ESPM 271 Course Outline
Objectives and Style of Instruction
Topics
Course Grading
Textbook
References
Major Journals
ESPM 271
Course Outline
Lecture: Wed. 2:00-5:00 pm
Location: 42 Giannini Hall / 124
Mulford Hall
Office Hours: Tue. 11:00-12:00, Wed.
11:00-12:00 AM, or by Appointment
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Objectives
and Style of Instruction
The aim of the course is to show students how to learn
principles of remote sensing and image analysis. These
include the ways in which remote sensing systems are used to
acquire data, how these data may be analyzed and how
information on our environment can be derived from such data
for natural resources and human settlements, and how
information derived from remotely sensed data can be
integrated with other spatial data such as map data, census
data and field survey data in a geographic information
system.
At the end of the course, students should be capable of
advising on the best types of imagery, scales and analysis
procedures for information extraction. They should be capable
of undertaking various analyses using digital image analysis
software packages. They should also be able to transfer
information between digital image analysis systems and GIS
systems.
The course is divided into two parts with part I emphasizing
on lectures and part II on instructed project work and
presentation. The first 10 weeks (until March 31, 1995) will
be used for lecturing and lab exercise. During this time
period, students are required to read materials and
encouraged to question, discuss, and find answers on their
own. In addition, 4 - 5 3-hour lab instruction sessions will
be made. 8-10 assignments will be given. The last 5 weeks
will be allocated to project work. Each student is required
to undertake a project that must contain 4 components - use
of remotely sensed data, digital data processing, analysis of
results, and a project report. The project can be selected in
consultation with the student's major professor or the
instructor. The class hours will be used for each student
make progress reports. Problems encountered will be
discussed.
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Topics
1. Introduction to the Mapping Science
and Current Status of Sensing Technology
2. General Procedures in Remote Sensing
Image Analysis for Earth System Sciences
3. Major Components in Digital Image
Analysis
4. Remote Sensing Image Calibration
- Radiometric
- Geometric
- Topographic
5. Remote Sensing Image Enhancement
- Filtering
- Data reduction and transformation
- Texture measures
Midterm 1 - 1.5 hour. February 26,
1997 or on another day all agreed on
6. Interpreting Remotely Sensed Data
7. Conventional Image Classification
- Classification design
- Classifiers
- Separability measures
- Accuracy assessment
8. Contextural Classification and
Linear Feature Extraction
- Classification based on image preprocessing
- Frequency-based classification
- Algorithms for linear feature extraction
9. Change Detection
10. Multiple Data Source Integration
Midterm 2 - 2 hour. April 2, 1997 or on
another day all agreed on
Deadline for final project report: May
16, 1997
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Course Grading
| Work |
Percentage |
| Assignments |
25% |
| Midterm
Exam 1 |
15% |
| Midterm
Exam 2 |
30% |
| Progress
Report and Discussion |
10% |
| Project
report |
20% |
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Textbook
John R. Jensen, 1996. Introductory Digital Image
Processing, A
Remote Sensing Perspective, 2nd Ed. Prentice Hall, Englewood
Cliffs, New Jersey.
Gong, P., 1997. Remote Sensing and Image Analysis,
Unpublished
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References
1. James B. Campbell, 1987. Introduction to
Remote Sensing, The Guilford Press, New York.
2. John
A. Richards, 1993. Remote Sensing Digital Image Analysis, An
Introduction. Second Edition. Springer-Verlag, New York.
3.
Asrar, ed.,1989. Theory and Application of Optical Remote
Sensing, Wiley, Toronto.
4.
Etachi, C., 1987. Introduction to the Physics and Techniques
of Remote Sensing, Wiley, Toronto.
5.
Pratt, 1991. Digital Image Processing, Wiley, Toronto.
6.
Hobbs, R.J., and H.A. Mooney. 1989. Remote Sensing of
Biosphere Functioning. Springer-Verlag, New York.
7.
Ehleringer, J.R. and C.B. Field, 1992. Scaling Physiological
Processes, Leaf to Globe. Academic Press, Inc. San Diego.
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Major Journals
Canadian Journal of Remote Sensing
Cartographica
Cartography and Geographic Information Systems
Geographic Information Sciences
International Journal of Geographical Information Systems
International Journal of Remote Sensing
Photogrammetric Engineering and Remote Sensing
Remote
Sensing of Environment
IEEE
Transactions on Geoscience and Remote Sensing
