Professor: Aaron Moody
Lectures: MWF 1:00-1:50, Johnston Center Rm 213
Office Hours: MW: 2:00 - 3:30
E-mail: aaronm@email.unc.edu
Office Phone: 962-5303
This course introduces the fundamental elements of the remote sensing process, the properties of remotely sensed data, and digital image processing methodologies. These topics will be covered in the context of a variety of natural resource applications, which involve the inference of Earth surface properties using remotely sensed data. An important goal of the course is to expose students to the range of technical approaches available for extracting surface information from digital satellite data. Students will also be introduced to the statistical and quantitative aspects of remote sensing and image processing methods. An emphasis is placed on remote sensing of vegetation, although those interested in atmospheric, aquatic, or geologic applications will benefit equally and are encouraged to enroll.
Remotely sensed data have become an integral tool for earth scientists and resource management specialists across a wide range of disciplines including forestry, ecosystem ecology, geology, climatology, oceanography, and agronomy. As such, we are in the midst of a rapid expansion in the variety and availability of satellite and aircraft-based digital data. This is met with a corresponding increase in the demand for personnel who understand and are able to extract information from such data sources. This demand is particularly high in areas of ecosystem modeling in the research arena, and resource monitoring and management in the public and private sectors. This class is intended to provide students with the fundamental background necessary to pursue remote sensing and digital image processing at a professional level. The course will be divided into four general topic areas:
I. Fundamentals of the Imaging Process & Characteristics of Satellite Data
II. Image Quality & Preprocessing
III. Image Display & Enhancement
IV. Information Extraction from Remotely Sensed Data
The format of this course consists primarily of lectures, readings, homework assignments and lab exercises (see bottom of page). There will be two exams (10/14/02 & 12/16/02). For graduate students, there will also be a final project with oral presentation and poster. The presentations will take place during the last one or two days of class. Posters are due the same day. Homeworks and labs are worth 50% of the grade. The exams are worth 25% each.
Richards, J. A. & Jia, X. 1999. Remote Sensing Digital Image Analysis: An Introduction, 3rd Ed., Springer-Berlag, Berlin, 363p.
Jensen, J. R. 1996. Introductory Digital Image Processing: A Remote Sensing Perspective, 2nd Ed., Prentice Hall, Upper Saddle River, NJ.
Lillesand, T. & Keifer, R. 2000. Remote Sensing & Image Interpretation, 4th Ed., Wiley & Sons, New York, NY.
Interesting Sites to Visit: TERRA More TERRA AQUA More AQUA TOPEX/Poseiden IKONOS Significant Event Imagery Remote Sensing Science in the News
Interesting Images: Lena River Delta Las Vegas Forestry Hong Kong Tokyo
I. Fundamentals of the Imaging Process & Characteristics of Satellite Data
II. Image Analysis, Display & Preprocessing
III. Image Enhancement & Interpretation
IV. Information Extraction from Remotely Sensed Data
V. Advanced Topics
Homeworks & Labs: Homework 1: Due 8/30/02 Homework 2: Due 9/16/02 Lab 1 Due: 9/9/02 Lab 2 Due: 9/23/02 Lab 3 Due: 9/30/02 Lab 4 Due: 10/7/02 Lab 5 Due: 10/28/02 Lab 6 Due: 11/4/02 Lab 7 Due: 11/11/02 Lab 8 Due: 11/18/02 Lab 9 Due: 11/25/02 Lab 10 Due: 12/2/02
Homeworks & Labs: Day 1