Fusion of Real-time Tsunami Simulation and Remote Sensing for Mapping the Impact of Tsunami Disaster

Bringing together state-of-the-art high-performance computing, remote sensing and spatial information sciences, we establish a method of real-time tsunami inundation forecasting, damage estimation and mapping to enhance disaster response. Right after a major (near field) earthquake is triggered, we perform a real-time tsunami inundation forecasting with use of high-performance computing platform. Given the maximum flow depth distribution, we perform quantitative estimation of exposed population using census data and the numbers of potential death and damaged structures by applying tsunami fragility curve. After the potential tsunami-affected areas are estimated, the analysis gets focused and moves on to the "detection" phase using remote sensing. Recent advances of remote sensing technologies expand capabilities of detecting spatial extent of tsunami affected area and structural damage. Especially, a semi-automated method to estimate building damage in tsunami-affected areas is developed using optical sensor data and a set of pre-and post-event high-resolution SAR (Synthetic Aperture Radar) data. The method is verified through the case studies in the 2011 Tohoku and other potential tsunami scenarios, and the prototype system development is now underway in Kochi prefecture, one of at-risk coastal city against Nankai trough earthquake. In the trial operation, we verify the capability of the method as a new tsunami early warning and response system for stakeholders and responders

Damage mapping after the 2017 Puebla Earthquake in Mexico using high-resolution Alos2 Palsar2 data

On September 19, 2017, the Mw7.1 Puebla Earthquake caused significant destruction in several cities in central Mexico. In this paper, two pre- and one post-event ALOS2-PALSAR2 data were used to detect the damaged area around Izucar de Matamoros town in Mexico. First, we identify the built-up areas using pre-event data. Second, we evaluate the earthquake-induced damage areas using an RGB color-coded image constructed from the pre- and co-event coherence images. Our analysis showed that the green and red bands display a great potential to discriminate the damaged areas.Accepted manuscrip

A framework of rapid regional tsunami damage recognition from post-event TerraSAR-X imagery using deep neural networks

Near real-time building damage mapping is an indispensable prerequisite for governments to make decisions for disaster relief. With high-resolution synthetic aperture radar (SAR) systems, such as TerraSAR-X, the provision of such products in a fast and effective way becomes possible. In this letter, a deep learning-based framework for rapid regional tsunami damage recognition using post-event SAR imagery is proposed. To perform such a rapid damage mapping, a series of tile-based image split analysis is employed to generate the data set. Next, a selection algorithm with the SqueezeNet network is developed to swiftly distinguish between built-up (BU) and nonbuilt-up regions. Finally, a recognition algorithm with a modified wide residual network is developed to classify the BU regions into wash away, collapsed, and slightly damaged regions. Experiments performed on the TerraSAR-X data from the 2011 Tohoku earthquake and tsunami in Japan show a BU region extraction accuracy of 80.4% and a damage-level recognition accuracy of 74.8%, respectively. Our framework takes around 2 h to train on a new region, and only several minutes for prediction.This work was supported in part by JST CREST, Japan, under Grant JPMJCR1411 and in part by the China Scholarship Council. (JPMJCR1411 - JST CREST, Japan; China Scholarship Council

Disaster debris estimation using high-resolution polarimetric stereo-SAR

AbstractThis paper addresses the problem of debris estimation which is one of the most important initial challenges in the wake of a disaster like the Great East Japan Earthquake and Tsunami. Reasonable estimates of the debris have to be made available to decision makers as quickly as possible. Current approaches to obtain this information are far from being optimal as they usually rely on manual interpretation of optical imagery. We have developed a novel approach for the estimation of tsunami debris pile heights and volumes for improved emergency response. The method is based on a stereo-synthetic aperture radar (stereo-SAR) approach for very high-resolution polarimetric SAR. An advanced gradient-based optical-flow estimation technique is applied for optimal image coregistration of the low-coherence non-interferometric data resulting from the illumination from opposite directions and in different polarizations. By applying model based decomposition of the coherency matrix, only the odd bounce scattering contributions are used to optimize echo time computation. The method exclusively considers the relative height differences from the top of the piles to their base to achieve a very fine resolution in height estimation. To define the base, a reference point on non-debris-covered ground surface is located adjacent to the debris pile targets by exploiting the polarimetric scattering information. The proposed technique is validated using in situ data of real tsunami debris taken on a temporary debris management site in the tsunami affected area near Sendai city, Japan. The estimated height error is smaller than 0.6m RMSE. The good quality of derived pile heights allows for a voxel-based estimation of debris volumes with a RMSE of 1099m3. Advantages of the proposed method are fast computation time, and robust height and volume estimation of debris piles without the need for pre-event data or auxiliary information like DEM, topographic maps or GCPs

Combination of school evacuation drill with tsunami inundation simulation: Consensus-making between disaster experts and citizens on an evacuation strategy

This paper aims to introduce an effective methodology for communicating a science-based tsunami risk scenario to non-expert citizens through consensus-making between disaster experts and non-experts, with the aid of four-way split-screen movie clips depicting evacuation scenarios. Action research on tsunami education in Zihuatanejo, Mexico found that a perception of tsunamis as catastrophic together with the one-directional nature of risk communication resulted in inaction on the part of non-experts in disaster preparedness, contrary to the expectations of experts. In other words, non-experts did not think that they could cope with a tsunami disaster and they perceived that as non-experts they themselves could not affect the tsunami risk scenario communicated to them by the experts. In response, movie clips simultaneously displaying a school evacuation drill and tsunami inundation simulation were developed. These movie clips are intended to serve as a tool in the process of establishing a school tsunami evacuation strategy by promoting consensus-making between experts and non-experts about the risk scenario, thereby helping to change the perception of a tsunami from a catastrophe that cannot be dealt with by non-experts to a realistic perception that non-experts can indeed help by engaging in their own tsunami risk preparedness activities. The developed movie clips were used at a workshop for stakeholders, including academics, local government, and teachers, with the aims of establishing scenario-based evacuation strategies and promoting the proactive implementation of preparedness activities by non-expert teachers. The study will contribute to establishing a mechanism for applying scientific knowledge to solving societal issues

Method to extract difficult-to-evacuate areas by using tsunami evacuation simulation and numerical analysis

Extracting the area where people have difficulty evacuating (hereafter difficult-to-evacuate areas, DEA) when tsunamis hit after an earthquake is important for effective disaster mitigation measures. The DEA was conven-tionally extracted by simply considering the walking speed, distance to the evacuation destination, and time needed for evacuation after considering the estimated tsunami inundation area. However, evaluating the DEA from such a simple scheme is insufficient because the behavior of residents and the road conditions to the evacuation destinations after an earthquake are not properly reflected in the scheme. In this study, agent-based tsunami evacuation simulations that can reflect the behavior of residents and real -time changes in the situation were conducted in Zihuatanejo, Guerrero, Mexico. It is a prime sightseeing destination under the high risk of megathrust events in the Guerrero Gap. First, by checking the simulation images at the tsunami arrival time, bottleneck locations were identified, and five additional models with different measures for the bottleneck locations were constructed and tested to find the best model with 195 casualties. Then, focusing on the best model, three indices for the casualties were proposed to extract the DEA effectively and quantitatively, and numerical analyses using the three indices was conducted. Finally, the subdistrict in the center of the target area (subdistrict 5) was quantitatively found to be the district that should be given the highest priority for measures. Moreover, an example model with a new measure in subdistrict 5 was validated to have 101 casualties. The key points for applying the proposed method for extraction of DEA in other areas are summarized

Lessons Learned from the 2011 Great East Japan Tsunami: Performance of Tsunami Countermeasures, Coastal Buildings, and Tsunami Evacuation in Japan

In 2011, Japan was hit by a tsunami that was generated by the greatest earthquake in its history. The first tsunami warning was announced 3 min after the earthquake, as is normal, but failed to estimate the actual tsunami height. Most of the structural countermeasures were not designed for the huge tsunami that was generated by the magnitude M = 9.0 earthquake; as a result, many were destroyed and did not stop the tsunami. These structures included breakwaters, seawalls, water gates, and control forests. In this paper we discuss the performance of these countermeasures, and the mechanisms by which they were damaged; we also discuss damage to residential houses, commercial and public buildings, and evacuation buildings. Some topics regarding tsunami awareness and mitigation are discussed. The failures of structural defenses are a reminder that structural (hard) measures alone were not sufficient to protect people and buildings from a major disaster such as this. These defenses might be able to reduce the impact but should be designed so that they can survive even if the tsunami flows over them. Coastal residents should also understand the function and limit of the hard measures. For this purpose, non-structural (soft) measures, for example experience and awareness, are very important for promoting rapid evacuation in the event of a tsunami. An adequate communication system for tsunami warning messages and more evacuation shelters with evacuation routes in good condition might support a safe evacuation process. The combination of both hard and soft measures is very important for reducing the loss caused by a major tsunami. This tsunami has taught us that natural disasters can occur repeatedly and that their scale is sometimes larger than expected