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Introduction to remote sensing & Digital Image Processing

This course provides an introduction to satellite remote sensing principles, on-board sensor data, and image processing functions and tools. Students will learn to process satellite data using off-the-shelf software packages and conduct remote sensing-based projects.

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Introduction to remote sensing & Digital Image Processing

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  1. Introduction to remote sensing & Digital Image Processing Rao Zahid Khalil Contact: Zahidkhalil.rao@gmail.com Zahid.Khalil@mail.ist.edu.pk RG610 Course: Introduction to RS & DIP

  2. Outlines • Zero Semester Courses • Introduction to RS & DIP • Objectives • Learning Outcomes • Skills Outcomes • Course Assessment • Course Syllabus • Reference Books

  3. Zero Semester Courses

  4. Introduction to RS & DIP

  5. Objectives • The objectives of the course are: • To provide basic concepts and principles of satellite remote sensing and its applications • To give understanding on various on-board sensor data and their applications • To give conceptual understanding of different image processing functions and tools and tasks

  6. Learning Outcomes • An understanding on remote sensing principles, satellites and their orbits, data acquisition, onboard sensors and their characteristics. • Knowledge of various data processing techniques for different applications. • An understanding of analysis and interpretation of remote sensing data.

  7. Skills Outcomes • By taking this course the students will be: • Able to process satellite data and apply different Digital Image Processing (DIP) algorithms for different tasks using off the shelf software packages. • Able to conceive and conduct a remote sensing based study/project. • Able to select and use appropriate remote sensing datasets for different applications

  8. Course Schedule • Day: • Every Tuesday • Time: 5:00 PM – 9:00 PM • Office Hours • Check my availability and drop-in

  9. Course Syllabus (RG610) • Fundamentals of Remote Sensing • History of remote sensing • Electromagnetic radiation • Interaction of EM with the atmosphere • Spectral response at various targets • Radiometric and geometric Errors

  10. Course Syllabus (RG610) • Sensors • Types of Sensors • Characteristics of optical sensors • Resolution • Remote Sensing Satellite Systems • Earth imaging by satellite • Data parameters • Low Resolution Satellite - NOAA, Aqua, Terra, Meteosat • Medium Resolution satellites - Landsat, SPOT, ASTER • High Resolution Satellites - IKONOS, QuickBird, etc.

  11. Course Syllabus (RG610) • Image Rectification and Restoration • Datum, Projection and Coordinate System • Geometric Correction • Data Mosaicing • Image Interpretation • Introduction • Interpretation elements

  12. Course Syllabus (RG610) • Image Enhancements • Introduction to digital image processing (DIP) • Perception of colors • Visualization of image data • Colour composites • Filter operations (noise removal, edgeenhancement) • Contrast Manipulation • Multi-Image Manipulation (Spectral ratioing and differencing, Density slicing, NDVI, HSI)

  13. Course Syllabus (RG610) • Image Classification • Principles of image classification • Unsupervised Classification • Supervised Classification • Remote Sensing data applications • Landuse/landcover • Urban planning • Geology/geomorphology • Hydrology/water resources • Thermal infrared data applications

  14. Reference Material • Remote Sensing and Satellite Image Interpretation byThomas M. Lillesand • Remote Sensing – Principles and Interpretation byFloyd F. Sabins • Introduction to Remote Sensing 5th Edition byJames B. Campbell • Introductory Digital Image Processing byJohn R. Jensen

  15. Reference Material • Reading material and other reference material will be provided time to time • Keep connect with https://istncrg.wordpress.com/

  16. Homework/Quiz/Exams • Homework: Students will be required to do homework and submit on the date mentioned on homework • Workshop Assignments: Each student will be assigned an exercise after each lab topic covered • Quiz: Several in class Quiz (both surprise and informed) • OHT: Two in class OHT (approximately 1/3 of the course coverage) • Lab Exam or Project Presentation: One week before Final Exam • Final Exam: Comprehensive coverage of the course during the last week of semester

  17. Marks Proportion • Assignments (~10%)                • Quiz ( ~ 10%) • Projects or Lab Exam (~10 %)    • OHT (~ 30%)                • Final Term Exam (~ 40%)

  18. Good Luck

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