Damage Estimation of Explosions in Urban Environments by Simulation

Ludwig Mohr, R Benauer, Peter A. Leitl, Friedrich Fraundorfer

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Precise models of the impact of explosions in urban environments provide novel and valuable information in disaster management for developing precautionary, preventive and mitigating measures. Yet to date, no methods enabling accurate predictions of the process and effect of detonations at particular locations exist. We propose a novel approach mitigating this gap by combining state-of-the-art methods from photogrammetric 3D reconstruction, semantic segmentation and computational based numerical simulations. In a first step, we create an accurate urban 3D reconstruction from georeferenced aerial images. The resulting city model is then enriched with semantic information obtained from the original source images as well as from registered terrestrial images using deep neural networks. This allows for an efficient automatic preparation of a 3D model suitable for the use as a geometry for the numerical …
Original languageEnglish
Pages (from-to)253-260
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Publication statusPublished - 2019

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Explosions
Semantics
Detonation
Disasters
Antennas
Geometry
Computer simulation
Deep neural networks

Cite this

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title = "Damage Estimation of Explosions in Urban Environments by Simulation",
abstract = "Precise models of the impact of explosions in urban environments provide novel and valuable information in disaster management for developing precautionary, preventive and mitigating measures. Yet to date, no methods enabling accurate predictions of the process and effect of detonations at particular locations exist. We propose a novel approach mitigating this gap by combining state-of-the-art methods from photogrammetric 3D reconstruction, semantic segmentation and computational based numerical simulations. In a first step, we create an accurate urban 3D reconstruction from georeferenced aerial images. The resulting city model is then enriched with semantic information obtained from the original source images as well as from registered terrestrial images using deep neural networks. This allows for an efficient automatic preparation of a 3D model suitable for the use as a geometry for the numerical …",
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AB - Precise models of the impact of explosions in urban environments provide novel and valuable information in disaster management for developing precautionary, preventive and mitigating measures. Yet to date, no methods enabling accurate predictions of the process and effect of detonations at particular locations exist. We propose a novel approach mitigating this gap by combining state-of-the-art methods from photogrammetric 3D reconstruction, semantic segmentation and computational based numerical simulations. In a first step, we create an accurate urban 3D reconstruction from georeferenced aerial images. The resulting city model is then enriched with semantic information obtained from the original source images as well as from registered terrestrial images using deep neural networks. This allows for an efficient automatic preparation of a 3D model suitable for the use as a geometry for the numerical …

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