Wildfires of high severity can have profound implications on natural and human environment affecting the quality of life; the health of living beings; and the prosperity of any society. Consequently, specific strategies, tactics and techniques should always be adopted for the alleviation of this critical phenomenon. Hence, the aim of the paper is the review of the most common geoinformatics-based techniques contributing to an integrated fire analysis through four pillars. The first one is related with the fire exposure on the ground, primarily analyzing the fire susceptibility in terms of fire risk and burn probability maps; The second one examines the fire effects on the most critical ecological and anthropogenic resources and infrastructures. The third pillar combines two effective geospatial tools supporting the wildfire prevention and suppression, such as the visibility analysis for early detection of fire hotspots and the network analysis for strategic and operational planning of fire events. Last, the Earth-Observation module, through the spatiotemporal monitoring and prediction of land use changes, permits the planners to evaluate the underlying pressures (fires, urbanization) against forests developing the appropriate planning guidelines. In the meantime, new perspectives emerge. Novel machine learning algorithms and remote sensing data techniques are expected to improve the fire risk/probability credibility enhancing the more precise identification of fire effects to any resource. The integration of specific geographic criteria (e.g. topography, accessibility) and programming techniques (e.g. maximizing the visible area) to visibility analysis would empower the immediate fire detection. New technologies such as the adoption of drones would be a cost-effective tool for quick retrieval of vital geo-data. Network analysis could propose financially and environmentally efficient location schemes of fire agencies and resources.