GEO-SCI426/626
Remote Sensing and Image Interpretation
Department of Earth, Geographic, and Climate
Sciences
University
of Massachusetts - Amherst
4
cr, Fall 2023
Notes, lab and assignments will be updated on the Canvas.
Lecture TuTh 1-2:15 am 225 Morrill Sci. Ctr.
Lab Tu
2:30-4:30 pm 212 Morrill IV South (UMass
IT lab) (No lab on 9/5. First lab on 9/12)
Instructor Prof. Qian Yu, Morrill 267, qyu@umass.edu, Office hour: Mon 1:30-2:30, Thu 10-11 or by appt
TA Hutch Tyree, Morrill 264, qtyree@umass.edu, Office hour: Tues Wed TBA or by appt
Course
description
This
course introduces the fundamentals of remote sensing. Class lectures will focus
on a range of concepts and techniques key to understanding how remote sensing
data are acquired, displayed, restored, enhanced, and analyzed. Topics include
remote sensing principles, aerial photography, image interpretation, major
remote sensing systems, image display and enhancement, information extraction,
accuracy assessment, and remote sensing in environmental research and
applications. First half of the semester focuses on theory of remote sensing.
In the second half, we have several hands-on computer labs to gain experience
using the image processing software ENVI. We will also explore a range of
practical issues related to the application of remote sensing to solve real
world problems. Overall, this class emphasizes remote sensing theory and
knowledge.
Course objectives
To provide you with an introduction
to the principles and practices of photo interpretation and digital remote
sensing for use in environmental monitoring, measurements of structural
parameters, and natural resource management.
This class will ensure students
have knowledge on these aspects:
1.
the properties and characteristics of aerial photographs.
2.
remote sensing systems: a) how to define the type of remote sensing
needed to fulfill the user’s stated objectives, b) where existing remote
sensing data which fulfills his/her objectives may be located, and c) how to
obtain new aerial photography, if necessary.
3.
digital image processing: a) basic concepts on non-photographic remote
sensing, b) general principles of digital image processing for remote sensing
applications, and c) future applications of remote sensing to natural resource
management and related fields.
4.
remote sensing information extraction: a) which characteristics of land
cover types can be mapped/measured from remote sensing, b) different techniques
available for mapping and measuring these land cover types, and c) how
accurately these land cover characteristics can be mapped from remote sensing.
Prerequisites: High
school Geometry, Algebra 2, and precalculus.
Required textbook for
lectures
1.
Jensen, John R., 2016, Introductory Digital
Image Processing: A Remote Sensing Perspective, Pearson,
4th ed. ISBN 978-0-13-405816-0.
* Digital,
hardcopy, any format is fine. The book is on reserve in the library.
Reference book for
lectures
2.
Jensen, John R., 2007, Remote Sensing of the Environment: An Earth
Resource Perspective, Prentice Hall: Upper Saddle River, NJ. 2nd ed. ISBN
0-13-188950-8
3.
Lillesand,
Kiefer and Chipman, Remote Sensing and Image Interpretation, Wiley.
4.
Sabins, Floyd and James Ellis. Remote Sensing: Principles, Interpretation,
and Applications,
Waveland Press.
* Reference books are not part of the reading. They are
listed as courtesy as some of my lecture figures are from those sources.
Lab
software access
A professional
remote sensing software ENVI will be used for most of the labs. ENVI is
installed in 212 Morrill. You can also access ENVI through UMass Azure Virtual
Desktop. You can find the instruction on how to access AVD here.
https://www.umass.edu/it/computer-classrooms/windows-virtual-desktop
Grading
and evaluation
|
Exercises and
assignments Mid-Term Exam Final Project Presentation Class
participation& attendance |
30% 30% 25% 8% 7% |
-
All written assignments must be handed
in on time.
-
Mid-exams will cover key concepts from lecture, readings and
remote sensing theories.
-
Presentation:
426
students will present a satellite sensor.
626 students will present a journal paper about
remote sensing application in your field.
-
Attendance will be accessed by class
participation, taking rolls at random dates and pop quiz.
Policy on attendance and due dates for assignments:
·
The class is taught
in person with zoom recording for lectures!
426
students must take the course in-person. For most students taking the class in
person, attendance to both lecture and lab session is required in the normal
circumstances and forms a portion of your grade. Lectures and some lab
tutorials will be recorded for the convenience of review. This does not mean
you are free to skip lectures or labs. For absences due to health reasons,
family illness, religious observance or other extenuating circumstances,
students should inform the instructor in a timely fashion. Verification
document is requested for alternate arrangements to be made. It is the
responsibility of the student to review the lecture recording in the event the
student cannot attend class. A google form is created to record excused
absences. https://forms.gle/C5gQa2mjMb4P2h4r7
The
class is also open to 626 students who enrolled in GIST Masters program online
and need to take the course by zoom live stream or asynchronously. Please fill
out the pre-class survey and get approval from the instructor at the beginning
of the semester. We also want to know how to
help your remote learning.
· Assignment late submission policy Both due date and late due date are noted in each assignment. The late due date is normally 7 days after the due date. For the assignments right before mid-term and near the end of the semester, the late due date could be shortened (e.g., 3 days late due) or no late due allowed. The purpose is for me to give out the assignment answers earlier for mid-term preparation. In all, late due date printed on the assignment should be followed.
All
exercises must be turned in by the due date for full credit unless arranged with the instructor before
the deadline. Each student has one chance of late submission
(before late due date) with no point deduction during the semester. Other late
submissions before late due date without advance permission by the instructor
will cause a grade deduction. No lab
assignment will be accepted after late due date. By that time,
the assignment answers will be released.
|
Late submission |
1-3 days |
4-7 days |
>7 days or after late due date |
|
Point deduction |
1/4 |
1/2 |
Not accepted, the assignment
answers will be released |
The instructor
could grant extension for excused late submission. Please email the instructor
to request an extension.
·
Assignments
should be submitted through Canvas. Any submission made by email
attachment or link to your shared document will not be considered for grading
and meeting deadline.
·
Mid-term is close book and the schedule on
syllabus is only tentative. No make-up exams will be given unless PRIOR
arrangements have been made with instructor and documentation of excused must
be provided.
·
Missing mid-term exam, presentations, final
project presentation, project report, or >=3 homework will result in an F
for the course regardless of the final grade.
Disability Accommodations
The University of Massachusetts Amherst is committed
to providing an equal educational opportunity for all students. If you have a
documented physical, psychological, or learning disability on file with
Disability Services (DS), you may be eligible for reasonable academic
accommodations to help you succeed in this course. For disability
accommodations, please register with Disability Services as early as possible.
Meanwhile please notify the instructor through the pre-class survey or email
within the first two weeks of the semester so that we may make appropriate
arrangements. DS accommodation request must be filed each
semester. Do not expect the request will be automatically carried over.
Policy on class materials and recordings
Students can only use the lecture notes and
the notes they take from class for their own personal use, and not share (sell)
these notes via an outside vendor or entity without the faculty/instructor’s
permission. This pertains to in-class
recordings as well. Usage of the notes
or in-class recordings in this way without the faculty member’s permission is a
violation of the faculty member’s copyright protection.
This does not pertain to accommodations under
the Americans with Disabilities Act (ADA), although recordings or sharing of
notes for ADA accommodations should not pertain to distribution beyond the
students in the class receiving the accommodations.
Academic Honesty Policy
Since the integrity of the academic enterprise of any
institution of higher education requires honesty in scholarship and research,
academic honesty is required of all students at the University of Massachusetts
Amherst. Academic dishonesty is prohibited in all programs of the University.
Academic dishonesty includes but is not limited to: cheating, fabrication,
plagiarism, and facilitating dishonesty. Appropriate sanctions may be imposed
on any student who has committed an act of academic dishonesty. (http://www.umass.edu/dean_students/codeofconduct/acadhonesty/).
·
All work submitted must be your own in
presentation. You may discuss homework and final project with other students
(you are encouraged to do so), but the homework and project write-up must be
your work.
·
Copying homework is not allowed, and collaboration
so close that it looks like copying is not allowed. Violation will be reported
to the UMass Academic Honesty Board.
·
In write-up, if you make use of a printed or
on-line source as reference, you need to cite it and mention it.
Class Schedule (subject to change according to the progress)
This table will be updated through the
semester. Schedule could change according to our progress and reading will be
filled in. You can direct access by the following URL. This URL is also posted
in Canvas.
http://www.geo.umass.edu/courses/geo426/