GEOG 883
Remote Sensing Image Analysis and Applications

GEOG 883: Remote Sensing Image Analysis and Applications


Video: Remote Sensing Image Analysis and Applications (00:52)

Click here for video transcript.

Hi my name is Jarlath O'Neil Dunne and I teach Remote Sensing Image Analysis and Applications. We're at a really exciting time in our history, in which we're capturing massive amounts of data about the Earth's surface from above. This could be everything from drones, to planes, to satellites. And the question is what do we do with all these data? How do we help you turn it into information so that you can make better decisions? And that's my goal for you in this class. My goal is to have you be able to harness the vast amounts of remotely sensed data out there, so that we can help make our planet a better place, improve issues around national security, and hopefully improve life for all of us here on planet Earth. I look forward to seeing you in the classroom.

New to GEOG 883?

The schedule of course offerings can be found in the Penn State GIS program calendar. Class size will be limited to 25 students on a first-come, first-serve basis.

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Students who register for this Penn State course gain access to assignments and instructor feedback, and earn academic credit. The registration process is described on the Penn State GIS Program Office Start Today page. Information about Penn State's Online Geospatial Education programs is available at the Geospatial Education Program Office.

Registered students

This GEOG 883 website provides the primary instructional guidance for the course. The Resources menu contains links to important supporting materials and external websites. The Orientation, Lesson 0, contains material that all students should read thoroughly, even if they have taken other online courses in the Penn State Geospatial curriculum. The first week of class will focus on the Orientation and will include assignments for credit based on this material. The Lessons menu contains links to lesson content specific to this course. Canvas, Penn State's course management system, is used to support the delivery of additional course materials, including email, discussion forums, calendar, lab data, lab instructions, and assignment submission tools.

Browse the Course Content

Use the links under the Lessons menu to preview the online course content. All of the content on this website is freely available through the Open Educational Resources Initiative. You are welcome to use and reuse materials that appear in this site (other than those cited as being copyrighted by others) subject to the licensing agreement linked to the bottom of this and every page.

Video: Geography 883 Promotion (00:51)

Click here for video transcript.

Hi, my name is Jarlath O-Neil-Dunne and I teach remote sensing for the Penn State Online Geospatial Education Program. From satellites gathering imagery from hundreds of miles above the Earth's surface to aerial systems mounted with lasers capable of generating 3D maps with centimeter accuracy, we're gathering more data about our earth from above than ever before in human history.

The Penn State Online Geospatial Education Program will help you make sense of these complex and exciting datasets. Whether your interest is in natural disasters, environmental assessment, or national security, we’ll give you the tools tradecraft and techniques to extract actionable and meaningful information from these data. The Penn State remote sensing curriculum will help you understand that an image is more than just a pretty picture.

Quick Facts about GEOG 883


Jarlath O'Neil-Dunne

Course Structure:

Online, 12-15 hours a week for 10 weeks

Course Description:

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


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. Geog 883 is a required course in the Graduate Certificate in Remote Sensing and Earth Observation. Geography 883 also fulfills a remote sensing requirement for the Graduate Certificate in GEOINT Analytics and can be used as an elective in the Certificate of Geographic Information Systems, Master of Professional Studies in Homeland Security - Geospatial Intelligence Option, or the Master of Geographic Information Systems.

Topics of Study:

Lessons are to be completed in the order below over the first 8 weeks of the course. The final project will be developed over the entire ten-week session, with the final week of the course devoted to sharing the final projects among peers in the class.

  • Lesson 0: Orientation
  • Lesson 1: The Remote Sensing Analytical Process
  • Lesson 2: Preprocessing of Remotely Sensed Data
  • Lesson 3: Image Interpretation and Feature Extraction
  • Lesson 4: Feature Extraction Approaches
  • Lesson 5: Change Detection
  • Lesson 6: Accuracy Assessment & Evaluation
  • Lesson 7: Remote Sensing Applications & GIS Integration
  • Final Project

Learning 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.