Dr. Ramanathan Sugumaran ("Sugu")
Email: sugu@uni.edu
Office: 216 ITTC
Phone: 319-273-3816
Mail box: 205 ITTC

Office hours: M F 12 – 1 or by appointment

Remote sensing is the science and art of collecting and interpreting information about the earth's surface through non-contact methods. Remote Sensing of the Environment teaches the theory and methodology of applied remote sensing technologies. We explore the principles of electromagnetic radiation, as well as the interactions of solar radiation with the earth's atmosphere and the three main classes of surface features--vegetation, soil, and water. The central portion of the course will be devoted to the characteristics of the multi-spectral sensor systems and data products of the earth-resources satellite systems from which data are the most accessible in the U.S.--Landsat , SPOT , and the NOAA Polar Orbiters. Computer processing of digital satellite images will be introduced. The concluding sections of the course will discuss thermal and active microwave (RadarSat and ERS2 ) remote sensing from satellites. New and future satellites will also be discussed including IKONOS , QuickBird Landsat 7 , SPOT 5 , EOS PM (Aqua), EOS AM (Terra), and LightSAR.

• Campbell, JB, 2002. Introduction to Remote Sensing, 3rd ed. The Guilford Press. New York, New York. 622p.

• The text for this course is Remote Sensing and Image Interpretation (Fourth Edition) which was written by Lillesand, T.M. and R.W. Kiefer: 2000, John Wiley.
• Jensen, JR, 1986. Introductory Digital Image Processing. Prentice-Hall. Englewood Cliffs, New Jersey. 379p.

The book that will be used for the practical component is "ERDAS Tour Guide" by ERDAS Imagine, 2001. The class will meet in Sabin 223. Each day we will first discuss the course readings and then we will do the practical exercises on the computers. You will not be able to finish the labs during the assigned time periods but the lab is open at the posted times if you do not finish. The practical exercises provide a way to acquire skills in using ERDAS Imagine to apply the course concepts to real data. Lab assignments should be submitted to the instructor at the beginning of the class period the follows the lab. Late labs will have 20% deducted per day.

Student performance will be evaluated on the basis of successful completion of the exams, lab assignments, project, and class participation. Each method is explained below.

Reading and homework assignments are given to supplement the lecture materials. Unless changed by the instructor, it is assumed that the student will have completed the assignment prior to coming to lecture on the due date. Several relatively brief homework exercises will be assigned during the semester to ensure that the pertinent procedures and concepts discussed in lecture are understood. Students are expected to work the homework individually and not collectively. Homework turned in after the due date but before the next class will receive 80 percent of the grade. Homework will not be accepted that is more than one class period late.

Three examinations, Exam1, Mid-Term and Final, will be given. Test1 and the Mid-Term Exam will include all materials assigned or presented through the previous weeks. More detailed on exams will be provided in class. The Final Exam will be given during the regular final exam week, at a place and time to be announced. It will include the material covered since the Mid-Term Exam.

Each class is critical to your semester-long learning experience. Your energy in contributing to class discussions, small-group exercises, and presentation will be important. Your grade for class participation will be based on attendance and participation in the group process such as class presentation etc.

The project is intended to provide a deeper understanding of a remote application through experience. The project should investigate a particular research problem and use the Erdas Imagine software package. You will need to acquire satellite data from the internet or from archives available in the Department of Geography. The project will be marked by a set of milestones from data collection, data management, data preprocessing, analysis and modeling, and result presentation. More detailed guidelines and requirements on class projects will be provided in class. Students are encouraged to freely discuss their project ideas with the instructor. During the last scheduled lab period, students will present their project to the class. The presentations can be no longer than fifteen (15) minutes and should use PowerPoint, overheads and/or slides. All assignments should be word-processed, double-spaced, using one side of the paper only with ample margins.

	Undergraduates	Graduate Students
Lab Assignments	45%	30%
Class Participation	10%	5%
Exam 1	15%	10%
Midterm	15%	10%
Final Exam	15%	10%
Final Project	0%	35%

Cheating, plagiarism and other forms of academic misconduct will not be tolerated under any circumstances. Any suspected or confirmed case of academic misconduct will be reported and pursued in accordance with University regulations.

Students having special needs/disabilities that require accommodations for successful completion of this course must notify both SWT’s Office of Disability Services (ODS) and the course instructor by no later than the end of the first week of classes. The ODS is located at: 213 Student Services Center and the phone number is: 273-2676.