Remote Sensing and Image Processing

Course Overview

In this course students are going to be introduced to the basic concepts and operational skills necessary to acquire the most appropriate remote sensing data, data manipulation and analysis, and the production of interpretable output.

The application of these techniques to the forestry and environmental sciences also will be provided. The first part of the course focuses on remote sensing, including the capture and processing of satellite images, and how data from various satellite platforms are used in the forestry and life sciences. The fundamentals of electromagnetic radiation are going to be explained, as are its interactions with Earth’s surface and atmosphere. Moreover, the course goes on to examine sensor characteristics, satellite orbits and various current.

The second part will include the most important image processing techniques that needed for the forestry field. In addition, the skills of image processing are going to be used to extract meaning and interpretation from the spatial relationships of data. The course is strongly computer-based, and students will gain experience in the use of ENVI (remote sensing).

Course Objective

  • To introduce students to the fundamentals of remote sensing, and demonstrate present applications of the technology in integrated & applied sciences including environmental and health science studies;
  • To develop a basic understanding of the concepts, science and theory behind Remote Sensing including Physical, Chemical, and Engineering aspects;
  • To become familiar with ENVI software, and basic introductory technical skills in this software;
  • Gain experience in the applications of remote sensing for solving managing and controlling problems in the Forestry and environmental sciences.


Student's Obligation

Student must follow and read the lectures day by day and have to show the ability of understanding the topic through the Lab and the projects. Moreover, Students will be responsible for information covered in the assigned readings and materials covered during lectures. Students will be expected to complete the specified assignments during or outside of the designated laboratory and lecture periods as necessary.‌


Assessment Scheme

  • Students will be responsible for information covered in the assigned readings and materials covered during lectures.
  • Students will be expected to complete the specified assignments during or outside of the designated laboratory and lecture periods as necessary.
  • Exams emphasize material from the lecture component of the course, but students also will be responsible for material covered in laboratories.

The following is a summary of the assignments, and exams.









Exercise & activities









Final Exam







Student Learning Outcome

At the end of the Remote Sensing image processing course students should:

  • ......... be able to understand the concepts of remote sensing;
  • ......... be familiar with ground, air, and satellite based sensor platforms; 
  • ......... Understand and use the language of image data to a professional standard in written reports;
  • ......... be able to discuss with critical insight appropriate image processing techniques for specific purposes;
  • ......... be able to apply knowledge of image processing principles strategically to new problems;
  • ......... be able to operate PC-based visualization software effectively.


Lectures and Materials

 Lect. Description


1.      Background theory:

Lab 0: Installing and configuring ENVI

1.1  Principles of satellite remote sensing.

Lab 1: The Basics of ENVI and the Nature of Digital Images

1.2  Electromagnetic energy and remote sensing.

Lab 2:  Exploring more tools of ENVI

2.      Sensors and systems:

Lab 3: linkage two satellite imageries

2.1  Sensors and platforms.

Lab 4: Exploring Multi-Spectral Imagery

2.2  Aerial cameras and photography.

Lab 5:  Digital Image Processing I

2.3  Multispectral scanners: Whiskbroom and Pushbroom

Lab 6: Digital Image Processing II (Filter & enhancement)

3.      Pre-processing corrections:

Lab 7: Digital Image Processing III (Radiometric Correction)

3.1  Radiometric.

Lab 8: Digital Image Processing IV (Atmospheric Correction & NDVI Landsat)

3.2  Geometric correction.

Lab 8: Digital Image Processing V (Geometric Correction)

4.      Visualization and analysis:

Lab 10: Digital Image Processing VI (Image Mosaicking Using ENVI)

4.1  Image enhancement and visualization.

Lab 11: Image classifications - I

4.2  Visual image interpretation.

Lab 12: Image classifications - II

4.3  Digital image classification.

Lab 13: Vegetation coverage assessment

5.      Application:


5.1  Estimation of vegetation coverage.

Lab14: Vegetation Coverage Mapping

5.2  Crop type mapping.

Lab 15: Crop Mapping

5.3  Land cover/Land use.

Lab 16: Land cover/Land use classifications

5.4  Trees mapping

Lab 17: Tree types classifications


Reading List and References

  • Tempfli, K., Huurneman, G. C., Bakker, W. H., Janssen, L. L. F., Feringa, W. F., Gieske, A. S. M., et al. (2009). Principles of remote sensing: An introductory textbook (4th ed. Vol. 2). Enschede: ITC.
  • Liang, S. (2008). Advances in land remote sensing. New York: Springer.
  • Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2004). Remote sensing and image interpretation (5th ed.). New York: Wiley.
  • Weng, Q. (2011). Advances in environmental remote sensing: sensors, algorithms, and applications. Boca Raton: CRC Press.