Analysis of forest potential fire environment based on GIS and RS
Forest fires cause a significant damage for public property by destroying a large tract of forest. Forest fire risk assessment, which based on an integrated index, becomes an important tool for forest fires management. The integrated index includes the information about fuel, topography and weather condition which constitute potential fire environment together. The fuel and weather condition are essential for forest fire occurrence, so the main potential fire environment parameters in the process of the forest fire risk assessment are temperature, fuel moisture content and vegetation status. The environment parameters data for traditional forest fire risk assessment were always obtained from the weather station, but these data are kind of point data. We must interpolate these point data into two-dimension continuous data, but existing interpolating methods produce larger error which we cannot accept if the number of the weather stations is very sparse in study area. Otherwise, not only the current environment status affects the assessment result but the cumulative effect of potential fire environment over longer period before fire event also contributes to the current potential fire environment, which has not been discussed in detail. RS and GIS technology, which can provide time series of continuous data and advanced data processing methods, becomes a viable avenue for providing accurate potential fire environment parameters data for forest fire risk assessment. In this paper, Land Surface Temperature (LST), Fuel Moisture Content (FMC) and Normalized Difference Vegetation Index (NDVI) were used to indicate the potential fire environment. We analyzed the cumulative effect of potential fire environment over one-month period before each of the typical historical forest fires occurrence from the year of 2000 to 2006. The analysis showed that the cumulative effect of the potential fire environment plays positive role on the fire occurrence, especially the cumulative effect of LST. 73% of the Accumulated Land Surface Temperature Departure (ALSTD) is plus over one-month period. Therefore, the variation character of potential fire environment parameters before forest fire occurrence will provide much useful reference information for forest fire risk assessment.