EGU2020-13143
https://doi.org/10.5194/egusphere-egu2020-13143
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Application of Grassland Fire Monitoring Based on Himawari-8 Geostationary Meteorological Satellite Data

jie chen and wei zheng
jie chen and wei zheng
  • National Satellite Meteorological Center, Remote Sensing Application, China (chenjie@cma.gov.cn)

Himawari-8 is the next-generation geostationary meteorological satellite, which is developed by JMA and was been launched in October,2014. As the successor to the MTSAT series,Its spatial resolution, observation frequency and position accuracy are much better than the last generation, so it has large advantage in grassland fire monitoring. In this paper, we presentthe method of fire monitoring self-adaptive threshold based on Himawari-8 data, and takean example of using Himawari-8 data to monitor dynamically the grassland fire located near the border of China in April of 2016. The monitoring results show that the fire lasted about 22 hours, the size of burned area were large than 1500 km2, the longest duration of a fire pixel was about 6 hours. Through analyzing a series fire information from successive  Himawari-8 10 minutes frequency observation,the result shows that the expanding speed of the fire is 5.4 km in the direction from west to east during some duration, which is up to the extent of fast speed fire type,. Using this method, analyzed the dynamic monitoring in the next day and other scattered fire point in different areas, which indicate that this method is universality in fire monitoring and Himawari-8 can be well used to monitor the fire dynamically changing, get the location, area and temperature of the fire, evaluate the expanding speed, estimate the trends of fire development and raise the ability of grass land fire monitoring and early warning.

How to cite: chen, J. and zheng, W.: Application of Grassland Fire Monitoring Based on Himawari-8 Geostationary Meteorological Satellite Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13143, https://doi.org/10.5194/egusphere-egu2020-13143, 2020