News
2019 Advanced Training Course on Ocean Colour Remote Sensing: 24 – 31 October 20
上传时间：2019-05-10 10:21:00 浏览次数：
Overview
An advanced training course on ocean colour remote sensing will be held in Hangzhou, China from 24-31 October 2019 to promote satellite ocean colour data applications. This training event is sponsored by the International Ocean-Colour Coordinating Group (IOCCG), the European Commission Copernicus Programme, the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), the State Key Laboratory of Satellite Ocean Environment Dynamics (SOED/SIO/MNR, China), the National Satellite Ocean Application Service (NSOAS, China), and Zhejiang University (ZJU, China).
The key objective of this training is to help early career scientists to download, analyze and visualize data from the EUMETSAT Copernicus Marine Data Stream as well as the Chinese HY-1C ocean colour mission. Participants will also learn how to use the Marine Satellite Data Online Analysis Platform (SatCO2) for environmental monitoring and scientific research, including water quality monitoring, red tide detection, and marine carbon cycling/climate change investigations.
Students are encouraged to bring their own laptop computers for the hands-on training sessions, but a limited number of desk top computers will also be available for these sessions.
Course Description
The training course will include lectures and hands-on practical sessions, as well as a field investigation to Lake Qiandao to enable students to gain a fundamental knowledge of optical instruments and enable them to make quality measurements.
Lectures
L1. Accessing Copernicus data
L2. Introduction to tools and system set up check
L3. Assessing ocean colour data quality
L4. Chinese ocean colour satellite data HY-1C
L5. Coastal water quality and harmful algal bloom
L6. Remote sensing of marine carbon cycle
L7. Time series satellite records and global change
L2. Introduction to tools and system set up check
L3. Assessing ocean colour data quality
L4. Chinese ocean colour satellite data HY-1C
L5. Coastal water quality and harmful algal bloom
L6. Remote sensing of marine carbon cycle
L7. Time series satellite records and global change
Hands-on Practical Sessions
P1. Data access (CODA and batch downloading with Python)
P2. Data quality assessment in SNAP
P3. Working with OLCI data in Python
P4. Introduction of Marine Satellite Data Online Analysis Platform (SatCO2)
P5: Harmful algal bloom detection in SatCO2
P6. Air-sea CO2 flux estimation in SatCO2
P7: Time series satellite data analysis in SatCO2
P2. Data quality assessment in SNAP
P3. Working with OLCI data in Python
P4. Introduction of Marine Satellite Data Online Analysis Platform (SatCO2)
P5: Harmful algal bloom detection in SatCO2
P6. Air-sea CO2 flux estimation in SatCO2
P7: Time series satellite data analysis in SatCO2
Application
Early career scientists, including postdoctoral fellows and junior scientists from Asian countries are cordially invited to apply for this training course. Since this is an advanced training course, all trainees are required to have basic experience in using satellite ocean colour data. The course will be limited to 20 participants. In principal, participants are required to cover the cost of their own travel as well as local accommodation. A limited number of IOCCG scholarships will be available to cover international flights for students residing outside of China, subject to evaluation by a Selections Committee.
If you are interested in attending this training course, please complete the application form below before 15 June 2019. A brief CV (1-2 pages) is required with the application form. The steering committee will review all applications and inform you of the success of your application no later than 15 July 2019.
Course Sponsors and Organizers
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International Ocean-Colour Coordinating Group (IOCCG)
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European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)
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State Key Laboratory of Satellite Ocean Environment Dynamics (SOED/SIO/MNR)
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National Satellite Ocean Application Service (NSOAS, China)
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Institute of Geographic Information Science/Zhejiang University (ZJU, China).
