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  • Remote Sensing and GIS
    by Basudeb Bhatta

Syllabus:-

Instructor

Jarlath O’Neil-Dunne

John A. Dutton e-Education Institute
Pennsylvania State University

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 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.

Prerequisites:

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

Overview:

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(link is external).
  • 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.

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