RS4101 - Remote Sensing (Syllabus) 2021-regulation Anna University

RS4101 - Remote Sensing (Syllabus) 2021-regulation Anna University

RS4101	REMOTE SENSING	LTPC

3003

OBJECTIVES:

• To familiarize about the basic principles of remote sensing
• To acquire knowledge about the motion of remote sensing satellites in the space
• To expose the various types of sensors used for remote sensing
• To gain knowledge about the generation of satellite data products
• To extract useful information from satellite images

UNIT I	PHYSICS OF REMOTE SENSING	9

Remote Sensing - Defintion - Components - Electro Magnetic Spectrum – Basic wave theory – Particle theory – Stefan Boltzman law - Wiens-Displacement Law - Radiometric quantities - Effects of Atmosphere- Scattering – Different types –Absorption-Atmospheric window- Energy interaction with surface features – Spectral reflectance of vegetation, soil and water –atmospheric influence on spectral response patterns- multi concept in Remote sensing -

UNIT II	PLATFORMS	9

Orbit elements – Types of orbits – Motions of planets and satellites – Launch of space vehicle – Orbit perturbations and maneuvers – escape velocity - Types and characteristics of different remote sensing platforms – sun synchronous and geo synchronous satellites.

UNIT III	SENSORS	9

Classification of remote sensors – selection of sensor parameters - resolution concept - Spectral, Radiometric and temporal resolution – Quality of images – imaging mode – photographic camera – opto-mechanical scanners – pushbroom and whiskbroom cameras – Panchromatic, multi spectral , thermal,hyperspectral scanners and microwave sensors – geometric characteristics of scanner imagery – Operational Earth resource satellites - Landsat, SPOT, IRS, WorldView, hyperion and hysis, ERS, ENVISAT,Sentinel.

UNIT IV	DATA RECEPTION AND DATA PRODUCTS	9

Ground segment organization – Data product generation – sources of errors in received data – referencing scheme – data product output medium – Digital products – Super structure, Fast,GeoTIFF, Hierarchical and HDF formats – Indian and International Satellite Data Products – ordering of data

UNIT V	DATA ANALYSIS	9

Data products and their characteristics – Elements of visual interpretation – interpretation keys – Digital image processing – Preprocessing – Image rectification – Image enhancement techniques– Image classification – Supervised and unsupervised classification algorithms for multispectral and hyperspectral images – Accuracy assessment.- hybrid classification techniques – Knowledge based classification, Neural Network Classification, Fuzzy Classification.

TOTAL : 45 PERIODS

OUTCOMES: On completion of the course, the student is expected to be able to

CO1 understand the concepts and laws related to remote sensing
CO2 acquire knowledge about various remote sensing platforms
CO3 understand the characteristics of different types of remote sensors
CO4 gain knowledge about reception, product generation, storage and ordering of satellite data
CO5 understand the concept of different image processing techniques and interpretation of satellite data

REFERENCES:

1. Lillesand T.M., and Kiefer,R.W. Remote Sensing and Image interpretation, VI edition of John Wiley & Sons-2015.
2. John R. Jensen, Introductory Digital Image Processing: A Remote Sensing Perspective, 4th Edition, 2015.
3. John A.Richards, Springer – Verlag, Remate Sensing Digital Image Analysis 5th edition, 2013.
4. Paul Curran P.J. Principles of Remote Sensing, ELBS; 1985.
5. George Joseph, Fundamentals of Remote Sensing, Third Edition, Universities Press (India) Pvt Ltd, Hyderabad, 2018