The number of climbers in Japanese mountains have increased for recent years, and climbing and hiking have been getting constructive fields in tourism. However, some climbing beginners, especially middle aged and older people, who are overconfident on own physical strength sometimes encounter serious accidents and distresses. Actually, an accident and a distress in a mountain have also increased in these years. In order to achieve safer mountain climbing, it would be effective to aggregate and analyze individual climbing experiences in accordance with not only individual conditions but also mountain environments even if there is poor network connection and power supply. Therefore, this paper aims to organize available datasets for analysis of practical behavior of mountain climbers, and describes methods to obtain climbing behavior data even for middle and older people under poor network and power environment. In particular, we implemented a cloud system to aggregate online-submitted climbing plans, and a check-in app using individual owned IC-cards. Finally, this paper describes some findings and discussions through our field experiments.
As a joint usage/research center, Center for Spatial Information Science has been supporting researchers by establishing a spatial data infrastructure for academic research and making it available for proposed research projects based on the strict review by inter-university researchers. We reconstruct the information system for managing the whole process above due to the expansion of the data infrastructure and the increase of the number of users. In this paper, we summarize the problems and the proposed solutions in developing the system and evaluate it based on the usage log. We especially summarize specific issues from the viewpoint of open science.
We often want to repeatedly calculate the distance and travel time between two locations, and GIS has been used for this purpose. However, it is generally assumed that such calculations require expensive software and data and therefore they may be considered not readily available. In the meantime, there currently are freely available spatial network data, GIS software, and web services for optimal path search, and therefore it may appear that it is possible to calculate the distance and traveling time for many sets of pairs of locations without spending any monetary cost. This study conducts an experiment of the calculation of the distance and travel time between locations using freely available data, software, and web services and reports the results. Specifically, we use OpenStreetMap data, QGIS, and Google Maps Distance Matrix API, in this experimental calculation. From the results, we demonstrate the possibilities and limitations of using freely available data, software, and services.
Demographic composition, e.g., population composition by age-groups, is one of the most basic information for discussing regional issue or planning. The present study compares the future Japan through 2010-2060, estimated by National Institute of Population and Social Security Research, with all municipalities in 2010 from the perspective of demographic compositions classified by fiveyear age groups (0-4, 5-9, ..., 90+). The (dis-)similarity of compositional data can be measured with Aitchison distance, one of the core concepts of compositional data analysis. We create choropleth maps based on Aitchison distance. The maps, for example, indicate that the demographic composition of Sobetsu-cho of Hokkaido prefecture of 2010 is the most analogous of the future of Japan of 2060.
We study location specifying method on the road. This paper describes specifying locations which are damaged by the 2016 Kumamoto earthquake on roads managed by Kumamoto Prefecture. We analyzed the expression of the announcement of damaged locations, investigated location gathering in the disaster situation by interview with the road administrator, and specified the locations from the announcement through maps and field investigation. In location specifying, there were some locations we could not specify and there were some locations we had mistaken. Improving the situation, we have developed "Road Geocoder" which shows candidates of location on roads using various geographical identifiers filtered through coordinates of road.
Understanding the skier's behavior (including snowboarders and other equipment users) in a snow area contributes not only to efficient management of safety and facilities but also improving services. However, a snow area manager only knows the number of skiers who use the lifts or gondolas in general. We proposed a framework to analyze skier's behavior with GPS in snow resorts, which consists of two standpoints such as inter- and inner-ski slopes. We clarified both a transition of skier's choice in relation to ski slopes, lifts/gondolas and rest places (inter-ski slopes), and a movement of skiers in each ski slope (inner-ski slope). We found that the characteristics of skier and ski slope had more variety than the technical levels: beginners', intermediate, and advanced. Even if ski slopes had the same level, they had different characteristics from each other. The framework contributes to understanding the detail of skier's behavior and improving services.