MICROWAVE REMOTE SENSING IN HYDROLOGY
- Offered byNPTEL
MICROWAVE REMOTE SENSING IN HYDROLOGY at NPTEL Overview
Duration | 4 months |
Mode of learning | Online |
Official Website | Go to Website  |
Credential | Certificate |
MICROWAVE REMOTE SENSING IN HYDROLOGY at NPTEL Highlights
- Certificate will be issued after completion of course
MICROWAVE REMOTE SENSING IN HYDROLOGY at NPTEL Course details
- Demonstrate a comprehensive understanding of the principles and concepts of microwave remote sensing and its application in hydrology
- Identify and evaluate different microwave sensors used in remote sensing for hydrological applications, including passive and active sensors
- Acquire, preprocess, and analyze microwave remote sensing data for hydrological studies, considering factors such as resolution, frequency, and polarization
- Apply microwave remote sensing techniques to estimate key hydrological parameters, such as soil moisture, precipitation, snow cover, and water levels
- Microwave Remote Sensing in Hydrology explores the use of microwave technologies to monitor Earth's water systems
- This course delves into principles, sensor technologies, and data analysis, empowering students to estimate hydrological parameters, model processes, and contribute to sustainable water resource management through innovative remote sensing applications
MICROWAVE REMOTE SENSING IN HYDROLOGY at NPTEL Curriculum
week-01
M1L1: History Of Microwave Remote Sensing
M1L2: Overview Of Active And Passive Microwave Remote Sensing
M1L3: Fundamentals Laws Of Remote Sensing
week -02
M1L4: Scattering Of Microwaves
M2L1: Synthetic Aperture Radars - Basics
M2L2: Sar Image Processing - Fundamental Terminologies
week-03
Tutorial 02 : Exploring Alos Palsar Data In Python
M2L5: Understanding Radar Imagery
Tutorial 03: Introduction To SNAP
week-04
M2L6: Doppler Shift
M2L7: Speckle
M2L8: Speckle- How To Handle
week-05
Tutorial 04 Part 03: Statistics Using Python
Tutorial 04 Part 04: Hypothesis Tesing Using Python
week-o6
M2L12: Polarization
Tutorial 05 Part 01: Speckle Filtering Using Python
week-07
M3L1: Image Classification - Basics
M3L2: Supervised Classification
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MICROWAVE REMOTE SENSING IN HYDROLOGY