NERTO Research Project Title:

Evaluation of Ocean Color Models using Landsat 8 OLI imagery for the Caribbean

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NERTO Outcomes:

I did not receive any particular or specific training. The research outcomes are related to understanding image processing and data analysis.

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Value of NERTO to the Line Office:

NESDIS-STAR supports sensor technology, products and applications through an extensive evaluation of data. It includes refining formulas used to improve algorithms combining data. This project aims to improve products quality for oligotrophic and shallow waters validating data. This effort tested the operational algorithms using Landsat 8 in need of regional and local monitoring for coastal areas. It promotes the scientific and informed management of ocean’s natural resources.

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NERTO Skills:

I started reviewing the basics of python through an open virtual course from EdX platform and two NOAA webinars. Lately, I decided to continue using the SeaDAS GUI platform to complete the work on time. On the other hand, my mentors suggested a paper that led me to be involved in searching for metrics to be implemented in my research. So now, I've been working on statistical data analysis that I never worked before. It is an advantage for my research project.