Remote Sensing - Course Outline

Course Description

Remote Sensing is the art and science of characterizing the Earth without touching it. Students will learn about this important, interdisciplinary, technical, computer-based, cutting-edge and growing branch of the Earth Sciences. Students will become familiar with the process of developing a remote sensing product from raw data both through a theoretical understanding of the characteristics of remotely-sensed imagery and direct experience with hands-on exercises using specialized software.

Course learning objectives

By the end of the course, students will be able to:

  • Briefly describe the past history and future potential of Remote Sensing.
  • Describe the remote sensing process and its four main procedures.
  • Understand the concept of electromagnetic radiation and its link with remote sensing measurements.
  • Understand the fundamentals of analog aerial photographs: acquisition, scale, photogrammetric corrections, measurements and interpretation.
  • Define the four characteristics of remotely sensed digital images, their interconnection and trade-offs: spatial, radiometric, spectral and temporal resolutions.
  • Classify remotely-sensed data according energy source, platform, wavelength and resolution.
  • Identify some of the most important satellites in orbit for Earth Monitoring and rank them accorging to their specifications.
  • Understand how pixel digital numbers can be transformed into known variables, indices or land cover category.
  • Perform basic procedures of digital image pre-processing using specialized software.
  • Define and perform unsupervised and supervised image classification using IDRISI software.
  • Understand the basics of lidar and radar.

Required text

All knowledge needed is provided or available to linked resources on the internet.


Student evaluation in the course will be based on participation in lecture tutorials, completed laboratory assignments, a final exam, and a self-evaluation of student achievement. The final exam will cover all material from lectures. The final weighting of coursework is as follows:

  • 40% Lab assignments
  • 30% Lecture tutorials
  • 30% Final exam