The purpose of this study is to develop an algorithm for a 10-day fire weather forecast on the basis of the Global Forecast System, a global weather forecast model, and implement it in the proprietary-design information system for forecasting vegetation fire hazard by natural and anthropogenic conditions through the example of the Russian Far East. A relational weather database was designed to store and access the data of the National Centers for Environmental Prediction and the system metadata were integrated to the database.
The purpose of this study is the use of remote sensing data on vegetative index NDVI (Normalized Difference Vegetation Index) for predicting the spread of grassfires in the example of the Jewish Autonomous Region (JAR). Calculation of specific daily indicators of climatic-caused fire hazard is carried out according to the method of V.G. Nesterov. To calculate the spread speed of the grassfire, the MacArthur method for meadow areas was used. Pictures of the MOD09GQK product in the red and near infrared channels were used to calculate the vegetative index NDVI, which is a quantitative index of photosynthetically active biomass.