GEOGRAPHY 751

Digital Techniques of Remote Sensing

Spring Semester 2007
Lecture: Tuesday 2:00 - 3:30 pm
Lab: Tuesday 3:30 - 4:30 pm
Room: 005 Callcott
Office
Hours
Phone
John R. Jensen, Ph.D.  
Carolina Distinguished Professor  
johnj@gwm.sc.edu
327 Callcott
TUE 12:30 - 2:00 pm
7-5790
Zhongwu Wang, Ph.D. Candidate
Teaching Assistant
wangz@mailbox.sc.edu
318 Callcott
WED 2:00 - 4:00 pm
7-3657

  * PowerPoint lecture materials are at ftp://129.252.3.174.  You need the username (rs) and password (rsclass).
     Lecture materials are under Lecture folder.
** Exercise schedule may be adjusted a little and the actual datasets to be used in the labs will be linked soon.

Date
Subject
Reading  
Assignment
Jan 16
Chapter 1: Remote Sensing and Digital Image Processing (ppt)
EXERCISE #1 Introduction to the Remote Sensing Process (Due Jan 23)
Chapter 1
Jan 23
Chapter 2: Remote Sensing Data Collection (ppt)
EXERCISE #2 Image Display and Cursor Operations (Due Jan 30) 
Chapter 2
Jan 30
Chapter 3: Digital Image Processing Hardware and Software Considerations (ppt)
EXERCISE #3 Data Formats, Contrast Stretching, and Density Slicing (Due Feb 6) 
Chapter 3
Feb 6
Chapter 4: Image Quality Assessment and Statistical Evaluation (ppt)
EXERCISE #4 Image Statistics Using Spatial Modeler (Due Feb 13)

Chapter 4

Feb 13
Chapter 5: Initial Display Alternatives and Scientific Visualization (ppt)
EXERCISE #5 Image Annotation and Map Composition (Due Feb 20)

Chapter 5

Feb 20
Chapter 6: Electromagnetic Radiation Principles and Radiometric Correction (ppt)
EXERCISE #6 Radiometric Correction - Empirical Line Calibration (Due Feb 27)

Chapter 6

Feb 27
Chapter 7: Geometric Correction (ppt)
EXERCISE #7 Geometric Correction (Due Mar 6)
Chapter 7
Mar 6
Midterm Examination
Chapters 1~7
Mar 20
Chapter 8: Image Enhancement (ppt)
EXERCISE #8 Spectral Enhancement: Band Ratioing and Image Filtering (Due Mar 27)
Chapter 8
Mar 27
Chapter 8: Image Enhancement (continued)
EXERCISE #9 Spectral Enhancement: Image Indices and PCA (Due Apr 3)
Chapter 8
Apr 3
Chapter 9: Thematic Information Extraction: Pattern Recognition (ppt)
EXERCISE #10 Image Classification (Due Apr 10)

Chapter 9

Apr 10
Chapter 10: Thematic Information Extraction: Using Artificial Intelligence (ppt)
EXERCISE #10 Image Classification (continued)

Chapter 10

Apr 17

Chapter 12: Digital Change Detection (ppt)
EXERCISE #11 Change Detection of Coastal Vegetation (Due Apr 24)

Chapter 12

Apr 24

Chapter 13: Remote Sensing-derived Thematic Map Accuracy Assessment (ppt)
Final Project Help Session

Chapter 13

May 4

Friday - Final Examination at 9:00 am
This is the Registrar's scheduled time for the Geography 751 final exam. I provide no make-up examination unless there is a documented reason. See me at the beginning of the semester if you have an exam schedule conflict.

n/a

Required Texts:

Jensen, J. R., 2005, Introductory Digital Image Processing: A Remote Sensing Perspective, Upper Saddle River, NJ: Prentice Hall, 3rd Ed., 526 pages.

Jensen, J. R., 2007, Remote Sensing of the Environment: An Earth Resource Perspective, Upper Saddle River, NJ: Prentice Hall, 592 pages.

Exercises:

Every major topic will have an image interpretation and/or computation exercise associated with it. There will be a total of eleven exercises throughout the semester. These exercises need to be typed and handed in on the due date shown (in parentheses) above. Each exercise is worth 10 points. One point will be deducted for every day it is late.

Project/Paper:

A concise project is required. It is due four days prior to the Final Exam (Friday, April 28). You will take an original remote sensor dataset and apply algorithms of your choosing to it. I am especially interested in the quality and significance of the digital image processing you perform. I want to see a one (1) page creative image of your work in ERDAS Map Composition format and a maximum three (3) page paper including references describing your logic and results. Use scientific referencing in the text, such as "Jensen et al. (1995) radiometrically corrected the remote sensor data. A summary of radiometric correction methods is found in Jensen (2005)".

Grading Policy:

Lab Exercises
20 %
Midterm Examination
30 %
Project/Paper
20 %
Final Examination
30 %
100%
 

USC Remote Sensing
 


Last Modified: June 25, 2007