GEOG 883
Remote Sensing Image Analysis and Applications

GEOG 883 Syllabus


Remote Sensing Image Analysis and Applications - Summer, 2024

Remote Sensing Image Analysis and Applications - Summer, 2024

This syllabus is divided into several sections. You can read it sequentially by scrolling down the length of the document. It is essential that you read the entire document as well as the material covered in the Orientation. Together, these serve the role of our course "contract."


J.B. Sharma, Ph.D.

John A. Dutton e-Education Institute
The Pennsylvania State University
2217 Earth and Engineering Sciences Building
University Park, PA 16802-6813

Course Overview

GEOG 883: Remote Sensing Image Analysis and Applications

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 an 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. Strong working knowledge of desktop geospatial software (e.g. ArcGIS) is expected of students who register for this course.

Students who do not meet these prerequisites may be disenrolled according to Administrative Policy C-5 if you do not have the proper prerequisite override. If you have not completed the listed prerequisites, then promptly consult with the instructor if you have not done so already. Students who re-enroll after being disenrolled, according to this policy, are in violation of the Student Code of Conduct.


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 and eight 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 defining 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, recorded lectures, video demonstrations, and links to external materials that may assist you. Quizzes in each lesson to test your comprehension of the reading 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. You will submit your lab work as a written report via Canvas. You are encouraged to ask questions and post comments at any time in the Discussion Forums provided for each lesson. Email 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 email 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 email 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., et al. (2023). Introduction to Remote Sensing, 6th edition. New York. The Guilford Press. ISBN 978-1462549405. 
E-book Option: An online version of the Campbell text is available at no cost as a Penn State Library E-book. Some E-books will be available online, while others will be available to download in full or in part. You may choose to use the E-book as an alternative to purchasing a physical copy of the text. You may access it by selecting the Library Resources link in the course navigation and then selecting the E-Reserves link, or by using this link: Introduction to Remote Sensing, 6th edition. For questions or issues, you can contact the University Libraries Reserve Help (UL-RESERVESHELP@LISTS.PSU.EDU).

Parece, Tammy, McGee, John, Campbell, Jim (2019). Remote Sensing with ArcGIS Pro. (Workbook). Virginia Tech. ISBN: 1797570986.

Optional Textbooks

Green, Congalton, and Tukman (2017). Imagery and GIS: Best Practices for Extracting Information from Imagery, Illustrated Edition.


Penn State honors and values the socioeconomic diversity of our students. If you require assistance with the costs of textbooks for this course, please contact your academic advisor. For additional needs, related to socioeconomic status, please visit Project Cahir or visit the Office of Student Care and Advocacy at 220 Boucke Building or call 814-863-2020.

Supplemental References (No Purchase Necessary)

Additional readings may be provided electronically through the course management system and Penn State library services.

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 Pro, Esri
    All students in the Online Geospatial Program have access to ArcGIS Pro through the Penn State Enterprise license. Instructions for installing ArcGIS Pro will be provided in Canvas.
  2. ArcGIS Online, Esri
    All students in the Online Geospatial Program have access to ArcGIS Online through the Penn State Enterprise license. Instructions for accessing ArcGIS Online will be provided in Canvas.
  3. ​​​​​​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.
  4. Google Earth Engine
    Instructions for obtaining access to Google Earth Engine will be provided in Canvas. Students are required to have a personal Google account.
  5. 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 7-Zip.
  6. Screen Capture Utility
    SnagIt (paid), Screenpresso (free), or use the built-in Windows Snipping Tool. You will need a file utility capable of unzipping .zip and .tar.gz files. 7-Zip can be downloaded for free from 7-Zip.

Using Penn State Library Resources

Just like on-campus students, as a Penn State student, you have a wealth of library resources available to you!

As a user of Penn State Libraries, you can...

  • search for journal articles (many are even immediately available in full-text)
  • request articles that aren't available in full-text and have them delivered electronically
  • borrow books and other materials and have them delivered to your doorstep
  • access materials that your instructor has put on Electronic Reserve
  • talk to reference librarians in real-time using chat, phone, and email
  • ...and much more!

To learn more about their services, see the Library Information for Off-site Users.

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 (12% of final grade)
  • Online discussions (6% of final grade)
  • Lab activities (56% of final grade)
  • Final project (26% of final grade)

Assignment Late Penalty Policy:

All the course assignments are expected to be turned in on the due date. It is important that all students move through the course as a group in order to maximize the class interaction and facilitate learning. Late assignments accrue a late penalty of 5% of the grade per day. In the instances where an assignment is going to be late due to an extenuating circumstance, please inform the instructor of the reason why the assignment is late and when the student intends to submit it. If the student adheres to their assignment submission plan, no late penalty will be charged for that case.

The final grading scale is shown below.

Letter Grade Percentages Points
Letter grades and percentages
A 93% and above 563 points and above
A- 90% - 92.9% 545 - 562 points
B+ 88% - 89.9% 532 - 544 points
B 83% - 87.9% 502 - 532 points
B- 80% - 82.9% 484 - 502 points
C+ 78% - 79.9% 472 - 483 points
C 70% - 77.9% 424 - 471 points
D 60% - 69.9% 363 - 405 points
F 59.9% and below 362 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
  • 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 accommodations for disabilities.
  • Communicate effectively with instructors and fellow students using a variety of online tools.
  • Online Orientation Material
  1. Orientation Survey
  2. Personal Introduction
  3. Lesson 0 Lab Activities
Lesson 1: Working with Remotely Sensed Data
Date Week 1
  • Describe the basic principles of remote sensing.
  • Explain the remote sensing workflow.
  • Select remotely sensed data and analyze by applying an appropriate remote sensing workflow.

Campbell, James B., et al. (2023). Introduction to Remote Sensing, 6th edition.

  • Chapter 1. History and Scope of Remote Sensing
  • Chapter 2. Electromagnetic Radiation
  • Chapter 7. Land Observation Satellites

Parece et al. (2019) Remote Sensing with ArcGIS Pro

  • Chapter 1. Opening an Existing Project/Creating a New Project
  • Chapter 2. Using ArcGIS Pro to Open a Map Created in ArcGIS Desktop
  • Chapter 3. Repairing a Broken Data Link
  • Chapter 4. Connecting to a Folder or an Online GIS Server
  • Chapter 5. Adding Shapefiles to a Project’s Geodatabase
  • Chapter 6. Adding Data to a Project
  • Chapter 7. Displaying Data
  • Chapter 8. Metadata
  • Chapter 9. Saving and Exporting Maps
  1. Lesson 1 Reading Quiz
  2. Lesson 1 Lab Activity
  3. Lesson 1 Graded Discussion
Lesson 2: Preprocessing of Remotely Sensed Data
Date Week 2
  • apply radiometric preprocessing techniques to image data
  • 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 point cloud data

Campbell, James B., et al. (2023). Introduction to Remote Sensing, 6th edition.

  • Chapter 5. Digital Imagery
  • Chapter 9. Lidar
  • Chapter 11. Preprocessing

Parece et al. (2019) Remote Sensing with ArcGIS Pro

  • Chapter 11. Downloading Landsat 8 Imagery using EarthExplorer
  • Chapter 12: Information about the Downloaded Landsat 8 Imagery Chapter 13. Displaying Landsat 8 Imagery in ArcGIS Pro
  • Chapter 14: Creating a Composite Image for Landsat 8 Imagery Chapter 15. Sub-setting a Landsat 8 Composite Image
  • Chapter 16. Band Combinations for Landsat 8 Imagery
  • Chapter 17. Radiometric Enhancement of Landsat 8 Imagery
  • Chapter 18. Spatial Enhancement of Landsat Imagery
  • Chapter 19. Spectral Enhancement of Landsat 8 Imagery
  1. Lesson 2 Reading Quiz
  2. Lesson 2 Lab Activity
  3. Lesson 2 Graded Discussion
Lesson 3: Emergent Earth Observation Sensors, Platforms, and Analytics
Date Week 3
  • identify a wide variety of emergent remote sensing platforms and satellite constellations
  • utilize cloud computing platforms for remote sensing data access and analysis
  • explain the fundamental principles of hyperspectral remote sensing
  • explain the fundamental principles of radar imaging, including SAR and IfSAR
  • explain the fundamental principles of thermal remote sensing
  • identify and distinguish between geospatial products produced from multispectral, hyperspectral, radar and thermal remote sensing systems

Campbell, James B., et al. (2023). Introduction to Remote Sensing, 6th edition.

  • Chapter 8.    Active Microwave
  • Chapter 10.    Thermal Imagery
  • Chapter 14.  Hyperspectral Remote Sensing

Maune and Nayegandhi (2018) Digital Elevation Model Technologies and Applications: The DEM Users Manual. 3rd Edition.

  • Chapter 2.    Vertical Datums
  • Chapter 5.    Object Space Coordinate Systems

Wolf, et al. (2014) Elements of Photogrammetry with Applications in GIS. 4th Edition

  • Chapter 5.    Object Space Coordinate Systems

Other Articles and Web Pages as assigned

  1. Lesson 3 Reading Quiz
  2. Lesson 3 Lab Activity
  3. Lesson 3 Graded Discussion
Lesson 4: Pixel and Object-Based Image Classification
Date Week 4
  • define the eight classic elements of image interpretation
  • explain the seven categories of tasks commonly performed with image interpretation
  • apply the elements of image interpretation to data collected from a variety of sensors
  • construct an image interpretation key
  • perform object-based supervised classification using ArcGIS Pro
  • apply segmentation algorithms to remotely sensing imagery in eCognition

Campbell, James B., et al. (2023). Introduction to Remote Sensing, 6th edition.

  • Chapter 6. Image Interpretation
  • Chapter 8. Active Microwave (continued from Lesson 3)
  • Chapter 10. Thermal Imagery

Other Articles and Web Pages as assigned

  1. Lesson 4 Reading Quiz
  2. Lesson 4 Lab Activity
  3. Lesson 4 Graded Discussion
  4. Post Final Project Idea
Lesson 5: Rule-Based Geographic Object-Based Image Analysis (GEOBIA) Classification
Date Week 5
  • explain pixel and object-based approaches to feature extraction
  • explain supervised and unsupervised approaches to feature extraction
  • execute a classification using spectral information
  • execute a classification using geometric information
  • execute a classification using texture information
  • execute 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, James B., et al. (2023). Introduction to Remote Sensing, 6th edition.

  • Chapter 6. Image Interpretation (continued from Lesson 4)
  • Chapter 12. Image Classification
  • Chapter 13. Accuracy Assessment
  1. Lesson 5 Reading Quiz
  2. Lesson 5 Lab Activity
  3. Lesson 5 Graded Discussion
  4. Post Final Project Idea Peer Reviews
Lesson 6: Change Detection
Date Week 6
  • develop rulesets in eCognition for automated feature extraction
  • create a thematic map using lidar and multispectral imagery
  • detect thematic change over time using two dates of multispectral imagery
  • quantify land cover change over time using object-based techniques
  • assess the utility of object-based classification approaches for change detection


Campbell, James B., et al. (2023). Introduction to Remote Sensing, 6th edition.

  • Chapter 6. Image Interpretation (continued from Lesson 5)
  • Chapter 15. Change Detection
  • Chapter 21. Land Use and Land Cover
  1. Lesson 6 Reading Quiz
  2. Lesson 6 Lab Activity
  3. Lesson 6 Graded Discussion
Lesson 7: Machine Learning and Classification of Remotely Sensed Data
Date Week 7
  • explain how Artificial Intelligence (AI), Machine Learning, and Deep Learning are utilized in the classification of remotely sensed data
  • develop expert system rulesets for land cover classification and change detection
  • perform OBIA classification of multispectral and nDSM daa acquired from UAS platform
  • summarize specific issues involved with the use of very high spatial resolution multispectral data acquired with UAS
  1. Lesson 7 Lab Activity
  2. Post Final Project Proposal
Lesson 8: Thematic Map Accuracy Assessment
Date Week 8
  • Discuss the principles of classification accuracy assessment
  • Explain the difference between errors of omission and errors of commission
  • Explain the difference between users accuracy and producer's accuracy
  • Construct an accuracy assessment error matrix
  • Apply the principles of classification accuracy assessment in a typical geospatial analysis

Campbell, James B., et al. (2023). Introduction to Remote Sensing, 6th edition.

  • Chapter 14. Accuracy Assessment (continued from Lesson 5)

  1. Lesson 8 Lab Activity
  2. Post Final Project Proposal Peer Reviews
Final Project: Remote Sensing Data Analytics: Addressing Contemporary Socio-Economic, Environmental, Urban, and Security Issues
Date Week 9-10 

The final project will challenge students to apply knowledge and skills acquired in the earlier lessons in a realistic problem scenario that requires the acquisition and analysis of remote sensing data. Project activities will span the entire course period. 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 the results of their study.

Readings/activities None
  • Final Project Idea Post (Week 4)
  • Final Project Idea Peer Reviews (Week 5)
  • Final Project Proposal Post (Week 7)
  • Final Project Proposal Peer Reviews (Week 8)
  • Final Project Presentation (Week 10)
  • Final Project Report (Week 10)

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 the World Campus Technical Requirements page, including the requirements listed for same-time, synchronous communications. If you need technical assistance at any point during the course, please contact the IT Service Desk.

Internet Connection

Access to a reliable 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 Wi-Fi ® hotspot.


This course must be viewed using the latest version of Firefox, Safari, Chrome, or Edge. Internet Explorer is not supported. If you use any other browser, or if you are not using the latest version of your browser, some pages containing equations may not render properly. In addition, javascript must be enabled for equations to render properly. If you have any issues with equations not rendering properly, please update your browser to the latest version or try using a different browser. If you need additional technical assistance at any point during the course, please contact the 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 Penn State 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

Academic integrity is the pursuit of scholarly activity in an open, honest, and responsible manner. Academic integrity is a basic guiding principle for all academic activity at Pennsylvania State University, and all members of the University community are expected to act in accordance with this principle. 

According to Penn State policy  G-9: Academic Integrity, an academic integrity violation is “an intentional, unintentional, or attempted violation of course or assessment policies to gain an academic advantage or to advantage or disadvantage another student academically.” Unless your instructor tells you otherwise, you must complete all course work entirely on your own, using only sources that have been permitted by your instructor, and you may not assist other students with papers, quizzes, exams, or other assessments. If your instructor allows you to use ideas, images, or word phrases created by another person (e.g., from Course Hero or Chegg) or by generative technology, such as ChatGPT, you must identify their source. You may not submit false or fabricated information, use the same academic work for credit in multiple courses, or share instructional content. Students with questions about academic integrity should ask their instructor before submitting work.

Students facing allegations of academic misconduct may not drop/withdraw from the affected course unless they are cleared of wrongdoing (see G-9: Academic Integrity). Attempted drops will be prevented or reversed, and students will be expected to complete coursework and meet course deadlines. Students who are found responsible for academic integrity violations face academic outcomes, that can be severe, and put themselves at jeopardy for other outcomes which may include ineligibility for the Dean's List, pass/fail elections, and grade forgiveness. Students may also face consequences from their home/major program and/or The Schreyer Honors College.

Please also see Earth and Mineral Sciences Academic Integrity Procedures, which this course adopts. To learn more, see Penn State’s “Academic Integrity Training 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 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. For example, uploading completed labs, homework, or other assignments to any study site constitutes a violation of this policy.

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 the contact information for every Penn State campus. For further information, please visit the Student Disability Resources website.

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. See Student Disability Resources: Applying for Services. 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.

Change in Normal Campus Operations

In case of weather-related delays or other emergency campus disruptions or closures 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 these delays or closures. If you are affected by a weather-related emergency, please contact your instructor at the earliest possible time to make special arrangements.

Reporting Educational Equity Concerns

Penn State takes great pride in fostering a diverse and inclusive environment for students, faculty, and staff. Acts of intolerance, discrimination, or harassment due to age, ancestry, color, disability, gender, gender identity, national origin, race, religious belief, sexual orientation, or veteran status are not tolerated (Policy AD29 Statement on Intolerance) and can be reported through Educational Equity via Report Bias.

Counseling and Psychological Services

Many students at Penn State face personal challenges or have psychological needs that may interfere with their academic progress, social development, or emotional wellbeing.  The university offers a variety of confidential services to help you through difficult times, including individual and group counseling, crisis intervention, consultations, online chats, and mental health screenings.  These services are provided by staff who welcome all students and embrace a philosophy respectful of clients’ cultural and religious backgrounds, and sensitive to differences in race, ability, gender identity, and sexual orientation.  Services include the following: 

Counseling and Psychological Services at University Park  (CAPS): 814-863-0395
Counseling Services at Commonwealth Campuses
Penn State Crisis Line (24 hours/7 days/week): 877-229-6400
Crisis Text Line (24 hours/7 days/week): Text LIONS to 741741

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.

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 for reasons that are beyond your control, it is possible to have the grade deferred with the concurrence of the instructor, following Penn State Deferred Grade Policy 48-40. To seek a deferred grade, you must submit a written request (by e-mail or U.S. post) to the instructor describing the reason(s) for the request. Non-emergency permission for filing a deferred grade must be requested before the beginning of the final examination period.  It is up to the instructor to determine whether or not you will be permitted to receive a deferred grade. If permission is granted, you will work with the instructor to establish a communication plan and a clear schedule for completion within policy.  If, for any reason, the coursework 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 weekly assignments with specific due dates. Many of the assignments are open for multiple days, so it is your responsibility 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. Such requests will be considered on a case-by-case basis.

In EMS, inclusivity is one of our core values. We prioritize fostering a diverse and equitable community where each member knows they belong here and is inspired to succeed. We encourage everyone in our EMS community to be actively engaged in fostering this ideal, and all members of this class should contribute to a respectful, welcoming, and inclusive environment and interact with civility. Our commitment to inclusivity aligns with Penn State’s values and policies. 

To learn more, visit EMS Educational Equity.  Here, you will find information about the EMS ALLWE initiative, the Rainbow EMS Network, Anti-Racism, active ally-ship, bystander intervention, and more. The site also has resources for where to turn if you need assistance and links to University references.  Also, contact your EMS department’s Associate Head for DEI for more information about department initiatives. 

Mandated Reporting Statement

Penn State’s policies require me, as a faculty member, to share information about incidents of sex-based discrimination and harassment (discrimination, harassment, sexual harassment, sexual misconduct, dating violence, domestic violence, stalking, and retaliation) with Penn State’s Title IX coordinator or deputy coordinators, regardless of whether the incidents are stated to me in person or shared by students as part of their coursework. For more information regarding the University's policies and procedures for responding to reports of sexual or gender-based harassment or misconduct, please visit Penn State's Office of Sexual Misconduct Prevention & Response website.

Additionally, I am required to make a report on any reasonable suspicion of child abuse in accordance with the Pennsylvania Child Protective Services Law.


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. Changes to the syllabus shall be given to you in written (paper or electronic) form.