package of your choice
(IDL, ENVI, C, Spreadsheets).
Group Research Meetings
One of the afternoon periods each week will be dedicated to a short
meeting in the IAS Reading Room to discuss the projects. This allows the use of your
cohorts as a sounding board for your projects and can be VERY helpful in clearing your
head as to your projects. Furthermore it is good practice for when you enter the "real"
world and out of the blue you are asked to talk about what you're doing!
Student Seminars
You will each provide at least two "sets" of seminars. For these seminars, you
are "strongly encouraged" to provide a hands on demonstration of any methods that you
present, thus concretizing the lecture/seminar material. Naturally, you should scope this so that it can be presented within the
prescribed lab time and doable in the on-after time following the lab. Topics can
include numerical analyses techniques, imagery types and methodologies. They MUST, however, explicitly be in the context of remote sensing. Be advised
that these can take a lot of work in research and preparation and some of you may wish
to do some dry runs before your talk(s). One meeting will involve us huddled in my
office with the scheduler to set up our times.
Lectures
In addition, I'll be giving a number of lectures starting with Fourier analyses. Currently Planned are
the Following (subject to additions and removals - students with special requests should
make them quickly):
Spectral Analysis (aka Fourier Analyses) (Schott, Ch7 and Schowengerdt 6.4) 1-D AND 2-D
Scale Issues in Remote Sensing (Q&G)
Fractal Analysis (Q&G; Schowengerdt*)
Remote Sensing and Model Integration (Data Assimilation)
Remote Sensing and GIS Integration (Also a potential Seminar Topic for one of you, pending ability)
Neural Networks
Special Labs
The primary core of the class is research on your projects. However, wherever possible, activities will be provided so that you can test-drive the material on data relevant to your projects. This gives you a familiar test bed on which you can ground yourself while trying new tricks. You'll be using IDL for some of them, so don't forget what you learned last semester!
Contact: William Capehart
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Last Modified: 02/03/2006 |
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