Sato, A, [4] R = Val Haz Vul (1) R: Val: Haz: ( ) Vul: () 0 1 / / (1) [5] [6] (preparedness) (JIS X0410)
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1 /Review 1 Disaster Risk Assessment for Resilience Improvement Aki-Hiro SATO 1 Abstract This article discusses how to assess disaster risks by using grid square statistics regarding socioeconomic data and natural hazard data. The risk is defined as multiplication among socioeconomic values, hazard, and vulnerability and depends on regions. This article shows how to create grid square data for anticipated inundation water height from polygon data provided from Ministry of Land, Infrastructure, Transport, and Tourism. Comparative analysis of seismic risk, tsunami risk, and inundation risk is considered. It is concluded that integrated analysis of natural hazard and socioeconomic values based on grid square data may enable us to improve preparedness for natural disasters in our usual life. Keywords Grid square statistics, Risk, Physical exposure, Flood, Tsunami, Earthquakes 1. [1] 3 28 (27 ) 23 1, 1 Kyoto University, JST PRESTO Received: 18 July 2017, Revised: 19 Auust 2017, Accepted: 21 August , [2] 10,000 2,000 ( 100 ) 100 [3] Oukan Vol.11, No.2 135
2 Sato, A, [4] R = Val Haz Vul (1) R: Val: Haz: ( ) Vul: () 0 1 / / (1) [5] [6] (preparedness) (JIS X0410)
3 Disaster Risk Assessment for Resilience Improvement Fig. 1: Fig. 2: 2. e-stat [7] ( ) (1) (2) (3) (4) (5) Fig , Oukan Vol.11, No.2 137
4 Sato, A, Fig. 3: e-stat Fig. 2 ( ) (m 2 ) 9 9 2, Mm 2 1,956 30Mm 2 187Mm Fig. 3 9 log 10 ( (m 2 )) = log 10 ( ( )) [8] 3 3 ( ) GIS
5 Disaster Risk Assessment for Resilience Improvement Table 1: 3 ( ) ( ) 0-0.5m 5,617 11,261, ,893 6,976, m 3,565 6,166, ,678 3,466, m 6,155 11,418, ,637 5,979, m 6,889 10,925, ,858 5,476, m 1, ,905 39, ,971 Fig. 4: 3 3 Fig Fig [9] [10] Table 1 5.0m (33.8 ) 39, m 1,092.5 (453.4 ) m % 4. 3 J-SHIS 2016 [6] [12]NOAA 2000 [13] JAXA (ALOS) 30m DEM [14] [15] 3 24 [8] 3 Fig [4] 2012 [10] (a) (b) (c) (100 1 ) km km Oukan Vol.11, No.2 139
6 Sato, A, (a) (b) Fig. 5: 24 (a) 3 (b) (a) Fig. 6:
7 Disaster Risk Assessment for Resilience Improvement (b) (c) Fig. 6: (a) 2012 (b) (c).y 3 6 x Fig. 7 [12] 2010 [9] 2012 [10] (a) (b) (c) Oukan Vol.11, No.2 141
8 Sato, A, (a) (b) Fig. 7: [16,17] [18]
9 Disaster Risk Assessment for Resilience Improvement (c) Fig. 7: (a) 2012 (b) (c) y 3 x 5. [15] : (JST) (Grant Number: JPMJPR1504; : ) Oukan Vol.11, No.2 143
![Sato, A, [1], [ONLINE] http://www. e-stat.go.jp/sg1/estat/newlist.do?tid= 000001024237, Accessed on 10 August 2017. [2], RISK, No. 64 (2002) pp. 22/25. [ONLINE] http://www.giroj.or.](/docs-images/91/104842544/images/10-0.jpg "jp/disclosure/risk/risk64-3.pdf, Accessed on 19 August 2017. [3], [ONLINE] http://disaportal.gsi.go.jp/, Accessed on 19 August 2017. [4] P. Peduzzi, H. Dao, C.Herold, and F.")
10 Sato, A, [1], [ONLINE] e-stat.go.jp/sg1/estat/newlist.do?tid= , Accessed on 10 August [2], RISK, No. 64 (2002) pp. 22/25. [ONLINE] jp/disclosure/risk/risk64-3.pdf, Accessed on 19 August [3], [ONLINE] Accessed on 19 August [4] P. Peduzzi, H. Dao, C.Herold, and F. Mouton, Assessing global exposure and vulnerability towards natural hazards: the Disaster Risk Index, Nat. Hazards Earth Syst. Sci., Vol. 9, pp. 1149/1159 (2009) [5] M.A. Konstantinidou, K.L. Kepaptsoglou, and M.G. Karlaftis, Transportation Network Post-Disaster Planning and Management: A Review Part I: Post-Disaster Transportation Network Performance, International Journal of Transportation, Vol.2, pp.1/16 (2014). [6],,, (2015) [7] ( ) [ON- LINE] GL do?gaid=GL &tocd= , Accessed on 23 August [8] ( 24 ), jp/ksj/gml/datalist/ksjtmplt-a31.html [9] , ( GIS), SG2/eStatGIS/page/download.html [10] , ( GIS), SG2/eStatGIS/page/download.html [11], J-SHIS, [12],, Tae-Seok Jang,, :,, 10 2 (2016) pp. 76/83 [13] NGDC/WDS Global Historical Tsunami Database, 2100 BC to present, [14] JAXA (ALOS) 30m DEM, http: // index.htm [15],,,, (2016) p. 5. [16] N. Hirayama, T. Shimaoka, T. Fujiwara, T. Okayama and Y. Kawata, Establishment of Disaster Debris Management Based on Quantitative Estimation Using Natural Hazard Maps, Waste Management and the Environment V, WIT Transactions on Ecology and the Environment, Vol. 140, pp. 167/178 (2010). [17] T. Tabata, Y. Wakabayashi, P. Tsai, and T. Saeki, Environmental and economic evaluation of pre-disaster plans for disaster waste management: Case study of Minami-Ise, Japan, Waste Management, Vol. 61, pp. 386/396 (2017). [18] M. Hua, T. Sayama, X. Zhang, K. Tanaka, K. Takara, H. Yang, Evaluation of low impact development approach for mitigating flood inundation at a watershed scale in China, Journal of Environmental Management, Vol. 193, pp. 430/438 (2017) ISO TC HPCI (2015 ) 4 (2015 ) Aki-Hiro Sato, Applied Data-Centric Social Sciences, Springer, Tokyo (2014),,, (2016)
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