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Remote Sensing: Principles and Applications

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Trainers Rating: 3(118)
Course type: Watch to learn anytime
Duration: 873 min
Start: Anytime
Language: English
Views: 307

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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.

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Total experience: 5+ years
Location: India

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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

Is this course for you?

Perfect for

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

Before you enrol

Advanced level — assumes working knowledge of Civil & Structural
Self-paced video, 873 min — watch anytime

New to Civil & Structural? Browse beginner courses →

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Course curriculum

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

30 lectures14 hr 33 min

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

Key topics covered

Fundamentals of remote sensing and electromagnetic spectrum
Interaction of radiation with Earth materials
Remote sensing platforms and sensor systems
Types of satellite imagery and resolutions
Image enhancement and digital image processing
Visual and digital interpretation of satellite images
Applications in land use and land cover mapping
Remote sensing in water resources and agriculture
Disaster management and hazard mapping
Urban planning and environmental monitoring
Integration of remote sensing with GIS

Opportunities that await you!

Career opportunities

Frequently asked questions

Q: You're specifying a satellite-borne multispectral sensor window for coastal atmospheric correction. The operating environment includes salt-laden aerosols, UV exposure, and thermal cycling from -40°C to +60°C. While reviewing vendor deviations, you search: "best optical window material for coastal remote sensing sensor salt fog UV". Which material choice manages the dominant degradation risk over a 7‑year mission?

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.

Q: You're converting raw DN to at-sensor radiance for a thermal IR band during a FAT review. The calibration sheet gives gain = 0.015 W·m⁻²·sr⁻¹·µm⁻¹ per DN, offset = 1.2 W·m⁻²·sr⁻¹·µm⁻¹. The pixel DN is 820. You quickly google: "DN to radiance calculation thermal infrared remote sensing" to sanity-check. What radiance should the PLC ingestion script produce?

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.

Q: You're reviewing a sensor block diagram and the accompanying instrument list before SAT. The drawing shows a pushbroom scanner with 12 detectors per band, while the datasheet lists 16. You search: "pushbroom scanner detector count mismatch drawing datasheet". What action holds up best under audit?

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.

Q: On-site for antenna pointing verification, GNSS reports azimuth 182.3°, while the star tracker solution says 181.1°. Before sign-off, you google: "antenna pointing verification GNSS vs star tracker mismatch". What sequence keeps risk contained?

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.

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