ALBERT

Description: The common situational awareness among the disaster-response organizations and the appropriate action based on the information sharing are the key factor for the effective and efficient disaster response. Supported by the Cross-ministerial Strategic Innovation Promotion Program (SIP), we have developed the Shared Information Platform for Disaster Management (SIP4D) which facilitate the “cross-ministerial information sharing” by intermediating the various governmental organizations. Also, as the empirical research for utilize the shared disaster-information by SIP4D, we have developed the Medical Activity Support System for Disaster Management, the Reservoir Disaster Prevention Support System, and the Disaster Management Information Service Platform. In this paper, we introduce the overview of our R&D project, and report the implementation plans of our systems in the society.

Description: I would like to express my sincere appreciation for the honor of receiving this prestigious award. The award has been presented to me for the “Special Issue on NIED Frontier Researches on Science and Technology for Disaster Risk Reduction and Resilience 2017” of JDR Vol.12 No.5, for which I was the guest editor. I heard that this special issue has been the most downloaded over the past three years. NIED, to which I belong, is an institute that deals with natural disasters comprehensively. Since 2016, we have been working to become a “core organization for innovation in disaster resilience science and technology” as a new seven-year plan. Japan is a country prone to disasters, with many large-scale natural disasters occurring every year. Recent examples would be the 2016 Kumamoto Earthquake, 2017 Nasu Avalanche, Northern-Kyushu Heavy Rain, 2018 Eruption of Mt. Kusatsu-Shirane, Western-Japan Heavy Rain, Hokkaido Eastern Iburi Earthquake, and 2019 Typhoon #19. We should collect “intelligence” related to natural disasters in multiple fields to reduce our disaster risk and improve our resilience. The Special Issue is a compilation of research results from individual fields. I am elated that the first special issue of NIED has gained such attention. NIED will continue to conduct research across multiple fields. We hope that NIED’s activities will lead to collaboration with many people and that the integration of intelligence will improve disaster resilience in Japan and all over the world.

Description: It is important to discern in real time the risk level of rain-related disasters such as floods and landslides in order to maintain readiness against heavy-rainfall disasters and to decide on the suitable response measures. In this study, we developed an information processing technology that employs hazard information which indicates the risk of inundation or landslides. It also presents indices of social vulnerability and applies the spatial resolution functions of a geographic information system (GIS) to extract in real time the highly exposed and vulnerable areas that are faced with an increased risk of flooding or landslides. The technology’s validity was verified using a case study – namely, the heavy rainfall that accompanied a pressure front in August, 2019. The results show that, with respect to flood risks, we were able to extract in real time specific areas where flooding may be taking place, thus demonstrating the possibility of applying the technology to decide priorities in disaster response measures. Future issues are related to information dissemination, including the specific labeling and expressions that are easy for the user to understand as well as improving the user interface so as to facilitate delivery of relevant risk information in real time.

Description: After a natural disaster occurs, the production and sharing of damage reports are extremely important for a disaster response site. However, one of the problems is that the data shared by the damage reports cannot clearly indicate when the damage situation could be grasped because such data change day by day. Accordingly, in this study, the data of the damage reports of the Headquarters for Disaster Control are treated as unequally spaced time series data to evaluate the changing conditions of the data quantitatively. For this purpose, a case is examined for the Headquarters for Disaster Control of Fukuoka Prefecture at the time of the Northern Kyushu Heavy Rainfall event in July 2017. As a result of the examination, it is indicated that the quantitative evaluation would be possible for 1) analysis on timing when the data of the damage reports are updated, 2) analysis on the characteristics of time series of the report data, and 3) visualization of the progress of the damage report service.

Description: Whenever a natural disaster occurs, a damage assessment must be conducted to determine the extent of the damage caused, in order to quickly and effectively undertake disaster response, recovery, and reconstruction efforts. It is important to consider not only natural phenomena, but the impact of the damage on local communities as well (which is a pressing concern at any disaster site). Although a conventional, field-survey-based disaster assessment can yield solid information, it still takes time to gauge the overall implications. While an SNS system can facilitate information collection in real time, it is riddled with problems such as unreliability, and the challenge of handling vast amounts of data. In this study we analyzed Twitter content that was generated after the 2018 Hokkaido Eastern Iburi Earthquake and was related to disaster response efforts at the site of the disaster, and used it to test an approach that combines and utilizes natural language processing and geo-informatics for disaster assessment. We then verified the use of this process in two different disaster response scenarios. In this paper, we discuss some possible approaches to disaster assessment that utilize SNS information analysis technology.

Description: The capability of resident-led responses to disasters has declined in recent years due to rapid changes in social and urban structures in Japan. In order to improve regional disaster prevention capabilities with regard to disaster risk, which includes a multitude of uncertainties induced by societal changes, it is necessary to reorganize conventional ways of disaster risk management from top-down to bottom-up principle of complementarity with residents as the base point. A multilayered disaster prevention system, corresponded to the diversity of local self-governing activities by residents in ordinary times, would improve regional capabilities for disaster prevention and also increase the likelihood that these capabilities could be expressed in the response at the time of a disaster. This is what we postulate in this paper as a new mode of 'disaster risk governance'. The effectiveness of this postulation will be verified based on a case study of the disaster response by residents in the Kitajo district of Kashiwazaki City, Niigata Prefecture at the time of the Chuetsu-Oki Earthquake, which occurred on July 16, 2007. On that basis, we have developed a new disaster risk communication method in which residents and other stakeholders can ; i) develop an awareness of the current situation of the disaster risk governance structure and related problems, ii) organize a variety of district self-government networks in ordinary times, iii) build a multilayered disaster prevention system that makes use of those networks and other local resources for disaster prevention, and iv) link these efforts to specific disaster prevention activities. To confirm its effectiveness, we have applied this method to the residents-led workshops with voluntary disaster prevention organizations in Fujisawa City, Kanagawa Prefecture.

Description: In April 2016, our institute, NIED, under its new English name the “National Research Institute for Earth Science and Disaster Resilience,” commenced its fourth mid-to-long term planning period, set to last seven years. We are constantly required to carry out comprehensive efforts, including observations, forecasts, experiments, assessments, and countermeasures related to a variety of natural disasters, including earthquakes, tsunamis, volcanic eruptions, landslides, heavy rains, blizzards, and ice storms. Since this is NIED’s first special issue for the Journal of Disaster Research (JDR), works were collected on a wide variety of topics from research divisions and centers as well as from ongoing projects in order to give an overview of the latest achievements of the institute. We are delighted to present 17 papers on five topics: seismic disasters, volcanic disasters, climatic disasters, landslide disasters, and the development of comprehensive Information Communications Technology (ICT) for disaster management. Even though the achievements detailed in these papers are certainly the results individual research, NIED hopes to maximize these achievements for the promotion of science and technology for disaster risk reduction and resilience as a whole. It is our hope that this special issue awakens the readers’ interest in a study, and, of course, creates an opportunity for further collaborative works with us.

Description: In disaster response, wherein many organizations undertake activities simultaneously and in parallel, it is important to unify the overall recognition of the situation through information sharing. Furthermore, each organization must respond appropriately by utilizing this information. In this study, we developed the Shared Information Platform for Disaster Management (SIP4D), targeted at government offices, ministries, and agencies, to carry out information sharing by intermediating between various information systems. We also developed a prototype of the National Research Institute for Earth Science and Disaster Resilience (NIED) Crisis Response Site (NIED-CRS), which provides the obtained information on the web. We applied these systems to support disaster response efforts in the 2016 Kumamoto Earthquakes and other natural disasters. We analyzed the effects of and issues experienced with the information sharing systems. As effects, we found 1) the realization of increased overall efficiency, 2) validity of sharing alternative information, and 3) possibility of using the system as a basis for information integration. As future issues, we highlight the needs for 1) advance loading of data, 2) machine readability of top-down data, and 3) identifying the common minimum required items and standardization of bottom-top data.

Description: Many researchers have highlighted the necessity of disaster prevention countermeasures based on regional characteristics. However, in situations wherein disaster prevention measures are executed, often, no index (data) objectively indicates the risk of disaster considering regional characteristics. Therefore, disaster prevention measures are sometimes implemented without considering regional characteristics. As such, a way to extract and present disaster prevention countermeasures and examples that consider regional characteristics, including the risk of disaster are now needed. In the present study, we search for indices of the regional characteristics necessary to implement disaster prevention countermeasures and study a method to extract these countermeasures and examples based on the indices. In addition, the appropriateness of the method to extract the disaster prevention countermeasures and examples considering regional characteristics is verified through a questionnaire survey and interview.

Description: Regional disaster prevention activities must be evaluated in terms of their effectiveness and suitability, and then improved on the basis of this evaluation. Those who can evaluate such activities are required to have abundant on-site experience in and extensive knowledge on disaster prevention. However, there is a shortage of such talent, and the training and nurturing thereof requires considerable resources. To address these issues, machine learning was introduced in our previous study to automate the evaluation of such activities. In the present study, we propose the automatic generation of the evaluation model of such activities using the responses of a self-evaluation questionnaire as the input variables. The output variables are the results of a review committee consisting of experts on disaster prevention. This paper describes the application of the model to the fourth Disaster Prevention Map Contest, examines the predicted results, and discusses the application conditions and issues to be resolved.