Climate changes and their negative effects on the environment and society are now well known, also due to the increasingly frequent news episodes reporting the occurrence of extreme events with disastrous consequences in economic terms and in terms of human lives. Fires have and will have a major impact on agricultural resources and urban settlements, with critical consequences for the safety and health of citizens, the safeguarding of economic assets and the provision of essential services from fire-damaged ecosystems. Nowadays, satellite monitoring platforms are largely diffused. Therefore, environmental data start to be broadly available. This very preliminary work aims at proposing an effective workflow for wildfire prevention using the leaf area index (LAI) as precursor. By looking at the time evolution of three indices (mean Green, NDV and LAI) on an area interested by wildfire, we show that LAI has maximum before the fire and can be used as an indicator in defining a fire-risk category map. Though many more data is necessary to validate the method and ground truth LAI is lacking, the workflow presented could be the first step of an effective towards a fire-prevention system aiming at reducing the reaction time of safeguards and fire-damage.