MARINE OIL SPILL POLLUTION DECISION SUPPORT SYSTEM USING NOVEL GEOSPATIAL AND ARTIFICIAL INTELLIGENCE MODELS
The inability to rapidly identify the location of the spill has resulted to various environmental consequences in the coastal ecosystem. Remote sensing technology has proven to be beneficial in the detection of marine oil spills. A major challenge with remote sensing remains the false positive detec...
| Main Author: | YEKEEN, SHAMSUDEEN TEMITOPE |
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| Format: | Thesis |
| Language: | English |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-utpedia.20688 / |
| Published: |
2021
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| Subjects: | |
| Online Access: |
http://utpedia.utp.edu.my/20688/1/Shamsudeen%20Temitope%20Yekeen_18001318.pdf http://utpedia.utp.edu.my/20688/ |
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| Summary: |
The inability to rapidly identify the location of the spill has resulted to various environmental consequences in the coastal ecosystem. Remote sensing technology has proven to be beneficial in the detection of marine oil spills. A major challenge with remote sensing remains the false positive detection of non-oil slick as oil slick because of the similar visual attributes with the non-oil slick (lookalike) elements like low wind areas, natural films, wind front areas, etc. Also, a large percentage of oil spill effects on coastal ecosystems is linked to the unavailability of reliable Decision Support Systems (DSS) which can accurately delineate the vulnerable coastal resources for prompt intervention at different climatic seasons. |
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