Geosciences 4400: Remote Sensing II: Digital Image Processing

Spring Semester 2016

Meeting Time:TR12:00 – 1:15 pm (Lecture)

R1:30 – 4:20pm (Lab)

Location:TR ScienceLabBuilding, Room 320 (SL 320)

R(Lab)SL 329 (GEAR Lab)

Instructor:Michael Hernandez

Department of Geosciences

Phone #:(801) 626-8186

Office:SL 203M (Mezzanine level between 2nd and 3rd floors)

Email:

Office Hours:TR: 10:30 am – 12:00 pm (SL 203M)

and by appointment

Required Texts

Jensen, John R. (2015) Introductory Digital Image Processing: A Remote Sensing Perspective, 4th Edition. Upper Saddle River, New Jersey: Pearson Prentice Hall. ISBN: 978-0134058160

OR

Jensen, John R. (2005) Introductory Digital Image Processing: A Remote Sensing Perspective, 3rd Edition. Upper Saddle River, New Jersey: Pearson Prentice Hall, 526 pp. ISBN: 0-13-145361-0

Additional Reading

There will be additional material you will need to review throughout the semester. Most will come from the ENVI or ArcGIS support documents. I will assign them at the appropriate time during the semester. The readings will support discussions on the course topics.

Course objectives

The objective of this advanced technical course is to build a strong foundation in the application of digital image processing techniques commonly used to manipulate and interpret remotely sensed imagery. The focus is on implementation of the various remote sensing concepts presented in the GEO 3400 course. Various image preprocessing, image analysis, image classification, and accuracy assessment techniques are examined in the lectures and implemented in the lab exercises. After successful completion of this course, you will have the knowledge needed to process, classify, and assess the accuracy of the most common types of multispectralremotely sensed imagery.

This lab-intensive course is divided into three major sections. First, an introduction to digital image processing of remotely sensed data, image/statistical display, and image preprocessing techniques are covered in both lectures and labs. Second, image analysis procedures (image enhancement, image classification, and change detection) are covered in lecture/lab. Finally, accuracy assessment procedures will be discussed and applied to classified imagery in a lab exercise.

Course Policies

Expectations: This is a 4-credit hour, scientific and technical course with a major lab component. Students are expected to spend 5.5 hours in class and an additional 10 to 12 hours per week outside of class on related course requirements (e.g., reading, completing lab assignments, reviewing lecture notes).

Attendance: Regular attendance is expected. You should be in the classroom prepared to begin work when class starts, as well as stay for the entire class period. The majority of test material and lab exercises will be presented in class. Therefore, it is important to attend all classes. You must have a valid excuse with documentation to make up exams or avoid grade penalties on late exercises and projects. Consideration for borderline grades will be given based on attendance and class participation. There will be NO EXTRA CREDIT ASSIGNMENTS or MAKE UP EXAMS (without a valid excuse).

Classroom Conduct: All cell phones must be turned off in class. There will be no eating or drinking allowed in the classroom or lab without prior consent. Also, as a courtesy to fellow classmates, please do not sleep during the lecture or hold conversations with classmates whenever the instructor or a student is speaking. These are distracting for both the instructor and class. If you must leave early, please inform me prior to the beginning of class and sit in a seat near the door. You are responsible for obtaining class notes and labs from fellow students if you miss class.

Grading: Final grades are based on overall performance, measured by the grades earned from the final exam, lab exercises, and a project assigned during the semester. This course will use the standard +/- grade scale in accordance with university policy. Final grades will be awarded using the following percentage scale that is based on the total number of points earned divided by the total number of available points (I reserve the right to make slight adjustments in the various cutoffs based on the total point average for the class. However, any adjustments will NEVER be upward, resulting in a lower grade.):

A92.0+%B-79.0-81.9%D+66.0-68.9%

A-89.0-91.9%C+76.0-78.9%D63.0-65.9%

B+86.0-88.9%C72.0-75.9%D-60.0-62.9%

B82.0-85.9%C-69.0-71.9%E<60.0%

Lab Exercises (40% of grade)

Final Project (40% of grade)

Final Exam (20% of grade)

Lab Exercises: You will be given lab exercises throughout the semester to teach specific topics relevant to understanding how to view, manipulate, classify, analyze, and assess remotely sensed images. You will attain a working knowledge of the capabilities (and limitations) of one of the specialized image processing software package (ENVI) as well as ArcGIS. This course will also prepare you with the fundamental skills needed as an entry-level imagery / geospatial analyst.

The lab exercises will be presented during the scheduled lab hours and completed outside of class. The Rules and Regulations for the lab will be reviewed the first week of the semester. This review will also include procedures on when you can access the lab. Due to the lab-intensive GIS and image processing courses being taught this semester, you will be required to sign up for lab PCs in 3-hour blocks.

Points will be taken away for turning in late assignments (ASSIGNMENTS NOT TURNED IN AT THE BEGINNING OF LAB ON THE DUE DATE) without a valid excuse. Your grade will be reduced 20% for each day it is late. Late assignments not turned in within 5 working daysof the due date will receive a failing score.

Final Project: The objective of the final project is to apply the knowledge that you’ve learned during the semester. This will allow you to demonstrate your understanding of digital image processing. More information on the project will be provided laterin the semester. Important dates are listed on the calendar.YOU MUST COMPLETE THE FINAL PROJECT TO PASS THE COURSE.

Final Exam: The exam will encompass all material presented in the lectures, readings, and lab exercises. It will includeshort answers, essays, and lab-based problems. The essays will consist ofone or two comprehensive questions that encompass the broad-based concepts presented throughout the course. Make up exams will only be given in special circumstances where the student has a valid university excuse or other legitimate reason provided they can present an acceptable signed note. Students must reschedule an exam prior to the exam date if they know they will not be able to take the exam during the scheduled class period.

Support Services for Students with Disabilities (ADA):Any student requiring accommodations or services due to a disability must contact Services for Students with Disabilities (SSD) in room 181 of the StudentServiceCenter. SSD can also arrange to provide course materials (including this syllabus) in alternative formats if necessary.

Academic Honesty: Every student should understand and adhere to WSU policies with regard to academic integrity and the consequences of violating such rules (see Student Code, Section IV: D). Academic honesty is fundamental to the university mission of both teaching and research. All members of the academic community must be confident that each person’s work has been properly acquired, developed, and presented. Any effort to gain an advantage not given to all students is dishonest. The academic community regards academic dishonesty as an extremely serious matter, and will result in the loss of credit in the assignment/exam, reduced grade in the course and further university disciplinary action according to the Student Code, Sections IV:D and X:A & B.

Academic dishonesty includes but is not limited to the following:

Cheating

Plagiarism

Collusion

Unauthorized possession of exams or reserve library material

Falsification of grades on exams, instructor’s grade book, or other grade records

Copyright infringement

Remember, when in doubt about plagiarism, paraphrasing, quoting, or collaboration, consult the course instructor or other faculty member for guidance.

Instructor Method of Contact Due to an Emergency: If class or lab is canceled (e.g., faculty illness, emergency – university code purple, weather-related campus closure, etc.) I will contact you via WSU Online message (i.e., Canvas) as the first option OR WSU email system as second option, with class-related information as soon as I am able to get online. If you have questions, contact the Department of Geosciences at 801-626-7139 or university information at 801-626-6000.

Important Dates:

01/12/16First class meeting

03/14/16 – 03/18/16SPRING BREAK

03/29/16 Last day to WITHDRAW (W), declare CR/NC or AUDIT for classes

04/21/16 Final presentations (lectureand lab periods)

04/25/16 Final projects DUE (NO EXCEPTION!!)

Tentative schedule (as of FEBRUARY 29, 2016)

Week

/

Date

/ Topics /

Required Readings

/ Labs Due
1 / 12 Jan
14 Jan / Review Syllabus
Digital Image Processing (DIP): overview / J2: Ch. 1
14 Jan / Lab 1: Introduction to ENVI
2 / 19 Jan
21 Jan /

Image acquisition (data collection) review

/ J2: Ch 2
21 Jan /

Lab 2: Exploring Imagery with ENVI

/ Lab 1
3 / 26 Jan
28 Jan / Image Statistics / J2: Ch. 4
28 Jan /

Lab 3

/ Lab 2
4 / 2 Feb
4 Feb / Visualizing imagery / J2: Ch. 5 (p. 164-172)
4 Feb / Lab 4 / Lab 3
5 / 9 Feb
11 Feb / Radiometric correction / J2: Ch. 6
11 Feb / Lab 5 / Lab 4
6 /

16 Feb

18Feb / Geometric correction / J2: Ch. 7
18Feb / Lab 6 / Lab 5
7 / 23 Feb
25 Feb / Image enhancement / J2: Ch. 8
25 Feb /

Lab 7

/ Lab 6
8 / 1Mar

3 Mar

/

Image enhancement (cont’d)

/ J2: Ch. 8
3 Mar / Lab 8 / Lab 7
9 / 8 Mar
10 Mar / Spring Break (no class)
10 Mar /

No Lab

/ ---
10 / 15 Mar

17 Mar

/ Remote Sensing-related field work

Final project assigned

/ O
17 Mar /

Lab 9

/ Lab 8
11 /

22 Mar

24 Mar / Image Classification (Thematic information extraction – pattern recognition) / J2: Ch. 9 & 10
24 Mar /

Lab 10

/ Lab 9
12 / 29 Mar
31 Mar / Thematic map accuracy assessment / J2: Ch. 13
31 Mar / Lab11 / Lab 10
13 / 5 Apr
7 Apr / TBD / TBD
7 Apr /

Work on final project

/ Lab 11
14 / 12 Apr
14 Apr / TBD / TBD
14 Apr /

Work on final project

/ ---
15 / 19 Apr

21 Apr

/ Work on final project
Final project presentations

21 Apr

/

Final project presentations

/ ---

25 Apr

23 - 28
Apr
23 - 28Apr / FINAL PROJECT REPORT DUE
------
Final Exam - available on ChiTester
(23 - 28 April)
Final Exam – Lab Component available on Chi Tester (23 - 28 April) – Will need GEAR Lab resources – ENVI software to complete.

J2 – Readings from Jensen – Introductory Digital Image Processing

O – Other readings

**LABS ARE DUE AT THE BEGINNING OF CLASS ON DATE SHOWN IN SCHEDULE**

1