Summary

Course description              

Ocean colour analysis is a proven tool for determining the health of ocean using oceanic biological activity through optical means. Phytoplankton pigment, chlorophyll, are indicators of equilibrium of CO₂ concentration between atmosphere and ocean. The oceanic colour changes due to chlorophyll a provides the level of primary productivity whereas the colour change due to CDOM can be attributed to the level of pollution and higher particulate matter. The ability of optical sensors to map the spatial and temporal patterns of ocean colour over regional and global scales has provided important insights into the fundamental bio-optical properties and bio-physical processes occurring in the aquatic media. Chlorophyll, SST and PAR can be operationally scaled up to estimate primary production and estimate the fish stocks. This training focuses on the basics of marine optics, ocean colour remote sensing, and its applications such as mapping primary productivity, phytoplankton classes and algal blooms. 

Learning outcomes

By the end of the course the participants should be able to:

• explain what Ocean Colour Remote Sensing and Marine optics are, and describe Ocean colour- sensor characteristics, data, and uncertainties.
• understand Ocean colour Algorithms, Chlorophyll, shallow water remote sensing, algal blooms
• Perform atmospheric correction of ocean colour observations.
• Describe primary production mechanisms and P-I experiments
• Perform phytoplankton classification using ocean colour data.
• Use the SeaDAS tool for processing ocean colour data (including the software and Plug-in tools for ocean data processing).
• Use different ocean colour algorithms.
• Generate and validate ocean colour remote sensing products.
• Understand ocean colour applications like PP, HABs etc.

Target audience

Target audiences include, but are not limited to, the following:

• Ocean and coastal data managers
• Staff and researchers working on ocean colour applications.
• Scientific/Technical staff involved in policy/decision making.
• University post-graduates

Course content (Topics and activities to be covered)

• L1: Fundamentals of marine optics and ocean colour remote sensing (Aneesh A. Lotliker)
• L2: Introduction to ocean colour satellite data processing with SeaDAS (Alakes Samanta)
• L3: Marine environmental variables vis-a-vis phytoplankton (Sanjiba Kumar Baliarsingh)
• L4: Ocean Colour Algorithms - Standard and Value-added products (Alakes Samanta)
• P1: Introduction to SeaDAS: processing capability and available tools; Processing, Projection and Binning of satellite ocean colour data using GUI of SeaDAS (Alakes Samanta / Sanjiba Kumar Baliarsingh)
• L5: Remote sensing of phytoplankton functional types (Sanjiba Kumar Baliarsingh)
• L6: Remote sensing in operational services (TBD)
• P2: Automatic processing of ocean colour satellite data using SeaDAS (Alakes Samanta / Sanjiba Kumar Baliarsingh)
• L7: Laboratory Analysis of optically active substances (TBD)
• P3: Generation of value-added products using SeaDAS (Alakes Samanta / Sanjiba Kumar Baliarsingh)
• P4: Mini Project

Instructors/Trainers

• Dr. Aneesh Lotliker, Scientist INCOIS, MoES
• Mr. Alakes Samanta, Scientist INCOIS, MoES
• Dr. Sanjiba Kumar Baliarsingh, Scientist INCOIS, MoES
• Others to be announced

Language

English

Pre-course Activities or Assessment

The mandatory online phase of the course takes place between 28^th November – 9^th December 2022 and this will be followed by the onsite course. The shortlisted candidates are expected to go through all the online course material and finish reading the material and the assignments before participating in the onsite course. The grades of the assignments will be added to the final grades.

Candidates must also familiarize themselves with the following:

1. Basic terminal commands (bash) in Linux (ubuntu) based system.
2. NetCDF files data structure
3. Understanding Satellite data levels (L0, L1, L2, L3)
4. Understanding basic concepts of ocean optics

Learner assessment

Assignment and tests will be conducted during the course while undergoing training. Pre-course assignments will also be counted for final grade.

Pre-requisites:

Language and computer skills required:

Applicants are expected to have:

• a working knowledge of English
• basic computer skills
• finding resources through search engines
• downloading and installing software
• using a word processing, presentation software, or other productivity applications
• using a data plotting application (e.g., Grapher, Origin, Sigma Plot)
• experience/familiarity with a variety of file formats such as: .pdf, doc or .docx, .txt, and .csv
• the ability to be self-directed in learning new technology skills (e.g., following a step-by-step tutorial, online video help, or access to support to learn necessary skills)
• Computer with Linux based (ubuntu) operating system or dual boot with Linux

Technology requirements

To complete this course, you should have access to:

1. Latest version of either Chrome, Edge, Firefox, or Safari web browsers
2. Linux (preferably ubuntu 16.04 or above)
3. Install SeaDAS (https://seadas.gsfc.nasa.gov/downloads/)
4. Access to internet (access during the onsite phase will be provided by INCOIS only to those who have valid antivirus installed)
5. For dual boot systems with Linux-Windows, Original Windows OS and active antivirus subscription required for INCOIS provided internet access.