Abstract

Abstract. The Fengyun-4A (FY-4A) is a relatively new geostationary satellite launched by the National Satellite Meteorological Center of China in 2016. With its Advanced Geosynchronous Radiation Imager (AGRI) instrument, FY-4A was able to provide a Fire and Hotspot product (FHS). This study explored the use of the FHS product in detecting wildfires and was compared to the similar fire detection product of the Visible Infrared Imaging Radiometer Suite (VIIRS) with the goal of assessing its effectiveness in the early detection and monitoring of wildfires. The FY-4A FHS and the VIIRS fire detection products have spatial resolutions of 2 km and 375 m, and temporal resolutions of 15 minutes and 12 hours, respectively. The results of the comparative study showed that the FY-4A FHS product generated false negative results for detecting wildfires smaller than 20 pixels of VIIRS data (∼2.82 km2), at less than 4 MW of radiative power, and brightness temperature lower than 330 K. The FY-4A FHS product was also shown to be 50% accurate (1 correct and 1 false negative out of 2 samples) in detecting large wildfires (>2.5 km2) with high radiative power (>4 MW) and high brightness temperature (>330 K). Lower accuracy may also be attributed to the presence of clouds that tend to obscure satellite images leading to an even lower accuracy of wildfire detection. For future studies, it is recommended that a comparison of the FY-4A FHS product be made with a more similar instrument, for example, the Advanced Himawari Imager 8/9 (AHI 8/9). It is also recommended to improve the fire and hotspot algorithm by incorporating a Normalized Brightness Temperature Difference Index (NBTDI) or by incorporating diurnal temperature cycle modelling for the older FY-2G data. Lastly, if available, a more reliable accuracy assessment can be done using FHS products of higher spatial resolution (at least 500 m).

Highlights

  • 1.1 Background of the StudyWildfires are unplanned fires that burn in natural areas such as forests, grasslands, or prairies

  • Et al (2019), compared the fire algorithm developed for the FY-2G Stretched Visible and Infrared Spin Scan Radiometer (S-VISSR) with the fire detection from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System satellites Terra and Aqua

  • This study focused on comparing and analyzing readily available fire and hotspot data from the National Satellite Meteorological Center of China and the fire detection product from the Visible Infrared Imaging Radiometer Suite (VIIRS) before, during and after the peak of reported wildfires in the study areas

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Summary

Background of the Study

Wildfires are unplanned fires that burn in natural areas such as forests, grasslands, or prairies. These are often caused by human activities or natural phenomena such as lightning. It is estimated that wildfire damage to forests can be as large as 6x106 hectares globally and detection and monitoring can be challenging (Mouillot et al, 2005). According to the World Health Organization, there are 6.2 million people affected by wildfires and volcanic activity between 1998-2017. This includes around 2,400 deaths due to suffocation, injuries, and burns (World Health Organization, 2021). The key in preventing such large fires that can cause severe damages to infrastructures, livelihoods and even lives, is early detection of small fires, smokes, plumes and fire in water pixels

Literature Review
Significance of the Study
STUDY AREAS
Methods
METHODOLOGY
RESULTS AND DISCUSSION
Radiative power and brightness temperature
CONCLUSIONS AND RECOMMENDATIONS
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