| Presentation | 2023-12-08 Towards Satellite Data Fusion For Active Fire Detection Nur Fajar Trihantoro, Simon Jones, Karin Reinke, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(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) |
| Keyword(in English) | Kalman Filter / Data Fusion / Wildfire Detection / Earth Observation / Brightness Temperature / Middle Infrared / Diurnal Temperature Cycle |
| Paper # | SANE2023-65 |
| Date of Issue | 2023-11-30 (SANE) |
| Conference Information | |
| Committee | SANE |
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| Conference Date | 2023/12/7(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Surakarta, Indonesia |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | ICSANE |
| Chair | Toshio Wakayama(Mitsubishi Electric) |
| Vice Chair | Takeshi Amishima(Meiji Univ.) / Atsushi Kezuka(ENRI) |
| Secretary | Takeshi Amishima(Mitsubishi Electric) / Atsushi Kezuka(Univ. of Electro-Comm) |
| Assistant | Junichi Naganawa(ENRI) / Yoshihiko Akamine(TRDI) |
| Paper Information | |
| Registration To | Technical Committee on Space, Aeronautical and Navigational Electronics |
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| Language | ENG |
| 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 |
| 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.) |
| Date | 2023-12-08 |
| Paper # | SANE2023-65 |
| Volume (vol) | vol.123 |
| Number (no) | SANE-298 |
| Page | pp.pp.35-35(SANE), |
| #Pages | 1 |
| Date of Issue | 2023-11-30 (SANE) |