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Road Centerline Data Accumulation for Rescue Workers Whose Expertise Is Not GIS

Published online by Cambridge University Press:  20 August 2020

Kanetoshi Hattori ,
Ritsuko Hattori ,
Hiromi Taneichi ,
Chiaki Funada ,
Junko Ouchi ,
Hitomi Watanabe  and
Eriko Tane
Kanetoshi Hattori*
Affiliation:
Naragakuen University, Department of Health Science, Nara City, Japan
Ritsuko Hattori
Affiliation:
Naragakuen University, Department of Health Science, Nara City, Japan
Hiromi Taneichi
Affiliation:
Tohto University, Faculty of Makuhari Human Care, Chiba City, Japan
Chiaki Funada
Affiliation:
Nagoya University, School of Medicine Hospital, Medical IT Center, Nagoya City, Japan
Junko Ouchi
Affiliation:
Hokkaido University of Science, Faculty of Health Science, Department of Nursing, Sapporo City, Japan
Hitomi Watanabe
Affiliation:
Tottori University, School of Medicine Hospital, Yonago City, Japan
Eriko Tane
Affiliation:
Oita University of Nursing and Health Science, Graduate School of Nursing, Midwifery Course, Oita City, Japan
*
Correspondence and reprint requests to Kanetoshi Hattori, 6-2-804 Chagasaki, Ohtsu City, Shiga Prefecture, Japan520-0023 (e-mail: hattorik@mx6.mesh.ne.jp).
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Abstract

Objectives:

The objective of this study is to provide road centerline data for professionals of disaster medicine areas who are often beginners in GIS use.

Methods:

Newly developed vector tile format data were converted into shapefile format data, then were organized as second level medical districts to which medical professionals are accustomed.

Results:

Road centerline data in Japan is being prepared to release from Association for Promotion of Infrastructure Geospatial Information Distribution free of charge.

Conclusion:

Professionals of disaster medicine areas increased their accessibility of GIS. Logistic planning for evacuation activities and dispatching of rescue teams were improved.

Keywords

ambulance transportcenterline datadisaster evacuationGISoperation routeroad rescue
Type
Original Research
Information
Disaster Medicine and Public Health Preparedness , Volume 16 , Issue 1 , February 2022 , pp. 109 - 115
Copyright
Copyright © 2020 Society for Disaster Medicine and Public Health, Inc.

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References

REFERENCES

Kuroshio-cho. High school students summit on “World Tsunami Awareness Day” in Kuroshio. 2016. https://www.town.kuroshio.lg.jp/pb/cont/summit-japanese/6023. Text in Japanese. Accessed February 10, 2020.Google Scholar
Kochi Prefecture. Portal site to prepare Nankai Trough earthquake. 2014. http://www.pref.kochi.lg.jp/sonae-portal/earthquake/tokucho.html#page1. Text in Japanese. Accessed August 8, 2019.Google Scholar
Wakayama Prefecture. On earthquake and tsunami countermeasures of Wakayama Prefecture. 2017. http://www.bousai.go.jp/jishin/nankai/taio_wg/pdf/h290131shiryo2-3.pdf. Text in Japanese. Accessed August 8, 2019.Google Scholar
Ministry of Land, Infrastructure, Transport and Tourism. Emergency transport routes. 2019. http://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-N10-v1_1.html. Text in Japanese. Accessed August 8, 2019.Google Scholar
Ministry of Land, Infrastructure, Transport and Tourism. Web map of road information for disaster prevention. 2015. http://www.mlit.go.jp/road/bosai/doro_bosaijoho_webmap/index.html. Text in Japanese. Accessed August 8, 2019.Google Scholar
Shimura, Y, Yamamoto, K. Method of searching for earthquake disaster evacuation routes using multi-objective GA and GIS. J Geogr Inf Syst. 2014;06(05):492–525. https://www.scirp.org/html/7-8401394_50474.htm. Accessed February 10, 2020.Google Scholar
Wang, J, Qin, Q, Zhao, J, et al. A knowledge-based method for road damage detection using high-resolution remote sensing image. In: IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, 2015:3564-3567. https://ieeexplore.ieee.org/document/7326591. Accessed February 22, 2020.Google Scholar
Geospatial Information Authority of Japan. Provision experiment of vector tile of map data (road centerline). 2015. https://github.com/gsi-cyberjapan/experimental_rdcl. Text in Japanese. Accessed January 3, 2019.Google Scholar
National Institute of Land and Infrastructure Management. Road Alignment Data Exchange Standard (Proposal) Ver. 1.1. 2013. http://www.nilim.go.jp/lab/qbg/bunya/cals/pdf/roadcenter1.1.pdf#search=%27%E9%81%93%E8%B7%AF%E4%B8%AD%E5%BF%83%E7%B7%9A%E5%BD%A2%E3%83%87%E3%83%BC%E3%82%BF%E4%BA%A4%E6%8F%9B%E6%A8%99%E6%BA%96%EF%BC%88%E6%A1%88%EF%BC%89%E5%9F%BA%E6%9C%AC%E9%81%93%E8%B7%AF%E4%B8%AD%E5%BF%83%E7%B7%9A%E5%BD%A2%E7%B7%A8+Ver1.1%27. Text in Japanese. Accessed February 10, 2020.Google Scholar
Chiaradia, EA. Geopaparazzi. 2015. https://plugins.qgis.org/plugins/ExportGeopaparazzi/. Accessed April 10, 2019.Google Scholar
QGIS Development Team. QGIS 3.4.4 Madeira. 2018. https://qgis.org/ja/site/. Text in Japanese. Accessed March 10, 2019.Google Scholar
ESRI. ESRI Shapefile technical description, an ESRI white paper – July 1998. 1998. https://www.esri.com/library/whitepapers/pdfs/shapefile.pdf. Accessed July 1, 2019.Google Scholar
Central Disaster Prevention Council. Plan regarding concrete activity contents based on guideline of Tohkai-Tohnankai mega earthquake emergency measure. 2009. http://www.bousai.go.jp/jishin/tonankai_nankai/pdf/tonankaihonbun.pdf. Text in Japanese. Accessed November 19, 2019.Google Scholar
Ministry of Health, Welfare and Labor. Current situation of Second Medical care area. 2016. https://www.mhlw.go.jp/file/05-Shingikai-10801000-Iseikyoku-Soumuka/0000058300.pdf. Text in Japanese. Accessed August 8, 2019.Google Scholar
Ministry of Health, Labor and Welfare. A list of disaster base hospitals. 2015. https://www.mhlw.go.jp/seisakunitsuite/bunya/kenkou_iryou/iryou/saigai_iryou/dl/saigai_iryou07.pdf. Text in Japanese. Accessed February 10, 2020.Google Scholar
National Land Numerical Information Download Service. Second Medical care areas. 2014. http://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-A38.html. Text in Japanese. Accessed August 8, 2019.Google Scholar
Kochi Prefecture. Prediction of tsunami water exposure by Nankai Trough mega-earthquake. 2012. https://www.town.kuroshio.lg.jp/pb/cont/jouhoubousai-nankai/45. Text in Japanese. Accessed August 8, 2019.Google Scholar
Association for Promotion of Infrastructure Geospatial Information Distribution. G Spatial Information Center. 2016. https://www.geospatial.jp/gp_front/. Text in Japanese. Accessed February 23, 2020.Google Scholar
Hattori, R, Miyagawa, S, Hattori, K. Estimation of pregnant women possibly left behind in 3 tsunami predicted areas of Nagoya City: a simulation 4 for rescue planning. Disaster Med Public Health Prep. 2020;epub:1-8.Google Scholar
Hattori, K. QGIS textbook for nursing professionals, preliminary version. Text in Japanese. Author; 2019.Google Scholar
Google. QField for QGIS. 2019. https://play.google.com/store/apps/details?id=ch.opengis.qfield&hl=ja. Text in Japanese. Accessed February 10, 2020.Google Scholar
ESRI. ArcGIS online. 2020. https://www.esrij.com/products/arcgis/arcgis-capabilities/apps/#field. Text in Japanese. Accessed February 25, 2020.Google Scholar