The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVI-4/W6-2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-91-2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-91-2021
18 Nov 2021
 | 18 Nov 2021

ACCURACY ASSESSMENT OF FY-4A FIRE/HOTSPOT (FHS) PRODUCT IN WILDFIRE DETECTION

M. A. D. A. Celiz, R. R. Landero, J. A. Principe, and M. R. C. O. Ang

Keywords: Fengyun 4A, VIIRS, wildfire detection, FHS

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).