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Remote Sensing: Principles and Applications

Remote Sensing: Principles and Applications banner
Preview this course
Self-paced Advanced

Remote Sensing: Principles and Applications

3(115)
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FREE
873 min
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English
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Why enroll

This course is highly valuable for civil engineers, environmental engineers, planners, and geoscience professionals seeking to use spatial data for analysis and decision-making. It builds essential skills in satellite data interpretation and geospatial analysis, which are increasingly important in infrastructure planning, environmental monitoring, and disaster risk assessment. The course also provides a strong foundation for advanced studies in GIS, digital image processing, and geospatial technologies.

Is this course for you?

You should take this if

  • You work in Oil & Gas Upstream or Rail & Transport
  • You're a Civil & Structural professional
  • You have 3+ years of hands-on experience in this field
  • You prefer self-paced learning you can revisit

You should skip if

  • You're new to this field with no prior experience
  • You need a different specialisation outside Civil & Structural
  • You need live interaction with an instructor

Course details

The Remote Sensing: Principles and Applications course provides a comprehensive understanding of how information about the Earth’s surface and atmosphere is collected, processed, and interpreted using satellite and airborne sensors. The course explains the physical principles behind remote sensing, including electromagnetic radiation, interaction of energy with matter, and sensor technologies used to acquire spatial data.

The course covers different remote sensing platforms, sensor types, and data acquisition systems, along with digital image processing techniques for extracting meaningful information. Emphasis is placed on practical applications of remote sensing in civil engineering, environmental studies, urban planning, disaster management, water resources, agriculture, and geology. By the end of the course, learners gain the ability to interpret satellite imagery, analyze spatial patterns, and apply remote sensing data to solve real-world engineering and environmental problems.

SOURCE- youtube [NPTEL IIT Bombay]

Course suitable for

Key topics covered

  1. Fundamentals of remote sensing and electromagnetic spectrum

  2. Interaction of radiation with Earth materials

  3. Remote sensing platforms and sensor systems

  4. Types of satellite imagery and resolutions

  5. Image enhancement and digital image processing

  6. Visual and digital interpretation of satellite images

  7. Applications in land use and land cover mapping

  8. Remote sensing in water resources and agriculture

  9. Disaster management and hazard mapping

  10. Urban planning and environmental monitoring

  11. Integration of remote sensing with GIS

Course content

The course is readily available, allowing learners to start and complete it at their own pace.

30 lectures14 hr 33 min
  1. Lecture 1: Introduction to RS and EMR
    19 min
  2. Lecture 2: Introduction to EMR
    25 min
  3. Lecture 3: Basic Laws of RS
    23 min
  4. Lecture 4: Properties of EMR – Part 1
    27 min
  5. Lecture 5: Properties of EMR – Part 2
    21 min
  6. Lecture 6: Interaction of EMR with atmosphere
    28 min
  7. Lecture 7: Radiometry – Part 1
    34 min
  8. Lecture 8: Radiometry – Part 2
    32 min
  9. Lecture 9: Radiometry – Part 3
    32 min
  10. Lecture 10: Reflectance, albedo and related quantities
    26 min
  11. Lecture 11: Interaction of EMR with terrain features – Part 1
    29 min
  12. Lecture 12: Interaction of EMR with terrain features – Part 2
    20 min
  13. Lecture 13: Radiation reaching sensor – Part 1
    29 min
  14. Lecture 14: Radiation reaching sensor – Part 2
    28 min
  15. Lecture 15: RS data: From Radiance to reflectance – Part 1
    33 min
  16. Lecture 16: RS data: From Radiance to reflectance – Part 2
    28 min
  17. Lecture 17: RS data: From Radiance to reflectance – Part 3
    33 min
  18. Lecture 18: RS image acquisition and RS systems – Part 1
    20 min
  19. Lecture 19: RS image acquisition and RS systems – Part 2
    33 min
  20. Lecture 20: RS image acquisition and RS systems – Part 3
    26 min
  21. Lecture 21: RS image acquisition and RS systems – Part 4
    36 min
  22. Lecture 22: RS image acquisition and RS systems – Part 5
    24 min
  23. Lecture 23: RS image acquisition and RS systems – Part 6
    39 min
  24. Lecture 24: RS image acquisition and RS systems – Part 7
    36 min
  25. Lecture 25: RS image acquisition and RS systems – Part 8
    36 min
  26. Lecture 26: RS image acquisition and RS systems – Part 9
    34 min
  27. Lecture 27: Spectral Properties of few common earth features in the Visible, NIR and SWIR bands- 1
    33 min
  28. Lecture 28: Spectral Properties of few common earth features in the Visible, NIR and SWIR bands– 2
    30 min
  29. Lecture 29: Spectral Properties of few common earth features in the Visible, NIR and SWIR bands– P 3
    31 min
  30. Lecture 30: Spectral Properties of few common earth features in the Visible, NIR and SWIR bands– P 4
    28 min

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Questions and Answers

A: Fused silica with a proper AR coating manages UV-induced solarization and shows negligible interaction with chlorides, which is what drives long-term transmission loss here. BK7 feels reasonable because it's common in optics, but alkali content makes it drift under UV and humidity. Sapphire's hardness is attractive, yet uncoated sapphire reflects heavily and doesn't address surface chemistry with salts. Polycarbonate works in housings, not precision optics; UV stabilizers slow yellowing but don't stop it over multi-year exposure.

A: The linear model here is radiance = gain×DN + offset, giving 0.015×820 + 1.2 = 13.5. Option B mirrors a calibration style used in some lab spectrometers, but the datasheet defines offset as additive. Option C imports a correction from another band; dark current handling is already embedded in the offset. Option D ignores units, a mistake that slips in when people jump between radiometric and image-processing conventions.

A: A formal MOC captures the conflict and forces reconciliation, which is what auditors expect when controlled documents disagree. Trusting the datasheet alone is tempting, but revision control isn't proven. Treating the GA as authoritative ignores that the instrument list drives software and telemetry. Option D splits hardware and processing logic, creating a latent integration fault that only shows up during end-to-end testing.

A: Frame definitions and time tags are common sources of small angular differences; clearing that avoids unnecessary mechanical work. GNSS dominance in position doesn't guarantee azimuth accuracy at this resolution, so B jumps the gun. Averaging hides a real inconsistency and won't satisfy a witness. Disabling an instrument to pass acceptance raises bigger questions during inspection.