In recent years, the Alps and other mountain regions in Europe have been increasingly affected by forest fires. Forest fires pose a major threat to the protective function of mountain forests and the provision of ecosystem services for the economy, tourism and society. The current forecasting tools for estimating the danger of forest fires often have a too coarse resolution, are based exclusively on weather information and do not take into account the actual surface moisture and vegetation conditions of forests. The CONFIRM project aims to integrate high-resolution Copernicus Sentinel 1 and 2 observational data of surface moisture and vegetation conditions with LiDAR data, predictions of current weather conditions, socio-economic information, topographic data and a forest fire database to develop a novel, high-resolution and satellite-based integrated forest fire hazard system (IFDS) for Austria and neighbouring regions. The aim is to use novel remote sensing methods and state-of-the-art machine learning methods to develop daily analyses and forecasts of the ignitability and propagation risk of forest fires according to the requirements of meteorologists, fire brigades, forest specialists and infrastructure providers.