About the Course :
With the advent of powerful remote sensing techniques one is able to gather errestrial information that might not have been possible earlier. Through this course, we aim to address geological problems with techniques of hyperspectral and microwave remote sensing. Participants will be given adequate knowledge of fundamental concepts and will go on to learn image processing in both hyperspectral and microwave regions of the spectrum.Hands on experience will be gained in areas of geological applications like land subsidence, earthquake, glacier dynamics, etc.
We invite you to attend this training program on Hyperspectral and Microwave Remote Sensing Techniques for Geological Studies. The course is scheduled from March 7-17, 2022
Curriculum :
Principles of Hyperspectral and Microwave Remote Sensing, Data analysis and applications
• Hyperspectral Processing techniques: Data reduction, end members selection, Mapping methods; SAR Data Processing: InSAR, DInSAR, PolSAR
• Spectroscopy of major rocks and minerals (terrestrial and planetary)
• DInSAR for Land Surface Deformation studies: Earthquake, Landslide, Land subsidence, and Glacier Dynamics studies.
Outcome :
At the end of this course, participants would be able to process and analyze spaceborne/ airborne Hyperspectral and Microwave remote sensing data for geological applications.
Fee: There is no course fee for attending this program.
Target Participants :
The candidates who want to participate in should be a postgraduate or final year postgraduate student of Geosciences . Scientific Staff of Central/State Government/Faculty/researchers at university/institutions are also eligible to apply for this course. Applications of participants have to be duly sponsored by
university/institute and forwarded through coordinators from respective centres. Users receiving programmes under CEC-UGC/ CIET networks can also participate. Institutions on high speed National Knowledge Network (NKN).
Certificate of attendance :
Working Professionals and Students: Based on 70% attendance
