Forecasting method of national-level forest fire risk rating

摘要

The risk level of forest fire not only depends on weather, topography, human activities, socio-economic conditions, but isalso closely related to the types, growth, moisture content, and quantity of forest fuel on the ground. How to timelyacquire information about the growth and moisture content of forest fuel and climate for the whole country is critical tonational-level forest fire risk forecasting. The development and application of remote sensing (RS), geographicinformation system (GIS), databases, internet, and other modern information technologies has provided importanttechnical means for macro-regional forest fire risk forecasting. In this paper, quantified forecasting of national-levelforest fire risk was studied using Fuel State Index (FSI) and Background Composite Index (BCI). The FSI was estimatedusing Moderate Resolution Imaging Spectroradiaometer (MODIS) data. National meteorological data and other basicdata on distribution of fuel types and forest fire risk rating were standardized in ArcGIS platform to calculate BCI. TheFSI and the BCI were used to calculate the Forest Fire Danger Index (FFDI), which is regarded as a quantitative indicatorfor national forest fire risk forecasting and forest fire risk rating, shifting from qualitative description to quantitativeestimation. The major forest fires occurred in recent years were taken as examples to validate the above method, andresults indicated that the method can be used for quantitative forecasting of national-level forest fire risks.