A three-dimensional geographic and storm surge data integration system for evacuation planning

Pava, Jairo; Fleites, Fausto C.; Ruan, Fang; Chatterjee, Kasturi; Chen, Shu‐Ching; Zhang, Keqi

doi:10.1109/iri.2010.5558942

Cited by 2 publications

(3 citation statements)

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“…Accounting for 90% of hurricane-related fatalities, the rise of ocean water due to a hurricane's strong winds, or storm surge, is the greatest cause of human life and property losses. Furthermore, saltwater flooding is the major origin of damage to buildings and infrastructure [Pava et al 2010a]. As a hurricane approaches a coastal area, various storm-surge models are used to predict the potential height of the storm surge in the projected rainfall area.…”

Section: D Simulation Of Disaster Impactsmentioning

confidence: 99%

“…However, for an untrained eye, it is hard to relate such two-dimensional maps to the daily threedimensional (3D) real world. Much research effort has been carried out to develop 3D storm surge visualization systems that better illustrate the disaster situation and facilitate residents to make potentially life-saving evacuation decisions [Singh et al 2005;Pava et al 2010a;. In this section, we will focus on the 3D simulation of hurricanes and storm-surge flooding.…”

Section: D Simulation Of Disaster Impactsmentioning

confidence: 99%

“…Figure 13 presents the high-level view of the architecture of a 3D storm surge simulation system ]. The data-processing layer provides the facilities to process Light Detection and Ranging (LiDAR), the Coastal and Estuarine Storm Tide (CEST) model [Pava et al 2010a;, and Digital Line Graph (DLG) data into formats that can be recognized by VTBuilder [Discoe 2002]. The output of VTBuilder is then used to construct 3D representation of terrain, buildings, and roads in the construction layer.…”

Section: D Simulation Of Disaster Impactsmentioning

confidence: 99%

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Data-Driven Techniques in Disaster Information Management

Xie

Zeng

et al. 2017

ACM Comput. Surv.

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Improving disaster management and recovery techniques is one of national priorities given the huge toll caused by man-made and nature calamities. Data-driven disaster management aims at applying advanced data collection and analysis technologies to achieve more effective and responsive disaster management, and has undergone considerable progress in the last decade. However, to the best of our knowledge, there is currently no work that both summarizes recent progress and suggests future directions for this emerging research area. To remedy this situation, we provide a systematic treatment of the recent developments in data-driven disaster management. Specifically, we first present a general overview of the requirements and system architectures of disaster management systems and then summarize state-of-the-art data-driven techniques that have been applied on improving situation awareness as well as in addressing users’ information needs in disaster management. We also discuss and categorize general data-mining and machine-learning techniques in disaster management. Finally, we recommend several research directions for further investigations.

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Section: D Simulation Of Disaster Impactsmentioning

confidence: 99%

Section: D Simulation Of Disaster Impactsmentioning

confidence: 99%

Section: D Simulation Of Disaster Impactsmentioning

confidence: 99%

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