Abstract
In the performance of their duties, authorities and organisations with safety and security tasks face major challenges. As a result, the need to expand the knowledge and skills of security forces in a targeted manner through knowledge, systemic and technological solutions is increasing. Of particular importance for this inhomogeneous end user group is the time factor and thus in general also space, distance, and velocity. Authorities focus on people, goods, and infrastructure in the field of prevention, protection, and rescue. For purposive tactical, strategic, and operational planning, geodata and information about past and ongoing operations dispatched and archived at control centers can be used. For that reason, a rule-based process for the geovisual evaluation of massive spatio-temporal data is developed using geoinformation methods, techniques, and technologies by the example of operational emergency data of fire brigade and rescue services. This contribution to the extension of the KDE for hotspot analysis has the goal to put the professional and managerial personnel in a position to create well-founded geoprofiles based on the spatial-temporal location, distribution, and typology of emergency mission hotspots. In doing so, significant data is generated for the neighborhood of the operations in abstract spatial segments, and is used to calculate distance measures for the Kernel Density Estimation (KDE) process. At the end there is a completely derived rule-based kde process for the geovisual analysis of massive spatio-temporal mass data for hotspot geoprofiling.
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Acknowledgements
The work presented here is part of the dissertation entitled “Konzeption und prototypische Umsetzung eines regelbasierten Prozesses zur geovisuellen Auswertung massiver raumzeitlicher Datenbestände von Feuerwehreinsätzen. Ein Beitrag zur Erweiterung der KDE für die Hotspot-Analyse im Kontext ziviler Sicherheitsforschung.” and was successfully completed at the University of Potsdam, Germany, in 2019. The support of his conference contribution by the German Aerospace Center, Institute of Optical Sensor Systems, Department Security Research and Applications is gratefully acknowledged.
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Gonschorek, J. (2020). Geoprofiling in the Context of Civil Security: KDE Process Optimisation for Hotspot Analysis of Massive Emergency Location Data. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12252. Springer, Cham. https://doi.org/10.1007/978-3-030-58811-3_42
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