Road network risk analysis considering people flow under ordinary and evacuation situations/ (Record no. 14659)

MARC details
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fixed length control field 02753nab a2200205 4500
005 - DATE & TIME
control field 20230914153711.0
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100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Sasabe, Masahiro
245 ## - TITLE STATEMENT
Title Road network risk analysis considering people flow under ordinary and evacuation situations/
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Sage,
Date of publication, distribution, etc 2020.
300 ## - PHYSICAL DESCRIPTION
Pages Vol. 47, Issue 5, 2020, ( 759–774 p.)
520 ## - SUMMARY, ETC.
Summary, etc Both pre-disaster approaches, e.g., mitigation and preparedness, and post-disaster approaches, e.g., response and recovery, play important roles to mitigate the damage from large-scale disasters. From the viewpoint of disaster response, there have been studies on evacuation guiding schemes and applications using evacuees’ mobile devices, e.g., smart phones. On the other hand, disaster preparedness has also been studied mainly on geographical information analysis, e.g., road blockage probability and people flow data. The road blockage probability is the probability that the corresponding road is blocked due to collapse of roadside buildings when an earthquake occurs. The people flow data express the people flow in usual time. In this paper, with the help of evacuation guiding schemes, road blockage probability, and people flow data, we propose a road network risk analysis approach that considers people flow in both ordinary and evacuation situations, which can be used to as a tool to strengthen the urban fabric for fostering better evacuees’ responses in disaster situations. First, the proposed approach derives ordinary road demand, which is the degree of road usage at a certain interval in an ordinary situation, from the people flow data. Then, it calculates evacuation road demand, i.e., the degree of road usage at a certain interval in an evacuation situation, by extending the edge betweenness centrality under the assumption that people located according to the ordinary road demand move to refuges along their evacuation paths. Finally, it detects roads with high risk of encountering blocked road segments by combining the road blockage probability and evacuation road demand. Through numerical experiments under a case study of Arako area of Nagoya city in Japan, we show the proposed approach can detect such high-risk roads. Furthermore, we show the detected roads spatially change according to the people flow in ordinary situations, evacuation behavior, and disaster occurrence time.
700 ## - Added Entry Personal Name
Added Entry Personal Name Fujii, Kodai
700 ## - Added Entry Personal Name
Added Entry Personal Name Kasahara, Shoji
773 0# - HOST ITEM ENTRY
Host Biblionumber 8876
Host Itemnumber 17104
Place, publisher, and date of publication London Pion Ltd. 2010
Title Environment and planning B: planning and design (Urban Analytics and City Science)
International Standard Serial Number 1472-3417
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1177/2399808318802940
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type E-Journal
100 ## - MAIN ENTRY--PERSONAL NAME
-- 57897
700 ## - Added Entry Personal Name
-- 57898
700 ## - Added Entry Personal Name
-- 57899
942 ## - ADDED ENTRY ELEMENTS (KOHA)
-- ddc

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