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Credit Hours: 3
Description: This course will provide the requisite materials to understand advanced hyperspectral imaging (HSI) technology and multi-sensor concepts. It will cover many civil and military applications. The emphasis will be on the scientific principles involved and the transition of the technology to real world applications. Topics that will be covered include Advanced Hyperspectral Concepts, Multi-System Tradeoffs, Data Collection and Processing Systems, Imaging Radar Systems, Laser Systems, Calibration Techniques, Data Fusion, Quantitative Remote Sensing Techniques, Case Studies, and U.S National Policy. The quantitative remote sensing techniques will include N-Dimensional Analysis to include literal and non-literal information extraction techniques. Applications and case studies will include environmental, homeland security, medical, military, anti-terrorism, disaster mitigation, agricultural, transportation, and others. Ground, airborne, and spaceborne multi-sensor remote sensing systems are covered.
Course Objective: To provide students with an introduction to modern advanced hyperspectral remote sensing techniques and the basic fundamental physics involved in this technology. The course will prepare the student to (1) undertake graduate advanced research in hyperspectral and multi-sensor literal and non-literal data processing, (2) prepare the student to participate in professional activities in this field of study, (3) broaden the student’s background in the general field of quantitative spectral remote sensing, and (4) prepare the student to explore finding applications of this enabling technology to areas of interest to specific users.
Prerequisites: An introductory course on Remote Sensing, or Earth Science, or Atmospheric Physics, or Hyperspectral Imaging, and an Undergraduate Degree in the Physical Sciences, or Permission of Instructor.
Text: Remote Sensing Digital Image Analysis: An Introduction, John A. Richards and Xiuping Jia, 3rd Revised and Enlarged Edition, Springer-Verlag, Berlin, 1999.
Grading: Assigned Project and Oral Presentation – 60%
Mid-Term Take-Home Exam – 25%
Class Participation and Assignments – 15%
Instructor: Dr. Richard B. Gomez (rgomez@gmu.edu)
Office: George W. Johnson Center, Room 237
Office Hours: Tuesdays 2:30 to 5:30 pm (other hours by appointment)
Office Phone: (703) 993-3629
Class Place, Dates, and Times: Innovation Hall, Room 320, Wednesdays 4:30 pm to 7:10 pm. First day of class is 1 September 2004 and last day of class is 8 December 2004.
EOS 840-001 Course Outline “Hyperspectral Imaging Applications” (Fall 2004)
Course Section Topics Number of Weeks
Part I. Introduction to Imaging Spectrometry 2
- Spectral Sensing Concepts
- Literal and Non-Literal Information
- Multi-Sensor Concepts
- Hyperspectral Systems
- Scientific Principles
- Remote Sensing Physics
- Physics of Imaging Spectroscopy
- Sensor Physics
Part II. Atmospheric Effects 2
Part III. Hyperspectral Concepts and Multi-System Tradeoffs 2
- Spectral/Spatial Resolution, Sampling, Range
- Signal-to-Noise Ratio (SNR)
- Dispersion Techniques
- Display and Data Models
- Current HSI Active and Passive Systems
- Ground
- Airborne
- Spaceborne
Part IV. Calibration Techniques 1
- Calibration Needs
- Calibration Process
- Calibration Systems
Part V. Multi-Sensor Analysis 3
Quantitative Remote Sensing Techniques
- Imaging Radar
- Laser Systems
- N-Dimensional Analysis and Visualization
- Pattern Recognition
- Principal Component Analysis (PCA)
- Spectral Matching
- Spectral Libraries
Part VI. Data Fusion Techniques 1
- Wavelets
- Neural Network Approach
Part VII. Multi-Sensor Applications and Case Studies 2
U.S. National Policy Issues
Part VIII. Class Project Presentations 1
FALL SEMESTER 2004
Course Project: Select a topic that is related to the subject matter of this course and write a scientific paper suitable for publication in an acceptable journal and or scientific conference. Present and defend your paper in class. The paper may be co-authored with another class member, but each student will be evaluated by me on the quality of his or her contribution to the paper. The paper can deal with policy and or other issues that are affecting the use of hyperspectral technology, such as potential markets and risk management. You can also write a computer program and or present a case study for publication. The application may address military, civil, academic, or commercial users. Any part of the spectrum may be used and any other sensor may be considered with the hyperspectral sensor, i.e., sensor fusion.
The goal is to enrich your exposure to the field of remote sensing with the emphasis on hyperspectral technology. It is not acceptable for you to report on a paper that you have already presented in the open literature and/or internal report in your work place. Feel free to discuss potential topics with me and with your class members. However, I must approve your topic before you start working on it.
The quality of the paper, the thoroughness of the study, and the organization of your thoughts, plus the correctness of the physics, will be paramount to the grading of your project. All presentations and submission of papers for publication must be completed by 8 December 2004. I encourage you to submit your paper for publication. It does not need to be accepted by the journal or conference that you submitted your paper for publication or presentation for you to get credit for your efforts in this course. I will be the judge of that.
Potential Topics may be in the field of:
Environmental Applications (wetlands, hydrology, monitoring, etc.)
Homeland Security
Precision Agriculture
Health Care (food safety, medical diagnoses, etc.)
Spectrum Exploitation (e.g., infrared exploitation)
Transportation Applications (traffic flow, disaster management, etc.)
Spectral Library Architecture
Land Mine Detection
Chemical and Biological Detection
Law Enforcement
Littoral Studies (bathymetry, water clarity, etc.)
City Planning and Real Estate
Disaster Mitigation
Camouflage, Concealment, Detection
Sensor Fusion (SAR plus HSI and/or Laser)
Image Processing Tools (computer algorithms)