ANALYSIS OF HUMAN CASUALTY USING INUNDATION DEPTH AND BUILDING DAMAGE RATIO IN CASE OF THE 2011 TOHOKU TSUNAMI IN ISHINOMAKI CITY

Abstract. Run-up processes of the 2011 Tohoku tsunami into the city of Kamaishi, Japan, were simulated numerically using 2-D shallow water equations with a new treatment of building footprints. The model imposes an internal hydraulic condition of permeable and impermeable walls at the building footprint outline on unstructured triangular meshes. Digital data of the building footprint approximated by polygons were overlaid on a 1.0 m resolution terrain model. The hydraulic boundary conditions were ascertained using conventional tsunami propagation calculation from the seismic center to nearshore areas. Run-up flow calculations were conducted under the same hydraulic conditions for several cases having different building permeabilities. Comparison of computation results with field data suggests that the case with a small amount of wall permeability gives better agreement than the case with impermeable condition. Spatial mapping of an indicator for run-up flow intensity (IF = (hU2)max, where h and U respectively denote the inundation depth and flow velocity during the flood, shows fairly good correlation with the distribution of houses destroyed by flooding. As a possible mitigation measure, the influence of the buildings on the flow was assessed using a numerical experiment for solid buildings arrayed alternately in two lines along the coast. Results show that the buildings can prevent seawater from flowing straight to the city center while maintaining access to the sea.

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PROPOSING AN ESTIMATION METHOD FOR BUILDING DAMAGE AND HUMAN CASUALTY BASED ON DETAIL DAMAGE DATA OF THE 2011 TOHOKU TSUNAMI

Journal of Japan Society of Civil Engineers Ser B2 (Coastal Engineering) ◽

10.2208/kaigan.76.2_i_1291 ◽

2020 ◽

Vol 76 (2) ◽

pp. I_1291-I_1296

Author(s):

Natsuki HASEGAWA ◽

Anawat SUPPASRI ◽

Fumihiko IMAMURA

Keyword(s):

Estimation Method ◽

Building Damage ◽

2011 Tohoku Tsunami ◽

Damage Data ◽

Tohoku Tsunami

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SEDIMENT MOVEMENT AT THE KITAKAMI RIVER MOUTH AFTER THE 2011 TOHOKU TSUNAMI AND ITS MODELING

Journal of Japan Society of Civil Engineers Ser B2 (Coastal Engineering) ◽

10.2208/kaigan.76.2_i_625 ◽

2020 ◽

Vol 76 (2) ◽

pp. I_625-I_630

Author(s):

Nguyen Trong HIEP ◽

Hitoshi TANAKA ◽

Nguyen Xuan TINH

Keyword(s):

River Mouth ◽

Sediment Movement ◽

2011 Tohoku Tsunami ◽

Tohoku Tsunami

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The 2011 Tohoku Tsunami from the Sky: A Review on the Evolution of Artificial Intelligence Methods for Damage Assessment

Geosciences ◽

10.3390/geosciences11030133 ◽

2021 ◽

Vol 11 (3) ◽

pp. 133

Author(s):

Jérémie Sublime

Keyword(s):

Artificial Intelligence ◽

Case Studies ◽

Damage Assessment ◽

Structural Damage ◽

North East ◽

2011 Tohoku Tsunami ◽

Artificial Intelligence Methods ◽

The Future ◽

Tohoku Tsunami

The Tohoku tsunami was a devastating event that struck North-East Japan in 2011 and remained in the memory of people worldwide. The amount of devastation was so great that it took years to achieve a proper assessment of the economical and structural damage, with the consequences still being felt today. However, this tsunami was also one of the first observed from the sky by modern satellites and aircrafts, thus providing a unique opportunity to exploit these data and train artificial intelligence methods that could help to better handle the aftermath of similar disasters in the future. This paper provides a review of how artificial intelligence methods applied to case studies about the Tohoku tsunami have evolved since 2011. We focus on more than 15 studies that are compared and evaluated in terms of the data they require, the methods used, their degree of automation, their metric performances, and their strengths and weaknesses.

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Building Damage Detection Based on OPCE Matching Algorithm Using a Single Post-Event PolSAR Data

Remote Sensing ◽

10.3390/rs13061146 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1146

Author(s):

Yuliang Nie ◽

Qiming Zeng ◽

Haizhen Zhang ◽

Qing Wang

Keyword(s):

Damage Detection ◽

Texture Features ◽

Classification Performance ◽

Building Damage ◽

Alos Palsar ◽

Yushu Earthquake ◽

Matching Algorithm ◽

2011 Tohoku Tsunami ◽

Collapsed Buildings ◽

Study Sites

Synthetic aperture radar (SAR) is an effective tool in detecting building damage. At present, more and more studies detect building damage using a single post-event fully polarimetric SAR (PolSAR) image, because it permits faster and more convenient damage detection work. However, the existence of non-buildings and obliquely-oriented buildings in disaster areas presents a challenge for obtaining accurate detection results using only post-event PolSAR data. To solve these problems, a new method is proposed in this work to detect completely collapsed buildings using a single post-event full polarization SAR image. The proposed method makes two improvements to building damage detection. First, it provides a more effective solution for non-building area removal in post-event PolSAR images. By selecting and combining three competitive polarization features, the proposed solution can remove most non-building areas effectively, including mountain vegetation and farmland areas, which are easily confused with collapsed buildings. Second, it significantly improves the classification performance of collapsed and standing buildings. A new polarization feature was created specifically for the classification of obliquely-oriented and collapsed buildings via development of the optimization of polarimetric contrast enhancement (OPCE) matching algorithm. Using this developed feature combined with texture features, the proposed method effectively distinguished collapsed and obliquely-oriented buildings, while simultaneously also identifying the affected collapsed buildings in error-prone areas. Experiments were implemented on three PolSAR datasets obtained in fully polarimetric mode: Radarsat-2 PolSAR data from the 2010 Yushu earthquake in China (resolution: 12 m, scale of the study area: ); ALOS PALSAR PolSAR data from the 2011 Tohoku tsunami in Japan (resolution: 23.14 m, scale of the study area: ); and ALOS-2 PolSAR data from the 2016 Kumamoto earthquake in Japan (resolution: 5.1 m, scale of the study area: ). Through the experiments, the proposed method was proven to obtain more than 90% accuracy for built-up area extraction in post-event PolSAR data. The achieved detection accuracies of building damage were 82.3%, 97.4%, and 78.5% in Yushu, Ishinomaki, and Mashiki town study sites, respectively.

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