The purpose of this study is to develop air patrol schemes depending on the location of fire-prone vegetation areas based on the author's deterministic-probabilistic model for predicting the occurrence of vegetation fires based on remote Earth monitoring data. Verification of air patrol routes is performed on the example of the Jewish Autonomous Region territory.
This study describes the development of the system of short-term fire weather hazard forecast, which takes into account pyrologic data of the quarter network of fire hazardous locations, weather stations and vegetation fires over multi-year period. A deterministic and probabilistic vegetation fire occurrence model was proposed to carry operational territorial units forecasting and verified with example of 2016 fire hazardous season in the federal constituent entities of the Russian Far East.
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.