Most of previous surveys of tourist activities using GPS devices have focused on where tourists visit and how long they stay, but not on what they actually do at each location. Thus, we have attempted to investigate the relations between the tourists' actual activities and their spatio-temporal data. In this paper, we conducted some experiments at a zoological park to build statistical methods for estimating whether a tourist is viewing an exhibition or not from his/her GPS logs. The result shows that their walking speed seems critical for the estimation, and, by considering additional parameters, we can estimate precisely whether 20s tourist is viewing or not.

We classified unsuccessful 60-year-old forests, planted mainly with hinoki cypress (Chamaecyparis obtusa), into types based on the species composition of invading trees, and determined the change of each forest type. Thematic maps of topographic factors were derived from a digital elevation model generated from LiDAR data. The study area was classified into four forest types, based on tree regression analysis of species composition and the topographic factors. Then the dominance of C. obtusa and invading trees was determined from the distribution maps of their top heights created based on tree regression analyses of them and the topographic factors. The relationship between the dominance of them and forest types was shown. Finally, changes in the stand volume of each forest type were determined. Based on the results, we suggest the following three future management policies for each forest type, taking into consideration the timber price of invading hardwood trees, the growth of C. obtusa, and the increase in stand volume: no operations, reinforcement planting, or switching to mixed conifers and hardwood forests.

It is inferred that spatial trend of Jomon occupation sites was largely affected by various and mixed environmental factors such as elevation, slope, land aspect, solar radiation and subsurface geology. In order to identify the most influential factors in selecting occupation sites, we conducted a GIS and univariate analyses of the location of archaeological sites in the Southwestern Kanto region. Then, we used a general linear model and a standardized partial regression coefficient analysis to investigate the relative importance of each environmental factor. As a result, we confirmed that the Jomon sites were distributed on uplands or gradual hills 7 to 21% more than expected by chance. Previously, solar radiation, slope and aspect of lands, that were thought to be main factors for site selection, but we revealed that the Loam layer in subsurface geology (distributed on upland and gradual hill) was the most important factor.

The promotion of paddy rice planted area is one of the important factors for estimating pesticide concentration in river water. The aim of this paper is estimating a ratio of paddy rice planted area derived from the National Land Numerical Information (NLNI) and statistics of agriculture using FOSS4G (Free and Open Source Software for Geospatial). First, we developed a spatial database about land use and river basin. And we calculated factors to convert paddy categories in NLNI to paddy rice planted area based on agricultural statistics. Then, the ratio of paddy rice planted area of prefectures, river systems and upstream basin area on river discharge monitoring sites were estimated. It is concluded that the estimation based on NLNI and statistics of agriculture reflected characteristic of the upstream basin at river discharge monitoring sites.

Point event cluster detection in networks have been proposed recently; they are suitable for analyses based on detailed location information, as they can describe the micro-space variation of locations of point events at the street level. However, the previous methods lack the flexibility to control the shapes of detected clusters; one can only detect‘circle-like’ compact clusters that might include links where point events are scarcely distributed, and the other can only detect complex-shaped clusters that are difficult to interpret their causes. This paper proposes a shape complexity index in networks and a new cluster detection method imposing constraint on the shape complexity based on the proposed index. The application revealed that the proposed method succeeds in controlling the shape complexity of detected clusters in networks.

The distance is one of the important indexes to make facility location plan. Our study aims to discuss how to consider the ratio of the road distance to the straight line distance for the index of facility location planning. By measuring the distance between the emergency landing field for a helicopter and the target point in Toyota City, there is an acceptable error range to evaluate the transport time by measuring the straight line distance. On the other hand, the ratio of the road distance to the straight line distance tend to have small coefficient of determination in case that the target point set the signalized intersection in rural area. In such a case, the distance by the road network analysis should be applied.