Much effort is underway to realize the concept of Building Information Modeling (BIM) in the building industry. However, in the civil infrastructure domain, the BIM concept has not been adopted yet in practice because few engineers are accustomed to 3D models. As the interaction between 3D models and structural analysis software packages is important in the design phase, two structural analysis software packages for railway viaduct were selected to investigate the linkage between 3D models and the packages. Furthermore, a method of the interaction with ST-BRIDGE, which has been developed by the Structural Group of buildingSMART Japan was demonstrated. Finally, issues related to 3D modeling were discussed.

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 For better image-texture analysis and interpretation, this paper proposes an index for evaluating visibility of Feature Composite Moving images (termed "FCM image") inducing visual illusion (i.e., pseudo-rotational and persistent of vision). The animation-like FCM image is produced by continuously displaying emboss processing-based images (i.e., shade images) according to eight directions of light sources. On the assumption that the fluctuation of digital number values (i.e., spatial frequency components) in each pixel of FCM image, which changes every second, is reflected in the visibility of texture features in FCM image, the power spectrums for those fluctuations calculated with Discrete Fourier Transform are grouped into 40 classes which are delineated on Visibility Evaluation Map (termed "VE Map"). Through the experiments, the result indicates that the VE map is useful for quantitatively evaluating the visibility of various kinds of texture features in the images.

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 For better estimation of hazardous areas affected by different types of simultaneous slope failures, this paper proposes an algorithm for improving representativeness of training data sets (i.e., past occurrences of slope failures) for producing susceptibility maps of slope failures. The spatial quantitative models generally elucidate the relationship between training data sets and causal factors (e.g. topography, surface geology, soil, vegetation, slope, aspect, drainage, etc.). The proposed algorithm resamples the matched pixels between original groups of past slope failures (i.e., surface slope failures, deep-seated slope failures, landslides) and classified three groups by cluster analysis for all pixels corresponding to those slope failures. For all cases of three types of slope failures, the improvement of success rates with respect to resampled training data sets was confirmed. Furthermore, the differences between produced susceptibility maps by using original and resampled training data sets are delineated on difference maps which are effective in evaluating hazardous areas affected by different types of simultaneous slope failures.

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 In urban planning and renewal or refurbishment of existing buildings and structures in urban areas, virtual reality (VR) simulation using 3 dimentional models in landscape investigation is useful and effective for building consensus among citizens and other stakeholders. However, it takes much effort, time and cost to make 3D models of all existing buildings and structures in the area. In the near future, many buildings will have their own Building Information Modeling (BIM) data, of which amount can be extremely large and which will not be easily used for VR simulation for urban planning. Thus, in this researche we developed a new method for making a simplified 3D model for VR from a huge BIM data using set intersection operation and we implemented the method as an automatic program. We verified the system by using 6 different kinds of buiding models successfully. The system was applied to a virtual landscape investigation in a hypothetical city model and showed a satisfactory performance.

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 This paper introduces a newly developed bridge management system for the prestressed concrete(PC) bridges (J-BMS PC version) which integrated with the PC bridge rating expert system(BREX). The proposed system is able to predict the deterioration process of the existing PC bridge superstructure components as well as assess a broad array of optional corrective strategies. The system also has the capability to search and retrieve from a J-BMS database system(J-BMS DB), the necessary information, carry out suitable analyses to arrive at some recommendations that would help users to optimize their decisions based on engineering aspects, cost and economic issues and bridge management policies. A comparison of the results of applying the system to some actual in-service PC bridges with a special designed survey form to experts shows that optimal maintenance planning as well as bridge rating can be predicted accurately by using the system.

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 The cross-hairs reticles of non-prism total stations cannot accurately measure the target on the objects which don't have a mark to put the cross-hairs on. Especially, it is too difficult to measure the centers of cylindrical structures. In this research, we propose to use a concentric reticle, the Baum, instead of the conventional cross-hairs reticles, and estimated the error from experiments. Total stations equipped with the Baum can measure the cylindrical structures. By measuring two points on the center, the tilt and the position of the axis can be measured, Applying this technology to driving pile, we have developed a navigation system for driving tilted piles which had been difficult to control their operation. The numerical value of to what degree the angle and distance should be adjusted is displayed from the operator's view. Also, the operation history can be recorded.

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 Traffic volume and travel speed road traffic data are extremely important not only for survey and research purposes, but also for administrative management. In order to more effectively understand road traffic conditions and explain the need for and effectiveness of road projects, we need to collect detailed road traffic data. There are fewer traffic data for general roads than for highways and collecting traffic data is a particular problem.We have developed a set of algorithms to take full advantage of the vehicle detectors placed on general roads to calculate highway traffic volume data, and put these algorithms into practice. One feature of the algorithm that was developed is its ability to calculate the daily highway traffic data with sufficient accu-racy for practical application based on a simple algorithm. This makes it possible to collect more detailed general road traffic volume data.

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 This paper proposes a methodology to estimate an "enclosure index" in urban areas using airborne LiDAR. The index is defined as a ratio of occluded area to whole of area in azimuth angle-elevation angle space. The index can be applied to assess local landscape, and it is expected to estimate it in a wide area at low cost. The author examined the methodology to estimate it using airborne LiDAR data measured in last-pulse mode. The estimated index map was validated with the ground truth data, and the error was acceptable, approximately 3%. Even though the last-pulse mode data may underestimate actual digital surface model (DSM), it was found that the proposed methodology is effective to estimate the index in a wide area at low cost.

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 In recent years, asset management has been conducted for structures such as roads and bridges, being promoted by Ministry of Land, Infrastructure, Transport and Tourism (MLIT). In asset management, it is necessary to make a maintenance plan with the highest cost effectiveness by quickly grasping corrosion or flaked coating of the structures as well as their long-term changes such as distortion and transformation. However, it takes much expense in time and effort to grasp the long-term changes because it is done by inspectors' visual inspection. This research first generates a panorama image and panorama range image from the image group and range image group obtained using the range image sensor in order to detect long-term changes in a large-scale structure. Second, the structures in the panorama image and panorama range image at current and past are aligned. Then, a system is developed to detect long-term changes in color- and three-dimensional information on the structures at the same time, by comparing color- and three-dimensional pieces of information on the structures at current and past. Finally demonstration experiments are performed to verify its usability.

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 As for the satellite based positioning system GPS has been used mainly, but GLONASS has made great progress and has come to be used in recent years. Therefore, improvement of positioning availability is expected in the urban and mountainous areas by using GLONASS satellite as well as GPS satellite. However, the increase of satellite may cause the increase of multipath; it is required to select the satellite to be used in advance check the status of satellite radio. The authors investigated the classification method of satellite radio of multipath using the distance change of the carrier wave L1 and L2; then verified the effect of interferometric positioning by satellite selection to be used for positioning. As a result, satellite radio of multipath affected was confirmed by distance change of the carrier wave. In addition, positioning ratio of interferometric positioning has been improved by the satellite selection, and high accuracy solution was confirmed to obtain by continuously.

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 Road network data is often utilized in areas of traffic analysis and routing assistance services. In recent years, the development of more convenient services and higher levels of precise analysis are on theverge of being realized by advances in ITS and street lane level analysis of travel speed. In anticipation of this, Japan DRM association is proceeding with a re-collection of road network data of street junctions at the street lane level, in metropolitan areas. However since each update of road network data require manual charting and field survey work, the efficiency is desired.
 In this study, we have conceived a semi-automatic method for generating three-dimensional road network data of each lane, with using the fundamental geospatial data of road and the point cloud data. In addition to this, we have verified the usefulness of developed method such as extraction algorithm of point cloud data of road surface, algorithm to grant height with live data.

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 Localized surface distress that increases pavement roughness needs the functional evaluation derived from road profile. This study examines a detection method of severe cracks in terms of quarter-car (QC) filtered roughness profile by lifting wavelet filters. Lifting wavelet filters are adaptive biorthogonal wavelet filters containing free parameters. In this paper, we design a set of lifting wavelet filters for detecting diagnostic cracks on the QC filtered profile. The filters includes free parameters that intend to enhance causative crack characteristics in the QC motion. According to the results of adapting the filters to the QC filtered profile, the locations of severe cracks are identified, whereas locations that are not related to the QC motion are not detected. Therefore, we conclude that the lifting scheme is an effective method for detecting the severe cracks for pavement surface monitoring activities.

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 Pavement ride quality testing is difficult to quantify the evaluation results based on the questionnaire due to the lack of objectivity. This study develops a ride quality rating system using a driving simulator and physiological information such as heart rate variability (HRV) that contributes to quantitative and high accuracy pavement surface monitoring. As a result, oscillations of HRV indicate a constant tendency toward different roughness conditions in case that experimental participants suffer mental stress caused by the vehicle vibration. On the other hand, some participants adjust to the vehicle vibration according to the increase of the number of trials. Because these results are observed on the driving simulator experiment as well as the in situ survey, the developed system is valid in pavement surface monitoring based on the ride quality rating of road users.

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 This paper propose a method of construction planning with geographical modified model as a visualization tool by contractor and ordering party. Natural disaster occurs, rapid response is required to prevent secondary disasters. and this response called emergency restoration work. Contractor and ordering party do construction planning. However, They must consider many things. For example, the number of days in heavy equipment and construction. geotechnical modified model can consider them. Using this model enables to reduce discussion time about a construction planning, moreover, to set about emergency restoration work immediately.

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 To keep road maps and map data in car navigation system current gives great benefits to citizens. However, a lot of time and effort is needed to gather information which follows roads change. To improve the situation, this paper presents construction-records which are collected to control the quality of public works all over Japan can predict for locations where roads change. First, construction-records within a certain period of time are grouped by location. Next, the construction method/ type information is converted into explanatory variables (independent variable). The variables aggregated by each location are calculated by a supervised machine learning. An experimental evaluation showed that the method outputted decision tree models which reflected process of road construction, and the average recall ratio was approximately 95%.

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 It is allegedly possible to create a topographical map on a scale of smaller than 1:2,500 if using the latest satellite. Furthermore, satellite imagery is superior in terms of cost, time, and efficiency since it allows shooting huge areas at a time compared with an aircraft; thus it is highly expected as the next-generation method for creating a topographical map to replace the existing method with the aircraft. At present, however, due to some problems and challenges, studies and researches are made merely on the level of cases and experiments both at home and abroad, not reaching the working level yet. This study aims to formulate a method for creating a three-dimensional topographical map using satellite imagery and a method for extracting update points. Specifically, a three-dimensional measuring method is formulated using different satellite images to solve the problem of recurrence periods. In addition, a method for automatically extracting update points in the topographical map by superimposing the radar satellite images in time sequence is also formulated.

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 In recent years, efforts to construct three-dimensional (3D) space data have been drawing attention. Representative cases include studies using MMS or a laser range sensor. In these studies, however, their availability is limited in some areas such as the inside of buildings or underground shopping malls where GPS accuracy is low. Methods without using GPS include a proposed approach called SLAM to construct 3D space data by estimating relative positions from a characteristic object in the real space and calculating the moving path. However SLAM, which uses learning data, has a problem in that the precision depends on learning data. Then, this research proposes a method for estimating the relative positions between a range image sensor and objects, which does not need GPS or learning data. This makes it possible to construct three-dimensional space without depending on the shooting environment.

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 The elevated highway bridges intensively developed during the high economic growth period are now becoming deteriorated over time all together. This requires a maintenance technology to preserve highway functions systematically. To make a systematic maintenance plan, it is essential to grasp the present condition of road surface. This requires a route survey by taking some measures such as temporary suspension of traffic, though it is not easy. This study proposes a method for creating three-dimensional (3D) current state drawings that keep information such as road centerlines and are usable for maintenance on the superstructure of highway bridge by performing a route survey with a mobile mapping system (MMS). Our demonstration experiments verify the validity in making a maintenance plan with current state drawings in comparison with the existing materials such as final drawings of construction works.

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 Affected by global warming, it is estimated that the sea level is rising up to 59cm by the end of this century. For this reason, it is necessary to create especially the elevation date of lowlands along the sea. In this research, elevation data was created in accordance with two or more DSM creation methods. And, we examined the comparison method of DEM and DSM accuracy generated by each method and compared the accuracy of the DEM and DSM generated by GSI-10m, LP, ALOS/PRISIM, and ALOS/PALSAR.

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 It is essential for disaster recovery to grasp the state of disaster promptly and properly. Existing assets useful in grasping affected areas such as LP are accumulated in river projects. Then, the detailed conditions of the affected areas can be grasped by comparing the three-dimensional CAD data generated from the existing asset LP with the dimensional CAD data from the LP after the earthquake disaster . However, while rapid response is required in recovery response, it takes much work to confirm all the affected areas in detail. This research first analyzes the situations of damage caused by the Great East Japan Earthquake, and set up guidelines for detecting affected areas. Second, a method for automatically detecting possible affected areas is proposed utilizing LP before and after the earthquake disaster. To evaluate usefulness of the proposed method, demonstration experiments are performed using LP obtained in the Great East Japan Earthquake, and the detection accuracy of the possible affected areas is evaluated.

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 According to the Fourth Assessment Report of the IPCC, due to the climate change, it is assumed that the flood damages such as typhoon will be increased at lowland area.In order to decrease storm and flood damages, it is important to unify the measures over landuse, environmental plan, and traffic environment. In this research, we focused on the Hai-Hau coast that is a downstream of Red-River,Vietnam. Around the Hai-hau coast, vast lowland area are distributed. So, in this research, it is estimated that the influence to the characteristics of landcover caused by the river flood and beach erosion.The result of this study, we generated the geographic information for water-related disaster, and considered the relation with present condition of landuse.

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 Rebuilding the operation scheme of public transportation is a recent topic of discussion in Japan becausethe number of passengers is decreasing especially in rural areas. However, the discussion dependingon the knowledge from transport data such as tendency of boarding and alighting volume, its dailyvariation and so on is only a few cases especially in rural areas of Japan. On the other hand, recently, usage of smart cards for public transport purchases is growing even in the rural area. That means the data of public transport passengers are continually collected, and it can be fundamental information to discuss about public transport marketing strategies. This research empirically analyzes variations in trip patterns to understand how passengers' daily travel patterns vary temporally and spatially among one month using smart card data measured in Kochi City. Spatial and Temporal Trip Pattern Dependency what is ratio between appearance of combination of most frequent usage hour and bus/tram stops and total tripped days is defined for all passengers from collected smart card data. The relationship between spatial and temporal trip pattern dependency showed that most of passengers doesn't have specific trip pattern, but children card holders tends to trip same hour and route. Especially elderly passengers tend to do not have any specific trip pattern. They are travelling by different hours and route when they use public transport. Using Spatial and Temporal Trip Pattern Dependency and other users' attribution information prepared from smart card data, groups of the passengers are generated by cluster analysis. The results shows fundamental information focusing on groups of public transport passengers to discuss about public transport marketing scheme, and also this could be fundamental knowledge to discuss more dynamic and individual operation schemes.

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 In this research, a format for the circulation of information about EV/PHV charging stations is developed. A pilot system in order to collect and distribute the information is also developed. By using the information, field operational tests with the Joint-Research members including automobile manufactures and map providers are performed. Based on these results, social benefits by collecting and distributing information about EV /PHV Charging Stations are evaluated.

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 In the civil engineering construction industry, two or more companies often form a joint venture in alliance with each other in constructing a large-scale structure. However, in order to create a corporate alliance, it is necessary to select appropriate companies by analyzing diverse pieces of information including their alliance records and technologies. Thus studies are made on methods for evaluating candidate partner companies based on the analysis results of the link structure of Web pages as well as of the web contents through natural language processing. However, the existing method has a problem in that the relationship between companies are not taken into consideration and consequently, therefor it is not possible to take the advantages of alliance into consideration. This study evaluates relationship between companies based on the technology division of the company obtained from its project achievement and the collaboration achievement between companies. Then, validity of the classification results is verified by classifying companies by visualizing based on the evaluation results, and comparing them with the past achievement of forming joint ventures.

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 High accuracy satellite positioning systems equipped with the new positioning method and new satellites will perform in the near future. There is a possibility to detect the precise vehicle trajectory in the lane using high accurate positioning method as RTK-GPS. The purpose of this study is to verity the availability of precise vehicle trajectory to estimate individual driving characteristics. Experimental results showed that the individual difference in running position and velocity on the direct path and curved path could be detected by the precise vehicle trajectory using RTK-GPS

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 In the construction projects of Japan, it is an important subject to construct the environment where three-dimensional computer aided design data (3D CAD data) is used for continuous acquisition and life-cycle support (CALS/EC), construction information modeling (CIM), and information integrated construction. Primarily two-dimensional drawing data are now used in the design and construction stages with the use of 3D information during these stages having only recently started.
 In this paper, a 3D CAD engine using a data model based on ISO 10303 is proposed for creating and modifying 3D CAD data. There are three design concepts required for applying the information to international construction projects: data models based on ISO 10303, parametric modeling, and the consideration of temporal attributes. For a case study, 3D models of various concrete structures are generated with the proposed 3D CAD engine and the software functionality is tested.

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 In recent years, as digital cameras have become widespread and it is getting common to equip a mobile phone or a smart phone with a camera, opportunities to treat digital images are rapidly increasing regardless of individuals or companies. This is particularly remarkable in the field of civil engineering; enormous-scale image databases are being built such as of highway images shot by a mobile mapping system, satellite photos, and textured images of three-dimensional models. However, the more these image databases become enormous, the more it will be difficult to find out the image of interest. This research develops a universal partial image retrieval system by creating templates for characteristic of pictorial images such as color information and position relationships and calculating the relevance between templates. Then the system is applied to the real problem and to verify its effectiveness on an enormous-scale image database.

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