ASSESSMENT OF THE UTILITY OF THE ADVANCED HIMAWARI IMAGER TO DETECT ACTIVE FIRE OVER AUSTRALIA
Wildfire detection and attribution is an issue of importance due to the socio-economic impact of fires in Australia. Early detection of fires allows emergency response agencies to make informed decisions in order to minimise loss of life and protect strategic resources in threatened areas. Until r...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-06-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B8/65/2016/isprs-archives-XLI-B8-65-2016.pdf |
| Summary: | Wildfire detection and attribution is an issue of importance due to the socio-economic impact of fires in Australia. Early detection of
fires allows emergency response agencies to make informed decisions in order to minimise loss of life and protect strategic resources
in threatened areas. Until recently, the ability of land management authorities to accurately assess fire through satellite observations of
Australia was limited to those made by polar orbiting satellites. The launch of the Japan Meteorological Agency (JMA) Himawari-8
satellite, with the 16-band Advanced Himawari Imager (AHI-8) onboard, in October 2014 presents a significant opportunity to improve
the timeliness of satellite fire detection across Australia. The near real-time availability of images, at a ten minute frequency, may also
provide contextual information (background temperature) leading to improvements in the assessment of fire characteristics. This paper
investigates the application of the high frequency observation data supplied by this sensor for fire detection and attribution. As AHI-8 is
a new sensor we have performed an analysis of the noise characteristics of the two spectral bands used for fire attribution across various
land use types which occur in Australia. Using this information we have adapted existing algorithms, based upon least squares error
minimisation and Kalman filtering, which utilise high frequency observations of surface temperature to detect and attribute fire. The
fire detection and attribution information provided by these algorithms is then compared to existing satellite based fire products as well
as in-situ information provided by land management agencies. These comparisons were made Australia-wide for an entire fire season -
including many significant fire events (wildfires and prescribed burns). Preliminary detection results suggest that these methods for fire
detection perform comparably to existing fire products and fire incident reporting from relevant fire authorities but with the advantage
of being near-real time. Issues remain for detection due to cloud and smoke obscuration, along with validation of the attribution of fire
characteristics using these algorithms. |
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| ISSN: | 1682-1750 2194-9034 |