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Forest fires are one of many natural disasters which can cause huge loses and damage to the environment. When dealing with such fires, a quick response is crucial. Remote sensing methods can be very helpful in such situations. Satellite images can be a useful tool in classifying the risk of forest fires occurring. In our research we set out to categorize the risk of forest fires of a chosen area based on satellite imagery. The area of interest was located close Kuźnia Raciboska, in the vicinity of the Kędzierzyn, Rudy Raciborskie and Rudziec forest inspectorates. During the research a number of methods, used to develop a risk map of forest fires, were presented. Two methods were used in order to generate risk maps of forest fires: determining the surface temperature and calculating the NDVI from satellite images from before the fires. These operations were conducted in order to incorporate different factors which have an impact on the potential risk of fire. Determining the spatial distribution of the surface temperature, by determining the radiation temperature of the vegetation was very useful in identifying different levels of fire hazard risk. However, using only this one parameter is not sufficient as it does not incorporate plan stress caused by very low humidity (drought). Determining the spatial distribution of the forest bed, by calculating the intensity of vegetation using the NDVI algorithm, allowed for a more precise conclusion of areas which are more or less at risk of forest fires. The described methods of determining the risk of forest fires can be helpful in rapidly acquiring information about the forest’s condition as well as enabling the possibility of analysing any changes which had occurred within the forest due to such natural disasters. As a result of calculating the NDVI and radiation temperature, it as possible to obtain a fire risk map which can be useful for many purposes such as fire risk management systems. Determining the level of fire risk using satellite data is one of the most efficient methods of preventing such natural disasters from occurring.
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