関連論文リスト - Publications -

論文リスト
- Publications -

人の流れに関する様々な研究が行われております。
以下に、これまで発表した論文をご紹介します。

2024年度

  • Garcia-Gabilondo, S., Shibuya, Y. and Sekimoto, Y.: Enhancing geospatial retail analysis by integrating synthetic human mobility simulations. Computers, Environment and Urban Systems, 108, p.102058, 2024.
  • Kashiyama, T., Pang, Y., Shibuya, Y., Yabe, T. and Sekimoto, Y.: Nationwide synthetic human mobility dataset construction from limited travel surveys and open data. Computer‐Aided Civil and Infrastructure Engineering, 39(21), pp.3337-3353, 2024.
  • Ma, J., Shibuya, Y., Pang, Y., Omata, H. and Sekimoto, Y.: A cost-and-effect simulation model for compact city approaches: A case study in Japan. Cities, 152, p.105212, 2024.
  • Yabe, T., Tsubouchi, K., Shimizu, T., Sekimoto, Y., Sezaki, K., Moro, E. and Pentland, A.: YJMob100K: City-scale and longitudinal dataset of anonymized human mobility trajectories. Scientific Data, 11(1), p.397, 2024.
  • Yabe, T., Luca, M., Tsubouchi, K., Lepri, B., Gonzalez, M.C. and Moro, E.: Enhancing human mobility research with open and standardized datasets. Nature Computational Science, 4(7), pp.469-472, 2024.
  • Xue, J., Yabe, T., Tsubouchi, K., Ma, J. and Ukkusuri, S.V.: Predicting individual irregular mobility via web search-driven bipartite graph neural networks. IEEE Transactions on Knowledge and Data Engineering, 2024.
  • Yabe, T., García Bulle Bueno, B., Frank, M.R., Pentland, A. and Moro, E.: Behaviour-based dependency networks between places shape urban economic resilience. Nature human behaviour, pp.1-11, 2024.
  • Liu, Z., Pang, Y. and Sekimoto, Y.: A Preliminary Study on Dynamic Urban Knowledge Graph Construction using Heterogeneous Spatio-temporal Data. In 2024 IEEE International Conference on Big Data (BigData) (pp. 6834-6841), 2024.
  • Cai, M., Pang, Y. and Sekimoto, Y.: Explainable Hierarchical Urban Representation Learning for Commuting Flow Prediction. In Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems (pp. 573-576), 2024.
  • Zheng, H., Zhao, C., Ogawa, Y., Shibasaki, R. and Fujiwara, N.: Mobility Patterns of Trailers Around International Container Terminals: A Case Study in Sendai Port, Japan. In 2024 IEEE International Conference on Big Data (BigData) (pp. 6823-6833), 2024.
  • Zhang, K., Pang, Y., Zhang, Y. and Sekimoto, Y.: MobGLM: A Large Language Model for Synthetic Human Mobility Generation. In Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems (pp. 629-632), 2024.
  • Zhang, Y., Zhang, K., Pang, Y. and Sekimoto, Y.: Agentic Large Language Models for Generating Large-Scale Urban Daily Activity Patterns. In 2024 IEEE International Conference on Big Data (BigData) (pp. 6815-6822), 2024.
  • Ma, J., Garcia, S., Torbjörnsson, C., Sun, C., Wu, Z., Shibuya, Y. and Sekimoto, Y.: Socioeconomic Disparities in Heat Exposure and Mitigation Based on Human Mobility in India. Book of Abstracts Netmob2024, 2024.
  • Sun, C., Shibuya, Y. and Sekimoto, Y.: Generation gaps in activity space segregations: A case study of Tokyo metropolitan areas using human mobility GPS data . Book of Abstracts Netmob2024, 2024.
  • 足立陽紀, 龐岩博, 関本義秀: 実データと擬似データの比較による高精度な人流シミュレーションモデルの改善. 第33回地理情報システム学会学術研究発表大会講演論文集, 2024.
  • Liu, L., Ma, J., Pang, Y., Shibuya, Y. and Sekimoto, Y.: Exploring Consumer Behavior in Tokyo based on Mobility Data: Development of a New Shopping Center. 第33回地理情報システム学会学術研究発表大会講演論文集, 2024.

2023年度

  • Yabe, T., Bueno, B.G.B., Dong, X., Pentland, A. and Moro, E.: Behavioral changes during the COVID-19 pandemic decreased income diversity of urban encounters. Nature communications, 14(1), p.2310, 2023.
  • Zhang, K., Pang, Y. and Sekimoto, Y.: Deep Learning Approach to Logistics Trips Generation: Enhancing Pseudo People Flow with Agent-Based Modeling. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC) (pp. 2535-2542), 2023.
  • Pang, Y., Ferry, P. and Zhang, K.: Synthetic Network Traffic Data Generation using Deep Generative Models. NetMob 2023 Book of Abstracts, 2023.
  • Zhang, Y., Zhang, K., Pang, Y. and Sekimoto, Y.: Towards Pseudo People Flow: Developing a Deep Generative Model based on PT Data to Reproduce Large-Scale Daily People Activity Profiles. 第32回地理情報システム学会学術研究発表大会講演論文集, 2023.

2022年度

  • Tsuboi, K., Fujiwara, N. and Itoh, R.: Influence of trip distance and population density on intra-city mobility patterns in Tokyo during COVID-19 pandemic. PLoS One, 17(10), p.e0276741, 2022.
  • Kumar, A., Kashiyama, T., Maeda, H., Omata, H. and Sekimoto, Y.: Real-time citywide reconstruction of traffic flow from moving cameras on lightweight edge devices. ISPRS Journal of Photogrammetry and Remote Sensing, 192, pp.115-129, 2022.
  • Kajiwara, K., Ma, J., Seto, T., Sekimoto, Y., Ogawa, Y. and Omata, H.: Development of current estimated household data and agent-based simulation of the future population distribution of households in Japan. Computers, Environment and Urban Systems, 98, p.101873, 2022.
  • Aoki, T., Fujishima, S. and Fujiwara, N.: Urban spatial structures from human flow by Hodge–Kodaira decomposition. Scientific reports, 12(1), p.11258, 2022.
  • Yabe, T., Jones, N.K., Rao, P.S.C., Gonzalez, M.C. and Ukkusuri, S.V.: Mobile phone location data for disasters: A review from natural hazards and epidemics. Computers, Environment and Urban Systems, 94, p.101777, 2022.
  • Cai, M., Pang, Y. and Sekimoto, Y.: Spatial attention based grid representation learning for predicting origin–destination flow. In 2022 IEEE International Conference on Big Data (Big Data) (pp. 485-494), 2022.
  • Zhao, C., Ogawa, Y., Chen, S. and Sekimoto, Y.: Scene Level People Flow Trend Prediction by Swin Transform. In IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium (pp. 2434-2437), 2022.
  • Tewari, A., Pang, Y. and Sekimoto, Y.: Uncertainty of Traffic Congestion Estimation Using Nationwide Pseudo Trip Data and Agent-Based Simulation. In 2022 IEEE International Conference on Big Data (Big Data) (pp. 3854-3863), 2022.
  • Pang, Y. and Sekimoto, Y.: Deep Learning for Destination Choice Modeling: A Fundamental Approach for National Level People Flow Reconstruction. In 2022 IEEE International Conference on Big Data (Big Data) (pp. 1900-1905), 2022.
  • Xue, J., Yabe, T., Tsubouchi, K., Ma, J. and Ukkusuri, S.: Multiwave covid-19 prediction from social awareness using web search and mobility data. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 4279-4289), 2022.
  • 笠原有貴, 関本義秀, 樫山武浩, 瀬崎薫: ベクトルタイル技術を用いた全国規模の人流データの効率的な可視化. GIS-理論と応用, 30(2):85-90, 2022.

2021年度

  • Cai, M., Pang, Y., Kashiyama, T. and Sekimoto, Y.: Simulating human mobility with agent-based modeling and particle filter following mobile spatial statistics. In Proceedings of the 29th International Conference on Advances in Geographic Information Systems (pp. 411-414), 2021.
  • Pang, Y., Kashiyama, T. and Sekimoto, Y.: Development of a reinforcement learning based agent model and people flow data to Mega Metropolitan Area. In 2021 IEEE International Conference on Big Data (Big Data) (pp. 3755-3759), 2021.
  • Yabe, T., Tsubouchi, K., Sekimoto, Y. and Ukkusuri, S.V.: Early warning of COVID-19 hotspots using human mobility and web search query data. Computers, Environment and Urban Systems, 92, p.101747, 2021.

2020年度

  • Fujishima, S., Fujiwara, N., Akiyama, Y., Shibasaki, R. and Sakuramachi, R.: The size distribution of ‘cities’ delineated with a network theory‐based method and mobile phone GPS data. International Journal of Economic Theory, 16(1), pp.38-50, 2020.
  • Yabe, T., Tsubouchi, K., Fujiwara, N., Sekimoto, Y. and Ukkusuri, S.V.: Understanding post-disaster population recovery patterns. Journal of the Royal Society Interface, 17(163), p.20190532, 2020.
  • Ogawa, Y., Sato, T. and Sekimoto, Y.: Creation of a Model for Estimating the Home-return Rate of Evacuees Using Mobile Phone Movement Histories and Its Application to the Nankai Trough Earthquake. AGILE: GIScience Series, 1, p.17, 2020.
  • Pang, Y., Kashiyama, T., Yabe, T., Tsubouchi, K. and Sekimoto, Y.: Development of people mass movement simulation framework based on reinforcement learning. Transportation research part C: emerging technologies, 117, p.102706, 2020.
  • Yabe, T., Tsubouchi, K., Fujiwara, N., Wada, T., Sekimoto, Y. and Ukkusuri, S.V.: Non-compulsory measures sufficiently reduced human mobility in Tokyo during the COVID-19 epidemic. Scientific reports, 10(1), p.18053, 2020.
  • Pang, Y., Tsubouchi, K., Yabe, T. and Sekimoto, Y.: Intercity simulation of human mobility at rare events via reinforcement learning. In Proceedings of the 28th International Conference on Advances in Geographic Information Systems (pp. 293-302), 2020.

2019年度

  • Joo, S., Kashiyama, T., Sekimoto, Y. and Seto, T.: An analysis of factors influencing disaster mobility using location data from smartphones: Case study of western Japan flooding. Journal of Disaster Research, 14(6), pp.903-911, 2019.
  • Yasumoto, S., Jones, A.P., Oyoshi, K., Kanasugi, H., Sekimoto, Y., Shibasaki, R., Comber, A. and Watanabe, C.: Heat exposure assessment based on individual daily mobility patterns in Dhaka, Bangladesh. Computers, Environment and Urban Systems, 77, p.101367, 2019.
  • KYAING, Lwin, K.K. and Sekimoto, Y.: Identification of Transportation Mode and Transit Behaviour from Mobile CDRs Data: A Case of Yangon City. Journal of the Eastern Asia Society for Transportation Studies, 13, pp.841-860, 2019.
  • Aung, T.,  Lwin, K.K. and Sekimoto, Y.: Identification and classification of land use types in yangon city by using mobile call detail records (cdrs) data. Journal of the Eastern Asia Society for Transportation Studies, 13, pp.1114-1133, 2019.
  • OO, N.T.K., Lwin, K.K. and Sekimoto, Y.: Estimation of Intercity Travel Pattern and Impact on Yangon-Pathein Road between Ayeyarwady Region and Yangon Region Using Call Detail Record. Journal of the Eastern Asia Society for Transportation Studies, 13, pp.277-297, 2019.
  • Joo, S.H., Ogawa, Y. and Sekimoto, Y.: Decision-making system for road-recovery considering human mobility by applying deep Q-network. In 2019 IEEE International Conference on Big Data (Big Data) (pp. 4075-4084), 2019.

2018年度

  • Lwin, K.K., Sekimoto, Y. and Takeuchi, W.: Development of GIS integrated big data research toolbox (BigGIS-RTX) for Mobile CDR data processing in disasters management. Journal of Disaster Research, 13(2), pp.380-386, 2018.
  • Zin, T.A., Lwin, K.K. and Sekimoto, Y.: Estimation of originating-destination trips in Yangon by using big data source. Journal of Disaster Research, 13(1), pp.6-13, 2018.
  • Lwin, K.K. and Sekimoto, Y.: Mapping the spatial distribution patterns of personal time spent based on trip purpose. International Journal of Applied Geospatial Research (IJAGR), 9(2), pp.1-13, 2018.
  • Kashiyama, T., Sekimoto, Y., Kuwahara, M., Mitani, T. and Koshimura, S.: Hybrid System for Generating Data on Human Flow in a Tsunami Disaster. Journal of Disaster Research, 13(2), pp.347-357, 2018.
  • Jiang, R., Song, X., Fan, Z., Xia, T., Chen, Q., Chen, Q. and Shibasaki, R.: Deep ROI-based modeling for urban human mobility prediction. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2(1), pp.1-29, 2018.
  • Ranjit, S., Witayangkurn, A., Nagai, M. and Shibasaki, R.: Agent-based modeling of taxi behavior simulation with probe vehicle data. ISPRS International Journal of Geo-Information, 7(5), p.177, 2018.
  • Batran, M., Mejia, M.G., Kanasugi, H., Sekimoto, Y. and Shibasaki, R.: Inferencing human spatiotemporal mobility in greater Maputo via mobile phone big data mining. ISPRS International Journal of Geo-Information, 7(7), p.259, 2018.
  • Ogawa, Y., Sato, T., Akiyama, Y., Shibasaki, R. and Sekimoto, Y.: Developing a model for estimating the home return of evacuees based on the 2011 Tohoku earthquake tsunami—Utilizing mobile phone GPS big data. In Advances and New Trends in Environmental Informatics: Managing Disruption, Big Data and Open Science (pp. 227-240), Springer International Publishing, 2018.
  • Lwin, K.K., Sekimoto, Y. and Takeuchi, W.: Estimation of hourly link population and flow directions from mobile CDR. ISPRS international journal of geo-information, 7(11), p.449, 2018.
  • Yabe, T., Sekimoto, Y., Tsubouchi, K. and Ikemoto, S.: Cross-comparative analysis of evacuation behavior after earthquakes using mobile phone data. PLoS one, 14(2), p.e0211375, 2018.
  • Batran, M., Kanasugi, H., Kashiyama, T., Sekimoto, Y. and Shibasaki, R.: Sensing Population Mobility through City Boundary in Greater Maputo via Mobile Phone Big Data Mining. In 2018 IEEE World Congress on Services (SERVICES) (pp. 9-10), 2018.
  • Batran, M., Arai, A., Kanasugi, H., Cumbane, S., Grachane, C., Sekimoto, Y. and Shibasaki, R.: Urban travel time estimation in greater maputo using mobile phone big data. In 2018 IEEE 20th Conference on Business Informatics (CBI) (Vol. 2, pp. 122-127), 2018.
  • Batran, M., Mejia, M.G., Sekimoto, Y. and Shibasaki, R.: Inference of Human Spatiotemporal Mobility in Greater Maputo by Mobile Phone Big Data Mining. In ATT@ IJCAI (pp. 1-8), 2018.
  • Méneroux, Y., Kanasugi, H., Saint Pierre, G., Le Guilcher, A., Mustière, S., Shibasaki, R. and Kato, Y.: Detection and localization of traffic signals with gps floating car data and random forest. In 10th International Conference on Geographic Information Science (GIScience 2018) (pp. 11-1). Schloss Dagstuhl–Leibniz-Zentrum für Informatik, 2018.
  • Pang, Y., Tsubouchi, K., Yabe, T. and Sekimoto, Y.: Replicating urban dynamics by generating human-like agents from smartphone GPS data. In Proceedings of the 26th ACM sigspatial international conference on advances in geographic information systems (pp. 440-443), 2018.
  • Yabe, T., Tsubouchi, K. and Sekimoto, Y.: Fusion of terrain information and mobile phone location data for flood area detection in rural areas. In 2018 IEEE International Conference on Big Data (Big Data) (pp. 881-890), 2018.

2017年度

  • Yabe, T., Tsubouchi, K. and Sekimoto, Y.: CityFlowFragility: Measuring the fragility of people flow in cities to disasters using GPS data collected from smartphones. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 1(3), pp.1-17, 2017.
  • Kashiyama, T., Pang, Y. and Sekimoto, Y.: Open PFLOW: Creation and evaluation of an open dataset for typical people mass movement in urban areas. Transportation research part C: emerging technologies, 85, pp.249-267, 2017.
  • Lwin, K.K., Sekimoto, Y. and Takeuchi, W.: Mobile CDR data disaggregation for home users based multitemporal grid square population estimation. In International Conference on Computers in Urban Planning and Urban Management (CUPUM 2017), 2017.
  • Kyaing, K., Lwin, K. and Sekimoto, Y.: Human mobility patterns for different regions in Myanmar based on CDRs data. IPTEK Journal of Proceedings Series, 3(6), 2017.
  • Kyaing, K.L. and Sekimoto, Y.: Estimation of trip generation in Yangon city by using CDRs data. In Proc. of the Eastern Asia Society for Transportation Studies, Vol. 11, 2017.
  • Pang, Y., Tsubouchi, K., Yabe, T. and Sekimoto, Y.: Modeling and reproducing human daily travel behavior from GPS data: A Markov Decision Process approach. In Proceedings of the 1st ACM SIGSPATIAL Workshop on Prediction of Human Mobility, pp. 1-9, 2017.
  • Batran, M.R., Kanasugi, H., Sekimoto, Y. and Shibasaki, R.: SPATIO-TEMPORAL ANALYSIS OF HUMAN MOBILITY IN CAIRO USING PERSON TRIP SURVEY DATA. The 38th Asian Conference on Remote Sensing, 2017.

2016年度

  • Song, X., Zhang, Q., Sekimoto, Y., Shibasaki, R., Yuan, N.J. and Xie, X.: Prediction and simulation of human mobility following natural disasters. ACM Transactions on Intelligent Systems and Technology (TIST), 8(2), pp.1-23, 2016.
  • Yabe, T., Tsubouchi, K., Sudo, A. and Sekimoto, Y.: Estimating Evacuation Hotspots using GPS data: What happened after the large earthquakes in Kumamoto, Japan. In Proc. of the 5th International Workshop on Urban Computing, Vol. 81, pp. 1-5, 2016.
  • Sekimoto, Y., Sudo, A., Kashiyama, T., Seto, T., Hayashi, H., Asahara, A., Ishizuka, H. and Nishiyama, S.: Real-time people movement estimation in large disasters from several kinds of mobile phone data. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, pp. 1426-1434, 2016.
  • Sudo, A., Kashiyama, T., Yabe, T., Kanasugi, H., Song, X., Higuchi, T., Nakano, S.Y., Saito, M. and Sekimoto, Y.: Particle filter for real-time human mobility prediction following unprecedented disaster. In Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 1-10, 2016.
  • Yabe, T., Tsubouchi, K., Sudo, A. and Sekimoto, Y.: Predicting irregular individual movement following frequent mid-level disasters using location data from smartphones. In Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 1-4, 2016.
  • Yabe, T., Tsubouchi, K., Sudo, A. and Sekimoto, Y.: A framework for evacuation hotspot detection after large scale disasters using location data from smartphones: case study of kumamoto earthquake. In Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems,  pp. 1-10, 2016.

2015年度

  • Phithakkitnukoon, S., Horanont, T., Witayangkurn, A., Siri, R., Sekimoto, Y. and Shibasaki, R.: Understanding tourist behavior using large-scale mobile sensing approach: A case study of mobile phone users in Japan. Pervasive and Mobile Computing, 18, pp.18-39, 2015.
  • Song, X., Zhang, Q., Sekimoto, Y., Shibasaki, R., Yuan, N.J. and Xie, X.: A simulator of human emergency mobility following disasters: Knowledge transfer from big disaster data. In Proceedings of the AAAI Conference on Artificial Intelligence, p.730-736, 2015.
  • Yabe, T., Sekimoto, Y., Kanasugi, H. and Kashiyama, T.: Making Real-Time Predictions of People’s Irregu-lar Movement in a Metropolitan Scale under Dis-aster Situations. In International Conference on Computers in Urban Planning and Urban Management (CUPUM2015), 2015.
  • 矢部貴大, 関本義秀, 樫山武浩, 金杉洋, 須藤明人: パーティクルフィルタを用いた災害時におけるリアルタイムな人流推定手法. 交通工学研究発表会論文集, 35:597-605, 2015.
  • 関本義秀, 樫山武浩, 長谷川瑶子, 金杉洋: スパースな携帯電話通話履歴を用いたリンク交通量の推定~ ダッカの事例. 交通工学論文集, 1(4):A_1-8, 2015.
  • 長谷川瑶子, 関本義秀, 金杉洋, 樫山武浩: 同化手法を用いたスパースな携帯基地局情報に基づく人の移動推定. 交通工学論文集, 1(4):A_9-17, 2015.
  • 須藤明人, 樫山武浩, 矢部貴大, 関本義秀: 携帯電話データによる災害時のリアルタイムな人の分布の推定のためのナッジング項を持つパーティクルフィルタの提案. 交通工学研究発表会論文集, 35:229-36, 2015.

2014年度

  • Song, X., Zhang, Q., Sekimoto, Y. and Shibasaki, R.: Intelligent system for urban emergency management during large-scale disaster. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 28, pp.458-464, 2014.
  • Song, X., Zhang, Q., Sekimoto, Y. and Shibasaki, R.: Prediction of human emergency behavior and their mobility following large-scale disaster. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 5-14, 2014.
  • Takahiro N., Yuki A., Hiroshi K., Horanont, T., Ryosuke S., and Yoshihide S.: Estimate of Human Demographic Attributes Using Person Flow Dataset. The International Symposium on City Planning 2014, 2014.
  • Hasegawa, Y., Sekimoto, Y., Kashiyama, T. and Kanasugi, H.: Transportation melting pot Dhaka: Road-link based traffic volume estimation from sparse CDR data. In Proceedings of the First International Conference on IoT in Urban Space, pp.105-107, 2014.
  • 若生凌, 関本義秀, 金杉洋, 柴崎亮介: GPS データを用いた東日本大震災における人々の経路選択行動分析. 土木学会論文集 D3 (土木計画学), 70(5):I_681-8, 2014.

2013年度

  • Sekimoto, Y., Watanabe, A., Nakamura, T., Kanasugi, H. and Usui, T. : Combination of spatio-temporal correction methods using traffic survey data for reconstruction of people flow. Pervasive and Mobile Computing, 9(5), pp.629-642, 2013.
  • Song, X., Zhang, Q., Sekimoto, Y., Horanont, T., Ueyama, S. and Shibasaki, R.: Intelligent system for human behavior analysis and reasoning following large-scale disasters. IEEE Intelligent Systems, 28(4), pp.35-42, 2013.
  • Horanont, T., Witayangkurn, A., Sekimoto, Y. and Shibasaki, R.: Large-scale auto-GPS analysis for discerning behavior change during crisis. IEEE Intelligent Systems, 28(4), pp.26-34, 2013.
  • Horanont, T., Phithakkitnukoon, S., Leong, T.W., Sekimoto, Y. and Shibasaki, R.: Weather effects on the patterns of people’s everyday activities: a study using GPS traces of mobile phone users. PloS one, 8(12), p.e81153, 2013.
  • Sekimoto Y: Relationship of People and Infrastructure during the 3.11 Earthquake with Information Technology as Mediating Channel. Journal of JSCE 1(1):276-85, 2013.
  • Kurokawa, M., Watanabe, T., Muramatsu, S., Kanasugi, H., Sekimoto, Y. and Shibasaki, R.: Extracting People’s Stays from Cellular Network Data. NetMob2013, 2013.
  • Witayangkurn, A., Horanont, T., Ono, N., Sekimoto, Y. and Shibasaki, R.: Trip reconstruction and transportation mode extraction on low data rate GPS data from mobile phone. In Proceedings of the international conference on computers in urban planning and urban management (CUPUM 2013), 2013.
  • Horanont, T., Witayangkurn, A., Sekimoto, Y. and Shibasaki, R.: Expose urban activities from human flow. In Proceedings of the international conference on computers in urban planning and urban management (CUPUM 2013), 2013.
  • 中村敏和, 関本義秀, 薄井智貴, 柴崎亮介: パーティクルフィルターを用いた 都市圏レベルの人の流れの推定手法の構築. 土木学会論文集 D3 (土木計画学), 69(3):227-36, 2013.
  • 生形嘉良, 関本義秀: 大規模・長期間のGPSデータによる観光統計調査の活用可能性ー石川県を事例にー. 土木学会論文集 D3 (土木計画学), 69(5):I_345-52, 2013.
  • 関本義秀, 西澤明, 山田晴利, 柴崎亮介, 熊谷潤, 樫山武浩, 相良毅, 嘉山陽一, 大伴真吾: 東日本大震災復興支援調査アーカイブ構築によるデータ流通促進. GIS-理論と応用, 21(2):87-95, 2013.
  • 関本義秀, 瀬戸寿一: 地理空間情報におけるオープンデータの動向. 情報処理(特集 オープンデータ活用), 54(12):1221-5, 2013.
  • 新井亜弓, 関本義秀: 大規模人口流動データの利活用について. 写真測量とリモートセンシング, 52(6):327-31, 2013.
  • 関本義秀: 人々の流動データの基礎的な処理・分析手法について. 写真測量とリモートセンシング, 52(6):321-6, 2013.

2012年度

  • Sekimoto, Y., Matsubayashi, Y., Yamada, H., Imai, R., Usui, T. and Kanasugi, H. : Lightweight lane positioning of vehicles using a smartphone GPS by monitoring the distance from the center line. In 2012 15th International IEEE Conference on Intelligent Transportation Systems, (pp. 1561-1565), 2012.
  • Nakamura, T., Sekimoto, Y., Usui, T. and Shibasaki, R.: Data-Oriented Algorithm for Route Choice Set Generation in a Metropolitan Area with Mobile Phone GPS Data. ISPRS Annals of the Photogrammetry. Remote Sensing and Spatial Information Sciences, 1, pp.111-116, 2012.
  • 秋山祐樹, 金杉洋, 関本義秀, 柴崎亮介: 住宅地図データを用いた人々の時刻別空間位置の精細化. 第 32 回交通工学研究発表会論文集, 317-23, 2012.
  • 金杉洋, 黒川茂莉, 村松茂樹, 関本義秀: 携帯電話基地局通信情報の行動分析への適用可能性把握. 第 32 回交通工学研究発表会論文集, 309-15, 2012.
  • 関本義秀, 薄井智貴, 金杉洋, 増田祐介: 都市空間における効率的な動線解析の共通基盤のあり方について. 土木学会論文集 F3 (土木情報学), 67(2):I_170-80, 2012.

2011年度

  • Sekimoto, Y., Shibasaki, R., Kanasugi, H., Usui, T. and Shimazaki, Y.: Pflow: Reconstructing people flow recycling large-scale social survey data. IEEE Pervasive Computing, 10(4), pp.27-35, 2011.
  • Sekimoto, Y., Watanabe, A., Nakamura, T., Usui, T. and Kanasugi, H.: Digital archiving of people flow using person trip data of developing cities. In Proceedings of The First Workshop on Pervasive Urban Applications, 2011.

2010年度

  • Watanabe, A., Nakamura, T., Usui, T., Sekimoto, Y. and Sibasaki, R.: A Study for Reconstruction of People Flow in Asian Cities Using JICA Person Trip Data. Papers and Proceedings of Asia GIS, CD-ROM, 2010.
  • Sekimoto, Y., Kanasugi, T., Nakamura, T. and Usui, T.: Spatio-temporal route cashing from OD points in reconstruction of people flow. Papers and Proceedings of Asia GIS, CD-ROM, 2010.
  • Nakamura, T., Sekimoto, Y., Usui, T. and Sibasaki, R.: A Study on Data Assimilation of People Flow in Kanto Urban Area. Papers and Proceedings of Asia GIS, CD-ROM, 2010.
  • 島崎康信, 関本義秀, 柴崎亮介: 個人属性の情報量に応じたトリップ目的の判別精度に関する研究ーパーソントリップ調査の時空間内挿データと決定木分析を用いてー. 都市計画学会都市計画論文集, Vol.45, No.3, pp.163-168, 2010.
  • 薄井智貴, 関本義秀, 金杉洋, 南佳孝, 柴崎亮介: 都市圏パーソントリップデータの比較と時空間内挿処理の実現. 土木計画学論文集, Vol.27(3), pp. 569-77, 2010.
  • 関本義秀, 中村敏和, 薄井智貴, 金杉洋: 海外における人々の時空間位置の詳細化－ハノイのPT調査を事例に. 交通工学研究発表会, CD-ROM, 2010.
  • 関本義秀, 薄井智貴, 島崎康信, 南佳孝, 柴崎亮介 :東京都市圏パーソントリップ調査による交通特性分析とデータ活用ニーズ. 土木計画学研究・講演集, Vol.41, CD-ROM, 2010.
  • 中村敏和, 薄井智貴, 関本義秀, 柴崎亮介: パーティクルフィルタによる歩行者GPSオフラインマップマッチングアルゴリズム.  土木計画学研究・講演集, Vol.41, CD-ROM, 2010.

2009年度

  • 薄井智貴, 金杉洋, 関本義秀, 南佳孝: 都市圏パーソントリップ調査データのクレンジングと時空間内挿, 土木計画学研究・講演集, Vol.40 (CD-ROM), 2009.
  • 島崎康信, 関本義秀, 柴崎亮介, 秋山祐樹:  人の流れから算出される滞在時間と商業統計の関係性についての研究. 第18回地理情報システム学会講演論文集, Vol.18, pp.239-242, 2009.
  • 薄井智貴, 金杉洋, 関本義秀, 南佳孝, 柴崎亮介, 中野敦: 動線解析プラットフォームによる東京都市圏パーソントリップ調査データの時空間内挿の実現とその利用. 第18回地理情報システム学会講演論文集, Vol.18, pp.541-545, 2009.
  • 島崎康信, 関本義秀, 柴崎亮介, 秋山祐樹: 人の流れによる時間帯別人口と店舗数との相関関係についての研究. 都市計画学会都市計画論文集, Vol.44, No.3, pp.781-786, 2009.

2008年度

  • 関本義秀, 菊地英一, 佐藤圭一, 秋山祐樹: パーソントリップデータを活用した人の流れの時空間的な詳細化. 第28回交通工学研究発表会論文集, pp.197-200, 2008.

ページの先頭へ