TY - GEN
T1 - An environmental-semantic computing system of multispectral imagery for coral health monitoring and analysis
AU - Wijitdechakul, Jinmika
AU - Kiyoki, Yasushi
AU - Koopipat, Chawan
N1 - Funding Information:
Firstly, This research is supported in part by MEXT Grant-in-Aid for the Program for Leading Graduate School Program (GESL) and Multimedia Database Laboratory (MDBL), Graduate School of Media and Governance, Keio University. Secondly, We would like to express my gratitude to Dr. Supawat Kan-Atireklap, Director of Marine and Coastal Resources Research and Development Center, Eastern Gulf of Thailand and diver teams for supporting our experiment. Lastly, We thank the anonymous reviewers for their valuable and suggestions.
Publisher Copyright:
© 2019 The authors and IOS Press. All rights reserved.
PY - 2019
Y1 - 2019
N2 - The global environmental analysis system is a new platform to analyze environmental multimedia data that acquired from nature resources. This study aims to realize and interpret coral reefs phenomena and changes occurring that happening in global scale by utilizing Acropora coral as a bioindicator or natural sensing. This paper presents a new environmental-semantic computing system of multispectral imagery for automated coral health monitoring and analysis to realize and recognize coral condition in actual situation. Multispectral semantic-image space for coral monitoring and analysis can be utilized for ocean environment monitoring and assessment by measuring coral reef health which highly beneficial to the current ocean pollution problem. Our method applies semantic distance calculation to measure similarity between multispectral image data and context images including three coral conditions (healthy, bleaching, and dead). In our experiments, we applied the SPA function which is an effective concept to design environmental systems with Physical-Cyber integration. This paper presents case study of Acropora coral monitoring and assessment at Man-nai Island, Rayong province, Thailand. Therefore, an additional objective of this research is to apply the Artificial Intelligence (AI) and Environmental monitoring system for combatting the ocean pollution problem by transferring the knowledges and technology from computer science fields to fundamental marine science research.
AB - The global environmental analysis system is a new platform to analyze environmental multimedia data that acquired from nature resources. This study aims to realize and interpret coral reefs phenomena and changes occurring that happening in global scale by utilizing Acropora coral as a bioindicator or natural sensing. This paper presents a new environmental-semantic computing system of multispectral imagery for automated coral health monitoring and analysis to realize and recognize coral condition in actual situation. Multispectral semantic-image space for coral monitoring and analysis can be utilized for ocean environment monitoring and assessment by measuring coral reef health which highly beneficial to the current ocean pollution problem. Our method applies semantic distance calculation to measure similarity between multispectral image data and context images including three coral conditions (healthy, bleaching, and dead). In our experiments, we applied the SPA function which is an effective concept to design environmental systems with Physical-Cyber integration. This paper presents case study of Acropora coral monitoring and assessment at Man-nai Island, Rayong province, Thailand. Therefore, an additional objective of this research is to apply the Artificial Intelligence (AI) and Environmental monitoring system for combatting the ocean pollution problem by transferring the knowledges and technology from computer science fields to fundamental marine science research.
KW - Coral health monitoring
KW - Corals
KW - Global Environmental Analysis
KW - Multispectral image
KW - Semantic computing
UR - http://www.scopus.com/inward/record.url?scp=85059571480&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059571480&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-933-1-293
DO - 10.3233/978-1-61499-933-1-293
M3 - Conference contribution
AN - SCOPUS:85059571480
T3 - Frontiers in Artificial Intelligence and Applications
SP - 293
EP - 311
BT - Information Modelling and Knowledge Bases XXX
A2 - Endrjukaite, Tatiana
A2 - Jaakkola, Hannu
A2 - Dudko, Alexander
A2 - Kiyoki, Yasushi
A2 - Thalheim, Bernhard
A2 - Yoshida, Naofumi
PB - IOS Press
ER -
