IACM Colloquium
Speaker:
Katerina Spanoudaki
IACM-FORTH
Title:
Developing a near-real time detection and forecasting system for marine oil spills
Abstract:
The world’s oceans have been studied and monitored for many decades to enhance our understanding. In today’s world, with the explosion of new data provided by many different Earth observation sources and the availability of advanced computing infrastructures (cloud computing, HPC, IoT, Big Data, social networking, and more), creating a digital representation of the ocean is becoming a reality. The EU funded Iliad project builds on the assets resulting from two decades of investments in policies and infrastructures for the blue economy, aiming to establish an interoperable, data-intensive, and cost-effective Digital Twin of the Ocean (DTO). Iliad DTO combines ocean observations, state-of-the-art forecast models, citizen science, artificial intelligence and advanced computing infrastructures to create high-resolution, multi-variable and multi-dimensional near real-time virtual representations of the ocean. Several Digital Twin (DT) pilots will be undertaken in key thematic areas such as offshore wind energy, wave and tidal energy, biodiversity assessments, fisheries and aquaculture, marine pollution and more.
The current work presents the Oil Spill Response Digital Twin pilot developed in the frame of Iliad. The DT focuses on Cretan Sea and aims to provide early detection of marine oil spills and operational forecasting of spill trajectories to support immediate response to pollution events, minimizing thus the impact on marine ecosystems, coastal communities and the economy. A near-real time automatic oil spill detection system, from Sentinel-1 SAR images, is developed, which allows early detection of marine oil spills. Automatic detection and classification of oil spill events employs a trained FCOS model, which perxforms initial object detection, fine-tuned with a dataset of more than 1000 SAR images, including 4 different classes (oil spill, look-alike, ship, land). Image pre-processing and oil spill mask delineation is perxformed using SNAPpy-based (Sentinel Application Platxform Python toolbox) adaptive thresholding algorithms. A multi-model approach is followed for predicting the fate and transport of oil spills, employing MEDSLIK-II and OpenDrift particle tracking models, coupled to operational, high-resolution numerical weather (WRF), hydrodynamic (NEMO) and sea state (WAVEWATCH III) models for Cretan Sea. The oil spill detection and forecasting system is tested by reconstructing major spills that have occurred in the Mediterranean Sea. Sentinel-1 images are used to detect and delineate the coverage of the spill and to initiate the Lagrangian particle models for simulating oil spill fate and transport. Quantitative metrics are used to evaluate the ability of the oil spill models to reproduce the satellite oil spill observations.
Short Bio:
Dr. Katerina Spanoudaki is currently a collaborating researcher at the Institute of Applied and Computational Mathematics of the Foundation of Research and Technology – Hellas (IACM-FORTH). Her academic background is in Engineering (Diploma in Engineering from the National Technical University of Athens-NTUA, MSc in Environmental Engineering and Hydrology from Imperial College-London, PhD in Water Resources Engineering from NTUA).
Her research interests include the development and application of numerical models for surface water-groundwater flow and pollution interactions; inland and transitional waters hydrodynamics modelling; hydropower potential modelling and forecasting; coastal and inland flooding forecasting; marine pollution, ocean circulation and waves modelling, including the development of modelling components for the COASTAL CRETE operational ocean forecasting system, producing hourly forecasts for currents, waves and oil spills dispersion, on a daily basis. She is also leading tasks and activities related to ocean prediction (on behalf of FORTH), for the H2020 project ILIAD: INTEGRATED DigitaL Framework FOR Comprehensive MARITIME DATA AND INxFORMATION SERVICES, which aspires to build the first interoperable, data-intensive, and cost-effective Digital Twin of the Ocean.
She is a member of the steering committee of the MEDSLIK-II oil spill fate and transport community model and has developed algorithms for the physicochemical and biological interactions of oil spills with the marine environment and the simulation of deep-sea oil plumes. She is co-chairing the MonGOOS applications WG and she is a member of the steering committee for the UN Ocean Decade Ocean Prediction DCC for the Mediterranean and Black Seas. She has received 2 awards for her research in developing numerical models for environmental problems: The 2013 Computers & Geosciences Research Scholarship award for 3D numerical modelling of surface water-groundwater flow and salinity interactions in the coastal zone, Sponsored by Elsevier and the International Association of Mathematical Geosciences (IAMG) and the 2001, IPHE Prize (Institution of Public Health Engineers), for developing a modelling framework for predicting pathogen destruction in anaerobic sludge digesters. She has participated as a researcher in more than 25 research projects and has more than 40 publications in journals, book chapters and conference proceedings.
Time, Date & Location:
15:00, Thursday, March 28th, 2024, Fotakis Room
Zoom Info:
https://us06web.zoom.us/j/7761040361?pwd=dEs4TFZxck01Vk5PQWR1TUxKdndwUT09&omn=81030607604
Meeting ID: 776 104 0361
Passcode: 787479
Speaker:
Katerina Spanoudaki
IACM-FORTH
Title:
Developing a near-real time detection and forecasting system for marine oil spills
Abstract:
The world’s oceans have been studied and monitored for many decades to enhance our understanding. In today’s world, with the explosion of new data provided by many different Earth observation sources and the availability of advanced computing infrastructures (cloud computing, HPC, IoT, Big Data, social networking, and more), creating a digital representation of the ocean is becoming a reality. The EU funded Iliad project builds on the assets resulting from two decades of investments in policies and infrastructures for the blue economy, aiming to establish an interoperable, data-intensive, and cost-effective Digital Twin of the Ocean (DTO). Iliad DTO combines ocean observations, state-of-the-art forecast models, citizen science, artificial intelligence and advanced computing infrastructures to create high-resolution, multi-variable and multi-dimensional near real-time virtual representations of the ocean. Several Digital Twin (DT) pilots will be undertaken in key thematic areas such as offshore wind energy, wave and tidal energy, biodiversity assessments, fisheries and aquaculture, marine pollution and more.
The current work presents the Oil Spill Response Digital Twin pilot developed in the frame of Iliad. The DT focuses on Cretan Sea and aims to provide early detection of marine oil spills and operational forecasting of spill trajectories to support immediate response to pollution events, minimizing thus the impact on marine ecosystems, coastal communities and the economy. A near-real time automatic oil spill detection system, from Sentinel-1 SAR images, is developed, which allows early detection of marine oil spills. Automatic detection and classification of oil spill events employs a trained FCOS model, which perxforms initial object detection, fine-tuned with a dataset of more than 1000 SAR images, including 4 different classes (oil spill, look-alike, ship, land). Image pre-processing and oil spill mask delineation is perxformed using SNAPpy-based (Sentinel Application Platxform Python toolbox) adaptive thresholding algorithms. A multi-model approach is followed for predicting the fate and transport of oil spills, employing MEDSLIK-II and OpenDrift particle tracking models, coupled to operational, high-resolution numerical weather (WRF), hydrodynamic (NEMO) and sea state (WAVEWATCH III) models for Cretan Sea. The oil spill detection and forecasting system is tested by reconstructing major spills that have occurred in the Mediterranean Sea. Sentinel-1 images are used to detect and delineate the coverage of the spill and to initiate the Lagrangian particle models for simulating oil spill fate and transport. Quantitative metrics are used to evaluate the ability of the oil spill models to reproduce the satellite oil spill observations.
Short Bio:
Dr. Katerina Spanoudaki is currently a collaborating researcher at the Institute of Applied and Computational Mathematics of the Foundation of Research and Technology – Hellas (IACM-FORTH). Her academic background is in Engineering (Diploma in Engineering from the National Technical University of Athens-NTUA, MSc in Environmental Engineering and Hydrology from Imperial College-London, PhD in Water Resources Engineering from NTUA).
Her research interests include the development and application of numerical models for surface water-groundwater flow and pollution interactions; inland and transitional waters hydrodynamics modelling; hydropower potential modelling and forecasting; coastal and inland flooding forecasting; marine pollution, ocean circulation and waves modelling, including the development of modelling components for the COASTAL CRETE operational ocean forecasting system, producing hourly forecasts for currents, waves and oil spills dispersion, on a daily basis. She is also leading tasks and activities related to ocean prediction (on behalf of FORTH), for the H2020 project ILIAD: INTEGRATED DigitaL Framework FOR Comprehensive MARITIME DATA AND INxFORMATION SERVICES, which aspires to build the first interoperable, data-intensive, and cost-effective Digital Twin of the Ocean.
She is a member of the steering committee of the MEDSLIK-II oil spill fate and transport community model and has developed algorithms for the physicochemical and biological interactions of oil spills with the marine environment and the simulation of deep-sea oil plumes. She is co-chairing the MonGOOS applications WG and she is a member of the steering committee for the UN Ocean Decade Ocean Prediction DCC for the Mediterranean and Black Seas. She has received 2 awards for her research in developing numerical models for environmental problems: The 2013 Computers & Geosciences Research Scholarship award for 3D numerical modelling of surface water-groundwater flow and salinity interactions in the coastal zone, Sponsored by Elsevier and the International Association of Mathematical Geosciences (IAMG) and the 2001, IPHE Prize (Institution of Public Health Engineers), for developing a modelling framework for predicting pathogen destruction in anaerobic sludge digesters. She has participated as a researcher in more than 25 research projects and has more than 40 publications in journals, book chapters and conference proceedings.
Time, Date & Location:
15:00, Thursday, March 28th, 2024, Fotakis Room
Zoom Info:
https://us06web.zoom.us/j/7761040361?pwd=dEs4TFZxck01Vk5PQWR1TUxKdndwUT09&omn=81030607604
Meeting ID: 776 104 0361
Passcode: 787479