Prediction of Forest Fire Danger Rating(FFDR) in DPR Korea: Modeling of MODIS Fire product, 5km-resolution meteorological data, Daily Weather Index(DWI), Fuel Model index(FMI) and Topographical Model Index(TMI) database

This study has developed a forest fire occurrence probability model for inaccessible areas such as North Korea and Demilitarized Zone and we develop a real-time forest fire danger rating system that can be used in fire-related works. There are limitations on the research that it is impossible to conduct site investigation for data acquisition and verification for forest fire occurrence probability model and system development. To solve this problem, we estimated the fire spots in the areas where access is impossible by using MODIS satellite data with scientific basis. Using the past meteorological data (5 km resolution) produced by the Korea Meteorological Administration (KMA) on the extracted fires, the meteorological characteristics of the fires were extracted and made database. The meteorological factors extracted from the forest fire ignition points in the inaccessible areas are statistically correlated with the forest fire occurrence and the weather factors and the logistic regression model that can estimate the forest fires occurrence (fires 1 and non-fores 0) And used to calculate the Daily Weather Index (DWI). In addition to DWI, the characteristics of forest type (coniferous, deciduous, mixed forest) and topography (altitude, aspect) affecting forest fires were identified and weighted by frequency analysis of the Fuel Model Index (FMI) and Topography Model Index (TMI). We developed a forest fire danger rating system that can provide real-time data and web service through forest fire danger rating index(FFDRI) model for meteorology, forest type, and terrain developed through this study.