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This particular Assignment references the syllabus chosen for the subject of Geoinformatics, for the July 2024 - January 2025 session. The code for the assignment is MGY-05 and it is often used by students who are enrolled in the MSCGI, PGDGI Degree.
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Part A
1. Write short notes on the following:
a) Application of multispectral remote sensing.
b) Microwave remote sensing data processing .
2. Discuss principles and application potential of hyperspectral remote sensing. Add a note on its data products.
3. What is LiDAR remote sensing? Explain its principles, components and data types.
Part B
4. Write short notes on the following:
a) Image-to-map rectification.
b) Principal component analysis.
c) Systematic radiometric errors and their corrections.
5. What is image statistics? Explain the univariate and multivariate image statistics in detail.
6. Give an account of various image enhancement techniques.
Part C
7. Write short notes on the following:
a) Role of AI in image classification
b) Supervised classification
c) Error matrix and its generation
8. What is change detection? Describe various types of change detection techniques.
9. Discuss the scope of R programming in raster data processing giving suitable
examples
Part A
1. Write short notes on the following:
a) Photogrammetry
b) Imaging spectroscopy
2. Describe principles of thermal remote sensing. Also discuss its application potential. Support your answer with the help of neat well labelled diagrams, wherever necessary.
3. Give an account of the active microwave remote sensing and its application potential.
Part B
4. Write short notes on the following:
a) LiDAR data products
b) UAV based remote sensing
c) Linear image enhancement techniques
5. What are radiometric errors? Give a detailed account of radiometric image corrections techniques.
6. Give an overview of various image fusion techniques.
Part C
7. Write short notes on the following:
a) Change detection techniques
b) Unsupervised classification
c) Generation of error matrix
8. What is supervised classification? Describe the various steps involved in supervised classification.
9. Discuss R programming and its uses for data exploration and image processing.
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