Recently, frequency and strength of global wildfire are on the increase. The wildfire encourages the climate change through release of GHGs into the atmosphere over one time occur. The effect of wildfire GHGs can be estimate by FRP(fire radiative power), many research using the remote sensing are trying for its efficient produce. A satellite fire product including fire mask and FRP was produced by polar orbit satellite at first, thereafter it was expanded to geostationary satellites for continuous monitoring of wide areas. However, geostationary satellites observing in East Asia no got a standard to produce the fire product yet. This paper described a retrieval of FRP using the COMS(Communication, Ocean and Meteorological satellite) that is a Korean geostationary satellite. The COMS FRP was retrieved MIR(Middle infrared) radiance method which approaches by brightness temperature of single waveband. Our test was presented that large scale wildfires(FRP > 300MW and confidence level > 9) occurred in the each April. The COMS FRP showed MAE = 103.67 MW(16%) with the MODIS. This result represents much as possibility of the FRP in East Asia. This paper is expected to provide to baseline for the FRP in East Asia, and apply to biomass loss and estimate the GHGs. In addition, the COMS FRP will contribute to studies of aerosols, economic losses and ecosystem damages as basic data.
The forest fires do much damage to our life in ecological and economic aspects. South Korea is probably more liable to suffer from the forest fire because mountain area occupies more than half of land in South Korea. They have recently launched the COMS(Communication Ocean and Meteorological Satellite) which is a geostationary satellite. In this paper, we developed forest fire detection algorithm using COMS data. Generally, forest fire detection algorithm uses characteristics of 4 and 11 micrometer brightness temperature. Our algorithm additionally uses LST(Land Surface Temperature). We confirmed the result of our fire detection algorithm using statistical data of Korea Forest Service and ASTER(Advanced Spaceborne Thermal Emission and Reflection Radiometer) images. We used the data in South Korea On April 1 and 2, 2011 because there are small and big forest fires at that time. The detection rate was 80% in terms of the frequency of the forest fires and was 99% in terms of the damaged area. Considering the number of COMS’s channels and its low resolution, this result is a remarkable outcome. To provide users with the result of our algorithm, we developed a smartphone application for users JSP(Java Server Page). This application can work regardless of the smartphone’s operating system. This study can be unsuitable for other areas and days because we used just two days data. To improve the accuracy of our algorithm, we need analysis using long-term data as future work.
Global warming induced by greenhouse gases is increasing wildfire frequencies and scale. Since wildfire again releases greenhouse gases(GHGs) into the air, the vicious cycle is repeated. Satellite remote sensing is a useful tool for detecting wildfire. However, estimating the GHGs emission from wildfire has not been challenged yet. Wildfires are estimated to be responsible for, on average, around 30% of global total CO emissions, 10% of methane emissions, 38% of tropospheric ozone, and over 86% of black carbon. So we need to quantify the emitted gases by biomass combustions, which can be measured by the FRP (fire radiative power) derived from the spectral characteristics of satellite sensors. This paper described the algorithm for retrieval of FRP using COMS(Communication, Ocean and Meteorological Satellite), the Korean geostationary meteorological satellite. The FRP of wildfire is retrieved by single waveband methods suitable to COMS channels. The retrieval of FRP is dependent on the emissivity of each bandwidth. So, we used MODIS NDVI through a spatio-temporal calibration for the emissivity calculations. We made sure that the FRP in wildfire pixel is much higher than its spatially and temporally neighboring pixels. For future work, we should quantify the relationships between FRP and the biomass combustion according to fuel types.
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