Meet Maria Yulmetova, OFI Module I Master's student

by Maria Yulmetova

I use freely available satellite images to create maps which will help protect the environment and coastal communities in case of an oil spill.

Sentinel-2 image processing for shoreline classification in Newfoundland. ©Maria Yulmetova

Maria is a second-year master's student in engineering at Memorial University of Newfoundland (MUN) in St. John's. Her current project is related to the satellite-based shoreline classification for an oil spill response. She investigates the potential of Sentinel-2 imagery for coastal environmental sensitivity mapping. She specializes in the field of remote sensing and GIS. Having a background in engineering, she has also received a Diploma in GIS at MUN, where she got knowledge in spatial analysis, mapping, and remote sensing. During the last 3+ years, she has been involved in various GIS projects working on river ice monitoring, iceberg detection, mineral mapping, GIS dataset development, land investigation and analysis, etc. 

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What is your research about? What are you currently working on? 

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One hundred seventy-six oil spills occurred for the last decade during an offshore oil exploration and production in the Newfoundland and Labrador offshore area. Despite the significant development of new technologies for oil spill clean-up, it remains questionable whether we are able to mitigate a big oil spill in harsh environments like Newfoundland offshore. In fact, when Newfoundland's largest-ever oil spill happened in 2018, zero liters (out of 250,000) of spilled oil was collected during recovery efforts. Failing to mitigate will eventually cause the spilled oil to be washed onto shore.

My master's project aims to develop an on-shore oil spill clean-up preparedness. My research focuses on assessing the potential for shoreline classification using satellite and airborne data. Applying automated processing techniques to the satellite data allows a more cost- and time-effectively broad-scale mapping compared to the traditional helicopter videography. The developed algorithm for the shoreline classification is the first step to revealing the areas that have the most significant potential to be damaged in the case of an oil spill, which sets the priorities for shoreline clean-up.

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What is the most interesting aspect of your research? Share something you have discovered through your research so far.

I believe that the most exciting aspect of any research is developing something new. Although there have been several projects on shoreline classification, there is still no algorithm that could be applied to the whole Canadian coastline.

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How does your research address present day fisheries issues in Newfoundland and Labrador and elsewhere? How does it help inform governance responses for coastal communities in the province in a context of change?

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The resulting land cover classification map will depict different shore types and allow the determination of oil spill sensitive coastal environments. The obtained land cover classification data will be necessary to produce an ESI map which gathers the information about sensitive shorelines and other vulnerable biological and human-use resources. It will improve overall preparedness and help the government to make more efficient and informed decisions, thus reducing the environmental impact of oil spills.

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What is the one thing you would like the general public to know about your research?

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I use freely available satellite images to create maps which will help protect the environment and coastal communities in case of an oil spill.

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What are the next steps and what do you want to achieve with your research?

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I am on the final stage of my program summarizing and writing the thesis.

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What do you like doing when you are not working on research?

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Hiking, camping, fishing, doing yoga or just hanging out with my family.

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