Naresh N Spatial Modelling Group RMS India Pvt. Ltd., Noida February 8, 2012 Damage loss estimation of the 2011 Japan tsunami: A case study Co-authors.

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Naresh N Spatial Modelling Group RMS India Pvt. Ltd., Noida February 8, 2012 Damage loss estimation of the 2011 Japan tsunami: A case study Co-authors : Priya Logakrishnan, Avnish Varshney, Sreyasi Maiti, Edida Rajesh

© 2012 Risk Management Solutions, Inc. Agenda 2  Background  Study Area  Data Used  Methodology –Delineation of Tsunami extent –Developing building footprint  Validation & Results  Conclusion

© 2012 Risk Management Solutions, Inc. Background 3

© 2012 Risk Management Solutions, Inc. Background 4  Earthquake of 8.9 magnitude struck off the north coast of Tohoku, Japan (Mar’11)  Triggered Tsunami over entire east coast of ~20ft –Huge losses in terms of human lives, built-up urban areas, agricultural fields, and forested areas  Scope of the study area –To estimate the first cut losses and affected region which help modellers\scientist for further management –Delineating the affected region –High resolution data – building level information

© 2012 Risk Management Solutions, Inc. Study Area 5

© 2012 Risk Management Solutions, Inc. Study Area 6  Tohoku, Japan Tsunami –Coastal stretch of Ishinomaki to Sendai of Miyagi prefecture –Stretches about 70 Km from north to south of east coast of Japan with tsunami inundated region Building

© 2012 Risk Management Solutions, Inc. Data Used 7

© 2012 Risk Management Solutions, Inc. Data Used 8  Tsunami delineation –Remote sensing Images - MODIS Image (250m & 500m)  Pre event image (dated 23 rd Feb 2011)  Post event image (dated 12 th Mar 2011)  Developing the building level inventory –Using various open source data  GSI (Geospatial Information Authority of Japan) for major city extent  Open street map (OSM)  Google Earth utilities and Emporis # website are used as references for estimating the quality of the available building footprints # (

© 2012 Risk Management Solutions, Inc. MODIS Pre Tsunami image 9

© 2012 Risk Management Solutions, Inc. MODIS Post Tsunami image 10

© 2012 Risk Management Solutions, Inc. Methodology 11

© 2012 Risk Management Solutions, Inc. Methodology 12  Delineating the Tsunami Area –Change detection algorithm using multi-temporal data  Image registration  Radiometric Normalization –Histogram matching # algorithm is applied to normalize the radiometric affects –Change Vector Analysis (CVA) method is applied

© 2012 Risk Management Solutions, Inc. Methodology 13  Change Vector Analysis –Magnitude and direction - change algorithm is used to identify the impacted region –Two time point images, with two bands only, pixel of time1 image (pre) and time2 images (post)  Magnitude of the change vector ̶ Where date1 and date2 can be denoted by (a 1, b 1 ) and (a 2, b 2 ) respectively  Direction of change θ ̶ is angle of change and a i and b i are the spectral response of pixels in band 1 & 2  Kernel based thresholding algorithm is used after computing the magnitude of the change vector to find change and no-change region  Cleaning and gap filling methods are applied to extract the Tsunami extents using ArcGIS

© 2012 Risk Management Solutions, Inc. Methodology 14  Developing Building Footprint in the Impacted Region –GSI building level data  Region - Sendai and Ishinomaki –OSM data  For remaining region –Building selected –Noise correction

© 2012 Risk Management Solutions, Inc. Methodology 15  Large amount of building footprints –Assigning the building inventory (like number of floors and lines of business – Residential, Commercial & Industrial) –5 ×5 kilometre grid

© 2012 Risk Management Solutions, Inc. Methodology 16 Building data from GSI & OSMBuilding data over GoogleEarthRoad block data Street View from GoogleEarth for validation GSI Defined Process 0.17 million buildings 4 days with 5 resources RS

© 2012 Risk Management Solutions, Inc. Methodology 17  Each grid is further divided based on road block level  Commercial & Industrial are assigned to respective building  Tall rise building  Reference –Google Earth –Emporis website

© 2012 Risk Management Solutions, Inc. Building 3D view based on number of floors 18

© 2012 Risk Management Solutions, Inc. Methodology 19  Combined building footprint after cleaning and inventory assigning –Area calculated for each footprint using ArcGIS –Total building area  Total Area = Area of building × Number of floors –Total cost of the building  Building Cost = Total area × Cost per square meter –Total loss  Aggregated Loss = ∑ Building Cost

© 2012 Risk Management Solutions, Inc. Validation & Results 20

© 2012 Risk Management Solutions, Inc. Validation & Results 21  Tsunami inundated region and building footprints are validated by over laying spatial layers on Google Earth  Building footprints and attribute information are almost matching with the reference images  Removed duplicate building (if any)

© 2012 Risk Management Solutions, Inc. Validation & Results 22 LoBBld CountTot Area (Bld)Exposure MinExposure Max$ vs Yen on MarExposure Min in dollorExposure Max in dollor COM22,07813,597,5681,855,654,081,6012,268,021,655,2901$ = 82 yen22,518,352,13627,522,430,388 IND5,2605,307, ,261,629,3351,095,430,880,2991$ = 82 yen10,876,129,97213,293,047,744 RES106,16025,261,863223,196,736,41702,727,960,111,7631$ = 82 yen27,084,911,76233,103,781,043  Using the above equations, aggregate losses were computed  $60 billion to $74 billion (based on min and max coast value)  Figures are representing the structure loss only $60,479,393,870$73,919,259,175 Source:

© 2012 Risk Management Solutions, Inc. Conclusion 23

© 2012 Risk Management Solutions, Inc. Conclusion 24  Losses computed using MODIS multi-temporal images and digital building footprints  Study helps to compute the first cut losses/damage for disaster management within a short time frame after event  If accurate building footprints are available for a region, one can compute damage/impact cost more accurately.

© 2012 Risk Management Solutions, Inc. Questions ? 25

© 2012 Risk Management Solutions, Inc.26