In South Korea, where 64% of the country''s land is forest, forest fires are one of the disasters that cause huge damage to ecology, economy and society. In order to prevent and minimize the damage caused by forest fires, the fire risk index is introduced, which is an index expressing the occurrence of forest fires by using factors such as weather, topography.
In this study, the fire risk index is calculated in South Korea using the satellite and ground observation data for 15 years from 2000 to 2014, and the fire risk is compared with the selected forest fires. The comparison of pre - and post - forest fire occurrence and spatial distribution were used to find out the forest fire risk index which is closely related to forest fire in South Korea. The Daily Weather Index (DWI), Angstrom Index (I), Nesterov Index (NI), and Modified Nesterov Index (MNI) were selected for the forest fire risk index based on the ground observation. Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Drought Index (NDDI), Normalized Multi-band Drought Index (NMDI), and Temperature Vegetation Dryness Index (TVDI) were selected for the forest fire risk index based on the satellite observation.
I, NI, and MNI among the forest fire risk indexes based on the ground observation were calculated to be lower than those in the forest fire cases where the damage was large. I, NI, and MNI are empirically derived from outside the country. Therefore, it is necessary to adjust the classification of the risk of forest fires in order to apply to South Korea. On the other hand, DWI developed in South Korea is more sensitive to the expression of fire risk. The satellite - based index showed more detailed spatial distribution than the ground - based index. Especially, TVDI is sensitive to the expression of fire risk in South Korea in terms of temporal change and spatial distribution before and after forest fires. In addition, NMDI and NDDI showed difficulty in expressing forest fires. NDVI and NDWI were suitable for forest fire detection and damage analysis rather than expression of forest fire risk.