Cornell Logo
  Cornell University
  Earth and Atmospheric Sciences

June 3-14, 2024     


Many biological oceanographers and marine biologists have research projects that would benefit greatly from the addition of a satellite remote sensing perspective, but are prevented from using satellite data because they lack the training needed to make easy and effective use of freely available data sets.

Even people who intend to begin research careers that are specifically devoted to satellite remote sensing can be slowed down initially because they lack basic, but critical, skills.

In response to these broad needs, an intensive 2-week summer training workshop is offered to give participants the practical skills needed to work independently to acquire, analyze and visualize large data sets derived from a wide range of ocean satellite sensors.

The Course is Highly Methods-Oriented

The overarching goal of the course is to teach participants the basic skills needed to work independently with a wide variety of satellite datasets: e.g., SeaWiFS, MODIS, VIIRS, PACE, OLCI, HawkEye, GHRSST, QuikScat, SeaWinds, SSM/I and CMEMS Merged Altimetry. 

Strong emphasis is given to the use of NASA’s SeaDAS software to obtain mapped imagery of geophysical parameters (e.g., chlorophyll or CDOM) that are derived from raw satellite data obtain through the Ocean Biology DAAC. An important feature of the workshop involves running SeaDAS commands within pre-written python scripts to efficiently process large quantities of ocean color data. In addition to ocean color remote sensing, the workshop also addresses the acquisition and use of Level-3 satellite data for sea surface temperature, ocean wind speed and sea surface height.

A central goal of the course is to develop good python programming skills that are needed to make effective use of satellite data to routinely monitor ocean conditions, gain new insights into ocean dynamics, and to rigorously test new hypotheses regarding a range of oceanographic processes.  

Background lectures will cover the fundamentals of bio-optics, pigment algorithms, primary production algorithms and, to a lesser extent, the underlying physical principals leading to the measurement of sea surface temperature, ocean wind speed and ocean topography. See the course syllabus link for more details on the topics covered in this course.  

The class it typically comprised of about 80% graduate students, 15% post-graduate professionals and 5% undergraduates. Participants come from universities, NOAA/NASA facilities and private companies. There is also often international representation.  

Some prior python programming experience helps, but it is certainly not a prerequisite. The programming work will begin at a very basic level. More advanced students having some prior programming experience will be given more challenging programming problems from which to learn.  

Great effort is made to make the course fun and low stress while at the same time challenging the participants to learn a very large amount of material in a relatively short amount of time.