GEOG 883
Remote Sensing Image Analysis and Applications

GEOG 883 Syllabus


GEOG 883: Remote Sensing Image Analysis and Applications

This syllabus is divided into several sections. You can read it sequentially by scrolling down the length of the document or by clicking on any of the links below to “jump” to a specific section. That being said, it is essential that you read the entire document as well as material covered in the Orientation. Together, these serve the role of our course "contract."


Jarlath O'Neil-Dunne

John A. Dutton e-Education Institute
Pennsylvania State University

Course Overview


A graduate level course focusing on remotely sensed data for geospatial applications. This course assumes that students have prior knowledge in the basics of remote sensing, mapping, and GIS, and have experience with geospatial software, particularly ArcGIS. Students will develop a strong understanding of the tools and techniques used to display, process, and analyze remotely sensed data. Upon completion of GEOG 883 students will be able to develop analytical workflows to derive products and extract information from remotely sensed data for a broad range of applications. The culmination of this course is a independent final project in which students will demonstrate their ability to apply new skills to a real-world situation of personal or professional interest.


GEOG 480, 482, 483, or equivalent professional experience. A strong working knowledge of ArcGIS Desktop is expected of students who register for this course.


The course is specifically designed for adult professionals and is offered exclusively through the World Campus and the John A. Dutton e-Education Institute of the College of Earth and Mineral Sciences. Students who register in the course for credit will complete an orientation lesson and seven content lessons with corresponding hands-on assignments, quizzes, and online discussions, in addition to a final project. Throughout the course, students confront realistic problem scenarios that will test their ability to apply the tools and techniques covered in the course.

Students who register in the course for credit will complete seven lessons with corresponding hands-on assignments, online discussions, and a final project. Throughout the course, students confront realistic problem scenarios that incorporate such skills and concepts as definition of data needs, metadata content standards, data formats and types, and analysis methods.

What will be expected of you?

This course will require a minimum of 12-15 hours of student activity per week. You will be glad to know you don't have to show up for class at a certain time as the class is self-paced, but you will have to meet assignment deadlines.

Each lesson consists of a combination of reading assignments from the course website and required textbook, video demonstrations, and links to external materials that may assist you. Quizzes are periodically offered to test your comprehension of this material. The bulk of your grade will be tied to lab assignments. The labs are designed to test your ability to construct and execute remote sensing workflows using geospatial software. Lab instructions for each lesson are provided in PDF form for you to download and print for reference as you proceed through the hands-on exercises with data and software. Prerecorded video demonstrations of the lab exercise may be provided to assist you. You will submit your lab work in the form of a Canvas assessment. You are encouraged to ask questions and post comments at any time in the Canvas Discussion Forums provided for each lesson. E-mail communication to the instructor should only be used in those cases where the material is not appropriate for viewing by the entire class.

You should get in the habit of checking course e-mail and discussion forums in Canvas on a daily basis. That's where students and instructors share comments, pose questions, and suggest solutions to problems. With only occasional exceptions, instructors check e-mail and forums every day, and will try to respond to your questions and concerns within 24 hours.

For a more detailed look at what will be covered in each lesson, please refer to the Course Content part of this syllabus. Due dates for assignments and activities will be posted on the Calendar tab in Canvas.

Course Objectives

Upon completion of the course, students who excel are able to:

  • process remotely sensed data to make it useful in geographic information systems;
  • perform image enhancement on remotely sensed imagery;
  • extract information from remotely sensed data using a variety of manual and automated techniques;
  • critically assess the strengths and weaknesses of remote sensing instruments and platforms for a variety of application scenarios;
  • develop multi-step remote sensing workflows to solve problems in a variety of application areas;
  • apply acquired knowledge and critical thinking skills to solve a real-world problem with appropriate remote sensing data and processing methods.
  • clearly and concisely communicate findings from the analysis of remotely sensed data through the written word and graphical products.

Required Course Materials

In order to take this course, you need to have the required course materials and an active Penn State Access Account user ID and password (used to access the online course resources). If you have any questions about obtaining or activating your Penn State Access Account, please contact the Outreach Helpdesk.

Required Textbooks

Campbell, James B. 2011. Introduction to Remote Sensing, 5th edition. New York. The Guilford Press. ISBN 978-1609181765

There is one required textbook for this course. It can be purchased through a number of commercial booksellers, such as Amazon. Please be sure that you acquire the correct edition.

An electronic version of the text can also be accessed online from the Penn State Library eReserve. The number of pages that can be read or printed is limited, so we recommend that you purchase a hard copy and use the electronic version for quick searches. To access the textbook online:

  • Go to the University Library web page.
  • Log in using your Penn State Account
  • In the search box enter "Introduction to Remote Sensing" in the Search field, and click Search.
  • Select "Introduction to remote sensing [electronic resource] 5th ed." in the Search results.
  • Click on the resulting link provided for online content.

Supplemental References (No Purchase Necessary)

Additional readings may be provided electronically through the course management system and Penn State library services. These readings may include, but are not limited to, the following sources. These are also useful references for final project development.

Congalton, R. and K. Green. 2009. Assessing the Accuracy of Remotely Sensed Data. 2nd edition. CRC Press. ISBN 978-1-4200-5512-2.

Maune, D. F., ed. 2007. Digital Elevation Model Technologies and Applications: The DEM Users Manual, 2nd edition. Bethesda, MD. American Society for Photogrammetry and Remote Sensing. ISBN 1-57083-082-7.

McGlone, J. C., ed. 2004. Manual of Photogrammetry, 5th edition. Bethesda, Md.: American Society for Photogrammetry and Remote Sensing. ISBN 1-57083-071-1.

Renslow, M. S., ed. 2012. Airborne Topographic Lidar Manual. Bethesda, MD. American Society for Photogrammetry and Remote Sensing. ISBN 1-57083-097-5.

Wolf, P. and B. Dewitt. 2000. Elements of Photogrammetry, 3rd edition. Boston. McGraw-Hill. ISBN 0-07-292454-3.

Photogrammetric Engineering and Remote Sensing, American Society for Photogrammetry and Remote Sensing.

Required Software

Be sure to read the Technical Requirements section at the end of the syllabus for minimum system requirements. You need an administrator password for your computer in order to properly install the course software.

  1. ArcGIS Desktop, Esri
    All students in the Online Geospatial Program receive a student license of ArcGIS valid for one year. Instructions for obtaining a license and installing the ArcGIS are provided in the Canvas folder for Lesson 0 - Orientation.
  2. eCognition, Trimble
    All students in this course will receive a fully functioning version of eCognition with a license valid for the duration of the course. Licenses will be issued by the instructor during the first week of class. Instructions for downloading and installing the software are provided in the Canvas folder for Lesson 0 - Orientation.
  3. 7-Zip (or similar)
    You will need a file utility capable of unzipping .zip and .tar.gz files. 7-Zip can be downloaded for free from
  4. Screen Capture Utility
    SnagIt (paid), Jing (free), or use the built-in Windows snipping utility.You will need a file utility capable of unzipping .zip and .tar.gz files. 7-Zip can be downloaded for free from

Supplemental Software Tutorials

Registered students have access to the Esri Virtual Campus courses free-of-charge. These courses are available for students who wish to review or enhance their ArcGIS skills in preparation for or during the course. Specific Virtual Campus courses may be assigned as part of the weekly lab activities; in which case the instructor will provide access codes. Visit the Penn State Esri Virtual Campus Subscription page to request access codes for any other Virtual Campus courses that are of interest.

Free tutorials for other commercial software used in this course are available directly from the vendor websites.

Using Penn State Library Resources

Many of Penn State's library resources can be utilized from a distance. Through the Library Resources and Services for World Campus and Distance Education site, you can...

  • access electronic databases, and even full text articles, from the LIAS Fast Track;
  • borrow materials and have them delivered to your doorstep...or even your desktop;
  • access materials that your instructor has put on Electronic Reserve;
  • talk to reference librarians in real time using the "Virtual Reference Service;"
  • ...and much more.

NOTE: You must be registered with the University Libraries in order to take full advantage of the Libraries' resources and services. Registration and services are free.

Assignments and Grading

Students earn grades that reflect the extent to which they achieve the learning objectives listed above. Opportunities to demonstrate learning include:

  • Online quizzes (10% of final grade)
  • Online discussions (8% of final grade)
  • Lab activities (52% of final grade)
  • Final project (30% of final grade)

Lesson weeks begin on Wednesdays per the course calendar in Canvas. Actitivies are due at the end of each lesson week, at 11:59 PM Eastern on Tuesday. Students who will be unable to meet the deadline for a given week must contact the instructor at least 24 hours prior to the deadline to request an extension. Online sessions will be held in Adobe Connect to review weekly labs and provide feedback; therefore, late submittals will not be accepted if an extension has not been granted and a zero will be entered in the gradebook for that assignment.

The final grading scale is shown below.

Letter Grade Percentages Points
Letter grades and percentages
A 93% and above 465 points and above
A- 90% - 92.9% 450 - 464 points
B+ 88% - 89.9% 440 - 449 points
B 83% - 87.9% 415 - 439 points
B- 80% - 82.9% 400 - 414 points
C+ 78% - 79.9% 390 - 399 points
C 70% - 77.9% 350 - 389 points
D 60% - 69.9% 300 - 349 points
F 59.9% and below 299 points and below

Class participation will be considered in grading for those whose final course grade is close to the next letter grade. To view your progress throughout the semester, click on the Grades tab in the Canvas course interface.

GEOG 883 Course Schedule

image Printable Schedule
Lesson 0: Orientation
Date Week 1
  • navigate between the course website and the Canvas course management system;
  • express your expectations about how and what you will learn in your online course;
  • articulate how and what instructors expect you to learn in your online course;
  • locate key information about the course, including assignments, due dates, technical information, and where to go for help;
  • locate detailed information about course policies, including academic integrity and accomodations for disabilities;
  • communicate effectively with instructors and fellow students using a variety of online tools.
  • Orientation Material
  1. Orientation Survey (5 points)
  2. VoiceThread Introductions (5 points)
  3. Lesson 0, Lab 1 (10 points)
  4. Lesson 0, Lab 2 (10 points World Campus, 5 extra credit points University Park)
Lesson 1: The Remote Sensing Analytical Process
Date Week 2
  • Describe the basic principles of remote sensing
  • Explain the remote sensing workflow
  • Analyze remotely sensed data using the principles of the remote sensing workflow
Readings None
  1. Lesson 2 Lab (40 points)
  2. Lesson 2 Graded Discussion (5 points)


Lesson 2: Preprocessing of Remotely Sensed Data
Date Week 3
  • apply spatial preprocessing techniques to image data;
  • apply spectral preprocessing techniques to image data;
  • manage image data using mosaics and compression;
  • create surface models from lidar data.
  • Campbell (2011) Introduction to Remote Sensing. 5th Edition. Chapter 4 - Digital Imagery
  • Campbell (2011) Introduction to Remote Sensing. 5th Edition. Chapter 8 - Lidar
  • Campbell (2011) Introduction to Remote Sensing. 5th Edition. Chapter 10 - Image Resolution
  • Campbell (2011) Introduction to Remote Sensing. 5th Edition. Chapter 11 - Preprocessing
  1. Lesson 3 Reading Quiz (10 points)
  2. Lesson 3 Lab (30 points)
  3. Lesson 3 Graded Discussion (5 points)


Lesson 3: Image Interpretation
Date Week 4
  • define the elements of image interpretation
  • interpret remotely sensed data using the elements of image interpretation
  • construct an image interpretation key
  • Campbell (2011) Introduction to Remote Sensing. 5th Edition. Chapter 5 - Image Interpretation
  • The following three papers are available in the Lesson 5 folder on Canvas:
    • Oliva, A. 2005. “Gist of the Scene.” Neurobiology of Attention 17.
    • Olson, C.E. 1960. “Elements of Photographic Interpretation Common to Several Sensors.” Photogrammetric Engineering 26 (4): 651–656.
    • Olson, C.E. 2009. “Is 80% Accuracy Good Enough?” In Proceedings of the ASPRS 17th Pecora Conference.
  1. Lesson 4 Reading Quiz (10 points)
  2. Lesson 4 Lab (30 points)
  3. Lesson 4 Graded Discussion (5 points)
Lesson 4: Feature Extraction
Date Week 5
  • discuss pixel and object-based approaches to feature extraction
  • discuss supervised and unsupervised approaches to feature extraction
  • carry out a classification using spectral information
  • carry out a classification using geometric information
  • carry out a classification using texture information
  • carry out a classification using contextual information
  • analyze multispectral imagery and lidar using object-based techniques
  • create an object-based workflow for extracting information from multiple types of geospatial data
  • Campbell (2011) Introduction to Remote Sensing. 5th Edition. Chapter 12 - Image Classification
  • Campbell (2011) Introduction to Remote Sensing. 5th Edition. Chapter 14 - Accuracy Assessment
  • Campbell (2011) Introduction to Remote Sensing. 5th Edition. Chapter 20 - Land Use and Land Cover
  1. Lesson 5 Reading Quiz (10 points)
  2. Lesson 5 Lab (30 points)
  3. Lesson 5 Graded Discussion (5 points)


Lesson 5: Change Detection
Date Week 6
  • detect thematic change over time from two dates of multispectral imagery
  • detect thematic change over time using lidar data
  • detect thematic change from radar data using coherent change detection techniques
  • Campbell (2011) Introduction to Remote Sensing. 5th Edition. Chapter 16 - Change Detection
  1. Lesson 6 Lab (40 points)
  2. Lesson 6 Graded Discussion (5 points)


Lesson 6: Accuracy Assessment
Date Week 7
  • discuss the principles of classification accuracy assessment;
  • construct an accuracy assessment error matrix;
  • apply the principles of classification accuracy assessment in a typical application setting;
  • design and deploy a workflow for mapping an urban heat island;
  • detect thematic change over time from two dates of multispectral imagery;
  • detect thematic change from radar data using coherent change detection techniques;
  • formulate an integrated workflow for mapping inundation areas.
Readings None
  1. Lesson 7 Lab (40 points)
  2. Lesson 7 Graded Discussion (5 points)

Final Project: Leveraging Remotely Sensed Data to Confront Contemporary Challenges in Geospatial Analysis
Date Week 9-10

This project will challenge students to apply knowledge and skills acquired in the earlier lessons in a realistic problem scenario that requires acquisition and analysis of remote sensing data. Project activities will span the final four to five weeks of the session. Students will work individually to scope a problem, determine the appropriate combination of remote sensing data and application software needed to support analysis, propose a processing and analysis workflow, and move to a solution. The students will then produce a final report that discusses their understanding of the problem, a detailed discussion of the workflow steps, and results of their study.

Readings None
  • Final Project Idea (10 points)
  • Final Project Idea Peer Reviews (5 points)
  • Final Project Proposal (30 points)
  • Final Project Proposal Peer Reviews (5 points)
  • Final Project Presentation (25 Points)
  • Final Project Presentation Peer Reviews (5 points)
  • Final Report (35 points)
  • Final Project Data Deliverable (30 points)
  • Final Project Abstract (Optional)

Lesson 7: Applications - Urban Heat Island
DATE Week 8
  • integrate remotely sensed and GIS data
  • apply zonal functions to summarize raster information by vector polygons
  • perform a qualitative and qualitative analysis of spatial data
  • Campbell (2011) Introduction to Remote Sensing. 5th Edition. Chapter 9
  1. Lesson 7 Lab (40 points)
  2. Lesson 7 Graded Discussion (5 points)

Course Policies

Use of Software

In this course, you are provided with access to both software and data. Under no circumstances should you use either the software or the data for purposes other than this course without written permission from the instructor.

Technical Requirements

For this course, we recommend the minimum technical requirements outlined on our "Program Technical Requirements" page. If you need technical assistance at any point during the course, please contact the Outreach Helpdesk (for World Campus students) or the IT Service Desk (for students at all other campus locations).

Internet Connection

Access to a reliable broadband Internet connection is required for this course. A problem with your Internet access may not be used as an excuse for late, missing, or incomplete coursework. If you experience problems with your Internet connection while working on this course, it is your responsibility to find an alternative Internet access point, such as a public library or wireless hotspot.

Mixed Content

This site is considered a secure website, which means that your connection is encrypted. We do, however, link to content that isn't necessarily encrypted. This is called mixed content. By default, mixed content is blocked in Internet Explorer, Firefox and Chrome. This may result in a blank page or a message saying that only secure content is displayed. Follow the directions on our technical requirements page to view the mixed content.


This course must be viewed using one of the following browsers: Firefox (any version), Safari (versions 5.1 or 6.0), Chrome (0.3 or later), or Internet Explorer with the MathPlayer PlugIn. If you use any other browser, there will be pages containing equations that do not render properly. If you need technical assistance at any point during the course, please contact the Outreach Helpdesk (for World Campus students) or the IT Service Desk (for students at all other campus locations).

Penn State E-mail Accounts

All official communications from the Penn State World Campus are sent to students' Penn State e-mail accounts. Be sure to check your Penn State account regularly, or forward your Penn State e-mail to your preferred e-mail account, so you don't miss any important information.

Academic Integrity

This course follows the guidelines for academic integrity of Penn State's College of Earth and Mineral Sciences. Penn State defines academic integrity as "the pursuit of scholarly activity in an open, honest and responsible manner." Academic integrity includes "a commitment not to engage in or tolerate acts of falsification, misrepresentation, or deception." In particular, the University defines plagiarism as "the fabrication of information and citations; submitting others' work from professional journals, books, articles, and papers; submission of other students' papers, lab results or project reports and representing the work as one's own." Penalties for violations of academic integrity may include course failure. To learn more, see Penn State's "Plagiarism Tutorial for Students."

Course Copyright

All course materials students receive or to which students have online access are protected by copyright laws. Students may use course materials and make copies for their own use as needed, but unauthorized distribution and/or uploading of materials without the instructor’s express permission is strictly prohibited. University Policy AD 40, the University Policy for the Recording of Classroom Activities and Note Taking Services addresses this issue. Students who engage in the unauthorized distribution of copyrighted materials may be held in violation of the University’s Code of Conduct, and/or liable under Federal and State laws.

Accommodations for Students with Disabilities

Penn State welcomes students with disabilities into the University's educational programs. Every Penn State campus has an office for students with disabilities. The Student Disability Resources (SDR) website provides contact information for every Penn State campus: Contacts for Disability Services at all Penn State Campuses. For further information, please visit the Student Disability Resources (SDR) website.

In order to receive consideration for reasonable accommodations, you must contact the appropriate disability services office at the campus where you are officially enrolled, participate in an intake interview, and provide documentation. If the documentation supports your request for reasonable accommodations, your campus’s disability services office will provide you with an accommodation letter. Please share this letter with your instructors and discuss the accommodations with them as early in your courses as possible. You must follow this process for every semester that you request accommodations.

Mental Health Services

Whether you study on campus or online, mental health services are available to help you maintain your academic success. Penn State provides resources to address concerns including anxiety, depression, relationship difficulties, and stress, and provides mental health advocates who can help you. If you are a resident student, resources can be found at Counseling and Psychological Services. If you are a World Campus student, please see the student website for further information. If you or someone you know is experiencing a crisis situation, please call your local emergency service.

Military Personnel

Veterans and currently serving military personnel and/or spouses with unique circumstances (e.g., upcoming deployments, drill/duty requirements, disabilities, VA appointments, etc.) are welcome and encouraged to communicate these, in advance if possible, to the instructor in the case that special arrangements need to be made.

Inclement Weather

In case of weather-related delays at the University, this online course will proceed as planned. Your instructor will inform you if there are any extenuating circumstances regarding content or activity due dates in the course due to weather delays. If you are affected by a weather-related emergency, please contact your instructor at the earliest possible time to make special arrangements.

Connect Online with Caution

Penn State is committed to educational access for all. Our students come from all walks of life and have diverse life experiences. As with any other online community, the lack of physical interaction in an online classroom can create a false sense of anonymity and security. While one can make new friends online, digital relationships can also be misleading. Good judgment and decision making are critical when choosing to disclose personal information with others whom you do not know.

Deferred Grades

If you are prevented from completing this course within the prescribed amount of time, it is possible to have the grade deferred with the concurrence of the instructor. To seek a deferred grade, you must submit a written request (by e-mail or U.S. post) to your instructor describing the reason(s) for the request. It is up to your instructor to determine whether or not you will be permitted to receive a deferred grade. If, for any reason, the course work for the deferred grade is not complete by the assigned time, a grade of "F" will be automatically entered on your transcript.


This course will be conducted entirely online. There will be no set class meeting times, but you will be required to complete assignments with specific due dates. Many of the assignments are open for multiple days. It is your responsibility to complete the work on time, which may require you to complete the work early if you plan to travel or participate in national holidays, religious observances, or University-approved activities.

If you need to request an exception due to a personal or medical emergency, contact the instructor directly as soon as you are able. The instructor's ability to accommodate you is dependent on the earliest possible notification. Such requests will be considered on a case-by-case basis.


Please note that the specifics of this Course Syllabus can be changed at any time, and you will be responsible for abiding by any such changes. All changes will be communicated with you via e-mail, course announcement and/or course discussion forum.