ADVANCED PRINCIPLES OF REMOTE SENSING (THEORY)

Paper Code: 
25RES331
Credits: 
04
Contact Hours: 
60.00
Max. Marks: 
100.00
Objective: 
To introduce the student to the physical Advanced Satellite of Remote Sensing, Hyperspectral Remote Sensing, LIDAR Remote Sensing and their different application in terrestrial and vegetation mapping. Acquire skills in handling instruments, tools, techniques and modelling while using Remote Sensing Technology.
Course Outcomes: 

Course Code

Course Title

Course Learning Outcomes

Learning & Teaching Strategies

Assessment Strategies

25RES331

Advanced Principles of Remote Sensing (Theory)

CO31: Apply radiation physics (Planck's, Stefan-Boltzmann, Kirchoff's laws)
CO32: Evaluate IRS sensor systems
CO33: Analyze image interpretation fundamentals
CO34: Implement digital image processing
CO35: Perform image classification
CO36: Contribute effectively in course interaction

Teaching Methods:
• Interactive lectures
• Technical discussions
• Sensor demonstrations
• Digital image processing labs
• Mini video lessons
• Summative/formative workshops

Student Activities:
• Physics law applications
• Sensor analysis exercises
• Image classification projects
• Seminar presentations

• Theory tests (radiation laws)
• Sensor evaluation quizzes
• Image processing assignments
• Classification projects
• Semester examinations
• Group research presentations

 

 

12.00
Unit I: 
• Physics of Remote Sensing- Electromagnetic Radiation and its Quantities- Radiant Energy-
Radiant Flux- Irradiance- Exultance- Solid angle Unit- Radiant intensity,
• Radiance Spectral Quantities- Radiation laws- Plancks,
• Stefans- Boltezman and Kirchoffs Laws.
12.00
Unit II: 

• Whisk Broom and Push Broom- sensors used in IRS- Landsat- spot satellite, 

• Resolution: spatial, spectral, temporal and radiometric.

12.00
Unit III: 
• Fundamental of Image interpretation:
• Image interpretation key.
12.00
Unit IV: 
• Digital Image Processing:
• pre-possessing, geometric and radiometric corrections,
• contrast starching, principle component and analysis and filtering.
12.00
Unit V: 
• Image Classification:
• Supervised and unsupervised. Accuracy assessment.
Essential Readings: 
• Cracknell, A and Hayes, L. (1990): Remote Sensing Year Book, Taylor and Francis, London. 
• Curran Campbell, J. B. (2002): Introduction to Remote Sensing. 5th edition. Taylor and Francis,
London.
• Cracknell, P.J. (1985): Principles of Remote Sensing, Longman, London. 
• Deekshatulu, B.L. and Rajan, Y.S. (ed.) (1984): Remote Sensing. Indian Academy of Science,
Bangalore.
• Floyd, F. and Sabins, Jr. (1986): Remote Sensing: Principles and Interpretation,W.H.Freeman, New
York.
 
Suggested Reading:
• Guham, P. K. (2003): Remote Sensing for Beginners. Affiliated East-West Press Private Ltd., New
Delhi.
• Lillesand, T.M. and Kiefer, R.W. (2000): Remote Sensing and Image Interpretation. 4th edition. 
• Hallert, B. (1960): Photogrammetry, McGraw Hill Book Company Inc., New York. 
References: 
e- Resources
1. Journal of the Indian Society of Remote Sensing – Annual, Springer and Indian Society of Remote
Sensing, Dehradun 0255-660X
2. Applied Geography- Quarterly, Elsevier, Netherlands 0143-6228
Academic Year: 
2025-2026