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The large number of risk prediction indices implemented globally and the lack of a universally accepted and widely used general model for predicting fire behaviour highlight the fact that forecasting forest fires remains a complex problem. The fire phenomenon is changing because the forest environment and its interactions with the climate and society have new connotations. The fire season is increasingly longer, and extreme weather events such as heatwaves and droughts are more frequent, increasing water stress on vegetation, making it highly flammable. Fire management should consequently evolve to reflect new environmental scenarios (climate change, expansion of new forests, growth in urban populations and interface areas), implementing forest and land-use planning, including environmental education, decision support systems, and forest management. This observation leads to the awareness of the need to intensify study, analysis, and research activities and initiatives in this area.In 2017 a large event involved the Vesuvius National Park (Campania, Italy) an area rich in natural resources, historic cradle of volcanology, breathtaking landscapes, crops, and centuries-old traditions. As part of the National Program "Italian Parks for the Climate" - Year 2020 - ", an innovative monitoring system, with the purpose to support a dynamic fire probability mapping and forest fire risk management, has been shared as an operational agreement between academia and stakeholders.The project uses a combination of integrated, interdisciplinary, and interoperable modules to prepare the actions and interventions needed to prevent and reduce the risk of forest fires and the resulting hydrogeological risks (soil erosion, shallow landslides, and hyperconcentrated flows), enabling alerts and support the natural reserve operators. A "REMOTE" module, based on the analysis of small-scale space-time Sentinel data for land cover and soil moisture assessment is supported by a “TERRA” module, based on the installation, validation, expert control and interactive communication of an intelligent monitoring system for water, soil and meteorological station data, aimed at early warning of forest fires, complemented by the use of an object-oriented and environmentally focused data analysis of Tri-Stereo Neo imagery from the Pléiades imagery constellation (European Space Agency).The monitoring program, launched in 2023 and still ongoing, has provided valuable data useful for the temporal dynamics of hydrological, climatic, and land cover variables that impact fire risk. Comparisons with fire events from 2023 to 2025 are being evaluated to test the forecasting capabilities that can be derived and put in practice to mitigate the wildfire risk.