Mapping of forest fire hazard depending on weather conditions using geoinformation technologies

A A Dvornik,N V Shamal,R S Kurilenko,V N Sehlin,R A Korol,A V Bardyukova,A M Dvornik

doi:10.29235/1029-8940-2021-66-3-320-332

Abstract

An important component of forest firefighting strategies is related to the accurate prediction of fire risks. This article describes the development process of special decision support system (ForestFire GIS) - for the analysis of climatic conditions and definition of fire risks in Belarus including radioactively contaminated territory. The application consists of two basic modules: fire danger rating module and module of radionuclides transfer during the fire event. Fire danger rating module uses data on daily temperature, dew point and 24-hour rainfall to calculate weather based fire hazard index (FHI). The program provides recommendations for firefighting officials about efficient wildfires suppression strategy. GIS core (based on the MapWinGIS) performs all basic operations with map layers (scaling, moving, geocoding etc.), load and save changes. The ForestFire GIS was tested for the beginning of fire seasons in Gomel region in Belarus.

Highlights

Among natural emergencies, forest fires are one of the most harmful disasters
The main output of this work is a modern tool for forest fire risk management, that could be useful in contaminated forests but for whole regions
One of the most important is the special emphasis on radiological consequences of wildland fires

Summary

Introduction

Forest fires are one of the most harmful disasters. During the last decades, vegetation fires in Eastern and Central Europe has become more common, intensive and less controllable as a consequence of land-use, social and economic changes and coupled with the impacts of global and regional climate changes [1]. Managing forest fire risks based on reliable information and forecasts on fuel loads, amount of radionuclides flowing out to the atmosphere through burning of contaminated biomass may be done using geographic information systems (GIS) and remote sensing.

Results

Conclusion