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Geo-information for Disaster Management
Geo-information technology offers an opportunity to support disaster management: industrial accidents, road collisions, complex emergencies, earthquakes, fires, floods and similar catastrophes (for example the recent huge disaster with the Tsunami in South-East Asia on 26 December 2004). Access to needed information, facilitation of the interoperability of emergency services, and provision of high-quality care to the public are a number of the key requirements. The book provides a broad overview of the (geo-information) technology, software, systems needed, used and to be developed for disaster management. The book provokes a wide discussion on systems and requirements for use of geo-information under time and stress constraints and unfamiliar situations, environments and circumstances.
Artificial intelligence for multisource geospatial information
Collects 10 original research contributions published in the Special Issue entitled “Artificial Intelligence for Multisource Geospatial Information” of the ISPRS International Journal of Geo-Information. The focus is on different methods of Geospatial Artificial Intelligence (GeoAI) based on deep learning using different network architectures, clustering, soft computing, and semantic approaches. They are proposed to deal with a variety of Geospatial Big Data (GBD), such as georeferenced texts and photos in social networks, remote sensing images, cartographic maps, multidimensional geo databases, metadata in spatial data infrastructures, and for different tasks, such as for multisource georeferenced text integration and geodata flexible querying, for social sensing by applying sentiment analysis, clustering and geo analysis, for segmentation of roads, clouds and snow, and for detection of small targets and people on the streets.
