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Paper Abstract and Keywords
Presentation 2023-12-08 08:50
Towards Satellite Data Fusion For Active Fire Detection
Nur Fajar Trihantoro, Simon Jones, Karin Reinke (RMIT Univ.) SANE2023-65
Abstract (in Japanese) (See Japanese page) 
(in English) Numerous Earth observation satellite instruments show potential for monitoring wildfire, yet current fire detection algorithms mostly rely on data from a single sensor. This highlights an opportunity to explore a multi-sensor approach, considering the abundance of available Earth observation data. This study introduces a novel data-fusion-based algorithm utilizing Earth observation satellite data. It aims to create a reliable fire detection system, merging middle infrared data from geostationary sensors like Himawari-8/9 AHI, GeoKompsat-2 AMI, and low earth orbit sensors like Sentinel-3 SLSTR. The Kalman filter is the data fusion method, which enhances data accuracy by filtering out noise. Following Roberts and Wooster's [1] approach, a Diurnal Temporal Cycle model provides background temperature information. Preliminary results show promise, with detection rates exceeding 95% for various scenarios, highlighting the algorithm's potential. The presented approach showcases a promising advancement in active fire detection, combining the benefits of data fusion and conventional methodology for improved accuracy and adaptability in disaster management scenarios. The method's sensor agnosticism, iterative detection process, and consideration of resolution discrepancies mark significant advancements, addressing limitations observed in existing fire detection methodologies. Future steps involve refining the algorithm's performance across varied study cases, addressing spatial and temporal resolution disparities among input sensors, and scaling the method for near real-time implementation to enhance its utility in disaster response further.
Keyword (in Japanese) (See Japanese page) 
(in English) Kalman Filter / Data Fusion / Wildfire Detection / Earth Observation / Brightness Temperature / Middle Infrared / Diurnal Temperature Cycle /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 298, SANE2023-65, pp. 35-35, Dec. 2023.
Paper # SANE2023-65 
Date of Issue 2023-11-30 (SANE) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee SANE  
Conference Date 2023-12-07 - 2023-12-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Surakarta, Indonesia 
Topics (in Japanese) (See Japanese page) 
Topics (in English) ICSANE 
Paper Information
Registration To SANE 
Conference Code 2023-12-SANE 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Towards Satellite Data Fusion For Active Fire Detection 
Sub Title (in English)  
Keyword(1) Kalman Filter  
Keyword(2) Data Fusion  
Keyword(3) Wildfire Detection  
Keyword(4) Earth Observation  
Keyword(5) Brightness Temperature  
Keyword(6) Middle Infrared  
Keyword(7) Diurnal Temperature Cycle  
Keyword(8)  
1st Author's Name Nur Fajar Trihantoro  
1st Author's Affiliation RMIT University (RMIT Univ.)
2nd Author's Name Simon Jones  
2nd Author's Affiliation RMIT University (RMIT Univ.)
3rd Author's Name Karin Reinke  
3rd Author's Affiliation RMIT University (RMIT Univ.)
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Speaker Author-1 
Date Time 2023-12-08 08:50:00 
Presentation Time 20 minutes 
Registration for SANE 
Paper # SANE2023-65 
Volume (vol) vol.123 
Number (no) no.298 
Page p.35 
#Pages 1 
Date of Issue 2023-11-30 (SANE) 

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