Fire Monitoring Algorithm and Its Application on the Geo-Kompsat-2A Geostationary Meteorological Satellite

Abstract

Geo-Kompsat-2A (GK-2A) is the third new-generation geostationary meteorological satellite that orbits Asia and monitors China and its surrounding areas, following the Himawari-8 and Fengyun-4A satellites. The nadir point positioning and satellite channel parameters of the GK-2A are better than those of the Himawari-8 and FY-4A, which are more conducive to fire monitoring in China. In this study, a new fire detection algorithm is proposed based on GK-2A satellite data. That is, considering the large solar zenith angle correction for reflectance and the proportion information of background pixels in the existing spatial threshold method, fires under the different underlying surface types and solar radiation states can be automatically identified. Moreover, the accuracy of the Himawari-8 fire monitoring algorithm and the present algorithm of GK-2A is compared and analyzed through the ground truth fire spot data. The results show that compared with the original fire monitoring algorithm with fixed parameter thresholds, the brightness temperature difference of this algorithm is reduced by 0.55 K, and the correction coefficient is reduced by 0.6 times, the fire can be found earlier, and the monitoring sensitivity is improved. According to the practical fire case, the present fire monitoring algorithm of GK-2A has better monitoring accuracy than the fire monitoring algorithm of Himawari-8. The present fire monitoring algorithm of GK-2A can meet the fire monitoring requirements under different sun angles, different cloud cover ratios and vegetation ratios with good versatility.

Remote Sensing and GIS Applications in Wildfires

“…Smaller and cooler fires have proven difficult to detect in global active fire datasets and by geostationary sensors [132,140]. Probably, in the near future, geostationary satellites with higher spatial resolutions may become available, allowing for near real-time detection and monitoring of small/cool fires, already new generation satellites for forest and grassland fire detection have been launched such as the Himawari-8 launched by Japan, GOES-R/S/T by the United States and Geo-Kompsat-2A (GK-2A) by South Korea, compared with the previous satellites, and these new-generation geostationary meteorological satellites have been improved in spatial resolution and observation frequency [276]. UAVs equipped with infrared or thermal or RGB cameras can be used where data can provide live feeds and be used to predict information such as propagation of a fire [277].…”

Hydrodynamic Characteristics and Pollutant Transport in Rivers and Nearshore Environments

“…According to the study by Chen et al (2022), the portion of remote sensing reflectance (Rrs) corresponding to solar zenith angle (SOZ) less than 60 °is considered as valid data. A correction is applied to the Rrs of bands 1 to 6 using Eq.…”

Near real-time retrieval of lake surface water temperature using Himawari-8 satellite imagery and machine learning techniques: a case study in the Yangtze River Basin

“…Atmospheric corrections was employed for the H8 satellite using the Py6s model (Niu et al, 2019). Based on the findings of Chen et al (2022), atmospheric correction is applied to the Remote Sensing Reflectance (R rs ) data for Solar Zenith Angles (SOZ) less than 60 °, assuming them as valid data. According to Ge et al (2018), all the image elements within the window are determined to be cloud image elements and considered as invalid data when R rst ' ≥ 0.25 (Eq.…”