TEMPORAL ANALYSIS OF MARINE MUCILAGE IN THE SEA OF MARMARA USING UNMIXING BASED CHANGE DETECTION

Çağatay Esi; Ali Özgün Ok; Esra Erten; Alp Ertürk

doi:10.1109/IGARSS52108.2023.10282098

TEMPORAL ANALYSIS OF MARINE MUCILAGE IN THE SEA OF MARMARA USING UNMIXING BASED CHANGE DETECTION

Çağatay Esi, Ali Özgün Ok, Esra Erten, Alp Ertürk

Department of Geomatics Engineering

Research output: Contribution to conference › Paper › peer-review

2 Citations (Scopus)

Abstract

Earth observation (EO) sensors and remote sensing play a crucial role in the detection and analysis of environmental hazards. Among these hazards, monitoring and understanding marine pollution remain challenging problems due to the complex and dynamic spatio-temporal characteristics of pollution and water. The recent outbreak of marine mucilage (or sea-snot) in the inland Sea of Marmara in the Spring of 2021 is a striking example of a dynamic environmental pollution, This work investigates temporal analysis of mucilage by unmixing based change detection on temporal hyperspectral satellite data acquired with the recently launched PRISMA sensor. The proposed unmixing-based approach enables detecting temporal changes in terms of endmembers and abundances, and hence provides information on the nature of the change, in an unsupervised manner without any training step.

Original language	English
DOIs	https://doi.org/10.1109/IGARSS52108.2023.10282098
Publication status	Published - 2023
Event	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, United States Duration: 16 Jul 2023 → 21 Jul 2023

Conference

Conference	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Country/Territory	United States
City	Pasadena
Period	16/07/23 → 21/07/23

Bibliographical note

Publisher Copyright:
© 2023 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

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10.1109/IGARSS52108.2023.10282098

Cite this

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title = "TEMPORAL ANALYSIS OF MARINE MUCILAGE IN THE SEA OF MARMARA USING UNMIXING BASED CHANGE DETECTION",

abstract = "Earth observation (EO) sensors and remote sensing play a crucial role in the detection and analysis of environmental hazards. Among these hazards, monitoring and understanding marine pollution remain challenging problems due to the complex and dynamic spatio-temporal characteristics of pollution and water. The recent outbreak of marine mucilage (or sea-snot) in the inland Sea of Marmara in the Spring of 2021 is a striking example of a dynamic environmental pollution, This work investigates temporal analysis of mucilage by unmixing based change detection on temporal hyperspectral satellite data acquired with the recently launched PRISMA sensor. The proposed unmixing-based approach enables detecting temporal changes in terms of endmembers and abundances, and hence provides information on the nature of the change, in an unsupervised manner without any training step.",

author = "{\c C}ağatay Esi and Ok, {Ali {\"O}zg{\"u}n} and Esra Erten and Alp Ert{\"u}rk",

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T1 - TEMPORAL ANALYSIS OF MARINE MUCILAGE IN THE SEA OF MARMARA USING UNMIXING BASED CHANGE DETECTION

AU - Esi, Çağatay

AU - Ok, Ali Özgün

AU - Erten, Esra

AU - Ertürk, Alp

PY - 2023

Y1 - 2023

N2 - Earth observation (EO) sensors and remote sensing play a crucial role in the detection and analysis of environmental hazards. Among these hazards, monitoring and understanding marine pollution remain challenging problems due to the complex and dynamic spatio-temporal characteristics of pollution and water. The recent outbreak of marine mucilage (or sea-snot) in the inland Sea of Marmara in the Spring of 2021 is a striking example of a dynamic environmental pollution, This work investigates temporal analysis of mucilage by unmixing based change detection on temporal hyperspectral satellite data acquired with the recently launched PRISMA sensor. The proposed unmixing-based approach enables detecting temporal changes in terms of endmembers and abundances, and hence provides information on the nature of the change, in an unsupervised manner without any training step.

AB - Earth observation (EO) sensors and remote sensing play a crucial role in the detection and analysis of environmental hazards. Among these hazards, monitoring and understanding marine pollution remain challenging problems due to the complex and dynamic spatio-temporal characteristics of pollution and water. The recent outbreak of marine mucilage (or sea-snot) in the inland Sea of Marmara in the Spring of 2021 is a striking example of a dynamic environmental pollution, This work investigates temporal analysis of mucilage by unmixing based change detection on temporal hyperspectral satellite data acquired with the recently launched PRISMA sensor. The proposed unmixing-based approach enables detecting temporal changes in terms of endmembers and abundances, and hence provides information on the nature of the change, in an unsupervised manner without any training step.

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M3 - Paper

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T2 - 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023

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ER -

TEMPORAL ANALYSIS OF MARINE MUCILAGE IN THE SEA OF MARMARA USING UNMIXING BASED CHANGE DETECTION

Abstract

Conference

Bibliographical note

UN SDGs

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