Hiromichi Fukui

Geographical structures and the cholera epidemic in modern Japan: Fukushima prefecture in 1882 and 1895

BackgroundDisease diffusion patterns can provide clues for understanding geographical change. Fukushima, a rural prefecture in northeast Japan, was chosen for a case study of the late nineteenth century cholera epidemic that occurred in that country. Two volumes of Cholera Ryu-ko Kiji (Cholera Epidemic Report), published by the prefectural government in 1882 and 1895, provide valuable records for analyzing and modelling diffusion. Text descriptions and numerical evidence culled from the reports were incorporated into a temporal-spatial study framework using geographic information system (GIS) and geo-statistical techniques.ResultsChanges in diffusion patterns between 1882 and 1895 reflect improvements in the Fukushima transportation system and growth in social-economic networks. The data reveal different diffusion systems in separate regions in which residents of Fukushima and neighboring prefectures interacted. Our model also shows that an area in the prefectures northern interior was dominated by a mix of diffusion processes (contagious and hierarchical), that the southern coastal region was affected by a contagious process, and that other infected areas experienced relocation diffusion.ConclusionIn addition to enhancing our understanding of epidemics, the spatial-temporal patterns of cholera diffusion offer opportunities for studying regional change in modern Japan. By highlighting the dynamics of regional reorganization, our findings can be used to better understand the formation of an urban hierarchy in late nineteenth century Japan.

Geospatial Mediator Functions and Container-Based Fast Transfer Interface in Si3CO Test-Bed

In order to improve the spatial information infrastructure in Japan, we have organized Si3CO (Spatial Information Infrastructure Interoperability Consortium), and we are newly developing a Japanese interoperable test-bed based on OGIS. In this system, we propose the new three tier model which is composed of web clients, legacy database wrappers, and GSM (Geo Spatial Mediator). Especially GSM locates between client and wrappers, and can compensate spatial objects. Moreover, we propose container-based fast transfer interface of spatial objects as for the CORBA implementation.

Real time monitoring for Imja Glacial Lake in Himalaya — global warming front monitoring system

Imja Tsho Lake is one of the fastest growing in the entire Himalayan region. Regular monitoring based on scientific data and information of the lake is crucial. To initiate an early warning system, a wireless LAN has been established using innovative geo-ICT tools and technologies to connect different field monitoring devices for real time monitoring and early warning system for potential GLOF. There are three main objectives of this project which includes the demonstration of real time monitoring, establishing early warning system with local community and promotion of Wi-fi technology in remote mountain areas for global connectivity.

Improvement of Glacial Lakes Detection under Shadow Environment Using ASTER Data in Himalayas, Nepal

The detection of glacial lake change in the Himalayas, Nepal is extremely significant since the glacial lake change is one of the crucial indicators of global climate change in this area, where is the most sensitive area of the global climate changes. In the Himalayas, some of glacial lakes are covered by the dark mountains’ shadow because of their location. Therefore, these lakes can not be detected by conventional method such as Normalized Difference Water Index (NDWI), because the reflectance feature of shadowed glacial lake is different comparing to the ones which are located in the open flat area. The shadow causes two major problems: 1) glacial lakes which are covered by shadow completely result in underestimation of the number of glacial lakes; 2) glacial lakes which are partly identified are considered to undervalue the area of glacial lakes. The aim of this study is to develop a new model, named Detection of Shadowed Glacial Lakes (DSGL) model, to identify glacial lakes under the shadow environment by using Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) data in the Himalayas, Nepal. The DSGL model is based on integration of two different modifications of NDWI, namely NDWIs model and NDWIshe model. NDWIs is defined as integration of the NDWI and slope analysis and used for detecting non-shadowed lake in the mountain area. The NDWIshe is proposed as a new methodology to overcome the weakness of NDWIs on identifying shadowed lakes in highly elevated mountainous area such as the Himalayas. The first step of the NDWIshe is to enhance the data from ASTER 1B using the histogram equalization (HE) method, and its outcome product is named ASTERhe. We used the ASTERhe for calculating the NDWIhe and the NDWIshe. Integrated with terrain analysis using Digital Elevation Model (DEM) data, the NDWIshe can be used to identify the shadowed glacial lakes in the Himalayas. NDWIs value of 0.41 is used to identify the glacier lake (NDWIs ≥ 0.41), and 0.3 of NDWIshe is used to identify the shadowed glacier lake (NDWIshe ≤ 0.3). The DSGL model was proved to be able to classify the glacial lakes more accurately, while the NDWI model had tendency to underestimate the presence of actual glacial lakes. Correct classification rate regarding the products from NDWI model and DSGL model were 57% and 99%, respectively. The results of this paper demonstrated that the DSGL model is promising to detect glacial lakes in the shadowed environment at high mountains.

Effects of excessive harvest on plant species and forest structures in a subtropical evergreen forest of Castanopsis sieboldii

Abstract The subtropical evergreen forest of Yanbaru in the northern district of Okinawa is famous for its treasury of biodiversity. For the most part, biodiversity continues to persist in abundance, especially in the forests inside the US Marine base - The Jungle Warfare Training Center (JWTC), which escaped the excessive harvest after WWII. However, these forests also experienced excessive use of trees and shrubs during the war. Now that the return of more than half the JWTC area is close at hand, it is important to clarify the effects of this pre-1945 impact in order to develop a biological conservation plan. Accordingly, plant species and forest structures in evergreen broadleaved forests dominated by Castanopsis sieboldii, the major forest type in Yanbaru, were investigated. The impact of severe use during the war was not detected in species richness and species composition. However, stand volumes and foliage height diversity in forests that were severely used before 1945 were found to be less developed. Rehabilitation of these severely used forests of C. sieboldii is an important mission for biological conservation, because many indigenous animals selectively inhabit old-grown forests of C. sieboldii with highly developed structures.

Database assessment of CMIP5 and hydrological models to determine flood risk areas

Solutions for water-related disasters may not be solved with a single scientific method. Based on this premise, we involved logic conceptions, associate sequential result amongst models, and database applications attempting to analyse historical and future scenarios in the context of flooding. The three main models used in this study are (1) the fifth phase of the Coupled Model Intercomparison Project (CMIP5) to derive precipitation; (2) the Integrated Flood Analysis System (IFAS) to extract amount of discharge; and (3) the Hydrologic Engineering Center (HEC) model to generate inundated areas. This research notably focused on integrating data regardless of system-design complexity, and database approaches are significantly flexible, manageable, and well-supported for system data transfer, which makes them suitable for monitoring a flood. The outcome of flood map together with real-time stream data can help local communities identify areas at-risk of flooding in advance.

The Web-Based Assessment for Inundated Area Detection

An object-based image processing technique is applied to detect inundated areas using Land sat images. An interoperable Web-based system was developed to conduct the analyses so that redundant steps in Land sat image processing can be effectively eliminated. A review process is used to discover and develop suitable algorithms to automatically detect inundated areas and immediately transfer the results to the Web-based interface. This is a significant improvement over currently available methods for inundation detection systems. The tool is expected to be a practical inundated area detection function and be applicable across wide-reaching areas.