We describe a Web-GIS wildfire prevention and management platform (AEGIS) developed as an integrated and easy-to-use decision support tool to manage wildland fire hazards in Greece (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing online access to information that is essential for wildfire management. The system uses a number of spatial and non-spatial data sources to support key system functionalities. Land use/land cover maps were produced by combining field inventory data with high-resolution multispectral satellite images (RapidEye). These data support wildfire simulation tools that allow the users to examine potential fire behavior and hazard with the Minimum Travel Time fire spread algorithm. End-users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations, i.e., single-fire propagation, point-scale calculation of potential fire behavior, and burn probability analysis, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANNs) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps are used to generate integrated output map of fire hazard prediction. The system also incorporates weather information obtained from remote automatic weather stations and weather forecast maps. The system and associated computation algorithms leverage parallel processing techniques (i.e., High Performance Computing and Cloud Computing) that ensure computational power required for real-time application. All AEGIS functionalities are accessible to authorized end-users through a web-based graphical user interface. An innovative smartphone application, AEGIS App, also provides mobile access to the web-based version of the system.

With the proliferation of the geospatial technologies on the Internet, the role of geo-portals (i.e. gateways to Spatial Data Infrastructures) in the area of wildfires management emerges. However, keyword-based techniques often frustrate users when looking for data of interest in geo-portal environments, while little attention has been paid to shift from the conventional keyword-based to navigation-based mechanisms. The presented OntoFire system is an ontology-based geo-portal about wildfires. Through the proposed navigation mechanisms, the relationships between the data can be discovered, which would otherwise not be possible when using conventional querying techniques alone. End users can use the browsing interface to find resources of interest by using the navigation mechanisms provided. Data providers can use the publishing interface to submit new metadata, modify metadata or removing metadata in/from the catalogue. The proposed approach can improve the discovery of valuable information that is necessary to set priorities for disaster mitigation and prevention strategies. OntoFire aspires to be a focal point of integration and management of a very large amount of information, contributing in this way to the dissemination of knowledge and to the preparedness of the operational stakeholders.