論文 - 山形　与志樹

Spatiotemporal Heatwave Risk Modeling Combining Multiple Observations

Murakami D., Yamagata Y., Yoshida T., Matsui T.

International Geoscience and Remote Sensing Symposium (IGARSS) （International Geoscience and Remote Sensing Symposium (IGARSS)）     5516 - 5519 2019年07月

ISSN  9781538691540

　概要を見る

Urban heatwave is increasingly severe as the global warming advances. Even worse, in Tokyo, an increasing proportion of residences are vulnerable against heats under the aging society. Today, heatwave monitoring is an emergent task toward climate adaptive urban development. Our final goal is developing a system to monitor real-time and micro-scale heatwave risk in Tokyo. To achieve it, we performed the following observation experiments: airborne monitoring, monitoring from the Tokyo Sky Tree, and micro-scale monitoring censoring inside and outside comforts. A method to combine these multi-scale information is developed to estimate micro-scale spatiotemporal behavior on heatwave risks. Based on the result, it is discussed how we can achieve the real-time and micro-scale heatwave monitoring, and make Tokyo more risk adaptive.

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A GPS-Based Simple Evaluation Simulation Approach: Case Study in Joso, Japan

Murakami D., Matsui T., Yoshida T., Yamagata Y.

International Geoscience and Remote Sensing Symposium (IGARSS) （International Geoscience and Remote Sensing Symposium (IGARSS)）     5636 - 5637 2019年07月

ISSN  9781538691540

　概要を見る

This study attempts to simulate evaluation flow after the flooding in the Kanto-Tohoku heavy rain in September 2015, using a mobile GPS data. A simple Monte Carlo approach is introduced to simulate micro-scale people flow from spatially sparse GPS information. The simulation result shows that GPS data effectively recovers people flow after flooding even if the simulation approach is very simple.

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Pathway using WUDAPT's Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling

Ching J., Aliaga D., Mills G., Masson V., See L., Neophytou M., Middel A., Baklanov A., Ren C., Ng E., Fung J., Wong M., Huang Y., Martilli A., Brousse O., Stewart I., Zhang X., Shehata A., Miao S., Wang X., Wang W., Yamagata Y., Duarte D., Li Y., Feddema J., Bechtel B., Hidalgo J., Roustan Y., Kim Y.S., Simon H., Kropp T., Bruse M., Lindberg F., Grimmond S., Demuzure M., Chen F., Li C., Gonzales-Cruz J., Bornstein B., He Q., Tzu-Ping , Hanna A., Erell E., Tapper N., Mall R.K., Niyogi D.

Urban Climate （Urban Climate）  28 2019年06月

ISSN  22120955

　概要を見る

The WUDAPT (World Urban Database and Access Portal Tools project goal is to capture consistent information on urban form and function for cities worldwide that can support urban weather, climate, hydrology and air quality modeling. These data are provided as urban canopy parameters (UCPs)as used by weather, climate and air quality models to simulate the effects of urban surfaces on the overlying atmosphere. Information is stored with different levels of detail (LOD). With higher LOD greater spatial precision is provided. At the lowest LOD, Local Climate Zones (LCZ)with nominal UCP ranges is provided (order 100 m or more). To describe the spatial heterogeneity present in cities with great specificity at different urban scales we introduce the Digital Synthetic City (DSC)tool to generate UCPs at any desired scale meeting the fit-for-purpose goal of WUDAPT. 3D building and road elements of entire city landscapes are simulated based on readily available data. Comparisons with real-world urban data are very encouraging. It is customized (C-DSC)to incorporate each city's unique building morphologies based on unique types, variations and spatial distribution of building typologies, architecture features, construction materials and distribution of green and pervious surfaces. The C-DSC uses crowdsourcing methods and sampling within city Testbeds from around the world. UCP data can be computed from synthetic images at selected grid sizes and stored such that the coded string provides UCP values for individual grid cells.

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Flood Area Estimation Using Personal Location Data - Case Study of Japan Floods in 2018

Hiroi K., Yoshida T., Yamagata Y., Kawaguchi N.

2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019 （2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019）     285 - 291 2019年03月

ISSN  9781538691519

　概要を見る

This research proposes a flood area estimation method in urban areas using personal location data. Many studies have investigated the estimation of flood levels; however, the majority of these previous works are based on the flood monitoring data. The main cause of flood disaster death is drowning due to evacuation delay in the area where observation equipment is not installed, so it is difficult to estimate flood occurrence by the previous method based only on monitoring data. In this research, we propose an estimation method that does not rely on monitoring data and instead estimates flood areas using GPS data collected from smartphones owned by the affected people. This method detects anomaly areas to analyze temporal and spatial changes of an area where a personal movement during a flooding event differs from that during regular times from personal location data. For anomaly detection, we use a dynamic time warping method with fixed window size and inequality metrics to estimate the area where an anomaly event occurred in 2 km grids. We applied this method to Kurashiki city, Okayama Prefecture, where there 52 people died during a flood that occurred in Japan in 2018. Our method found that, at the flooding time, the anomaly occurrence was estimated correctly in the area where inundation actually occurred.

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Planning and Monitoring of Building Energy Demands under Uncertainties by Using IoT Data

Chang S., Castro-Lacouture D., Matsui K., Yamagata Y.

Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019 （Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019）     211 - 218 2019年

共著,  ISSN  9780784482445

　概要を見る

Building energy models have under predicted actual electricity consumption by about 30%. These models are typically based on physical attributes of an actual building and simulate its operation at static indoor conditions. The attributes of building designs and systems may not represent accurate properties of the building because the data becomes available only as architectural and engineering design progresses. The lack of building data details creates uncertainties in the model. Internet of things (IoT) data enable us to obtain reliable building operational data. This research addresses a major challenge for using IoT data during a building energy prediction and operation. IoT data currently pose two major challenges: 1) IoT data has been generated in existing buildings, but it is often unused, and 2) uncertainties in building energy predictions have resulted in unreliability of the simulation results. The research objective is to present a methodology of IoT-initiated building energy modeling and monitoring to increase the reliability of energy predictions and energy management. The uncertainty-integrated energy modeling enables for reliable energy planning prior to building construction, and for resilient monitoring during post construction and facility operation.

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Real-time sensing in residential area using IoT technology for finding usage patterns to suggest action plan to conserve energy

Matsui K., Yamagata Y., Kawakubo S.

Energy Procedia （Energy Procedia）  158   6438 - 6445 2019年

ISSN  18766102

　概要を見る

To conserve energy in a residential sector, showing action plans how to conserve energy is important. However, we need to consider both energy efficiency and indoor comfort. The usage patterns in the residential sector change according to their life style and some people would try to maintain the indoor comfort at high level even paying high energy cost. It is necessary to understand home energy usage patterns in terms of the relationships between indoor comfort and electricity consumption in order to provide appropriate energy saving action plans to the residential sector. For this purpose, in this study we have collected real time data of electricity consumption and indoor temperature using IoT devices and sensors installed to 13 households for about one month in Summer at Sumida ward in Tokyo, Japan. Then, we have analyzed the data using three types of method, which are a clustering algorism to delineate the electricity usage pattern which characterize the household life style, conducted correlation analysis to look at the relationship between electricity consumption, and the indoor temperature for households living in condominium apartments and detached houses with different building structure and ages.

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A global dataset of co<inf>2</inf> emissions and ancillary data related to emissions for 343 cities

Nangini C., Peregon A., Ciais P., Weddige U., Vogel F., Wang J., Bréon F.M., Bachra S., Wang Y., Gurney K., Yamagata Y., Appleby K., Telahoun S., Canadell J.G., Grübler A., Dhakal S., Creutzig F.

Scientific Data （Scientific Data）  6 2019年

　概要を見る

We present a global dataset of anthropogenic carbon dioxide (CO ) emissions for 343 cities. The dataset builds upon data from CDP (187 cities, few in developing countries), the Bonn Center for Local Climate Action and Reporting (73 cities, mainly in developing countries), and data collected by Peking University (83 cities in China). The CDP data being self-reported by cities, we applied quality control procedures, documented the type of emissions and reporting method used, and made a correction to separate CO emissions from those of other greenhouse gases. Further, a set of ancillary data that have a direct or potentially indirect impact on CO emissions were collected from other datasets (e.g. socio-economic and traffic indices) or calculated (climate indices, urban area expansion), then combined with the emission data. We applied several quality controls and validation comparisons with independent datasets. The dataset presented here is not intended to be comprehensive or a representative sample of cities in general, as the choice of cities is based on self-reporting not a designed sampling procedure. 2 2 2

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Modeling uncertainty in electricity resilient community clustering: a spatial BigData approach

Yoshiki Yamagata, Takahiro Yoshida, Daisuke Murakami

Proceedings of the CIB World Building Congress 2019    123 - 129 2019年

研究論文（国際会議プロシーディングス）, 共著, 査読有り

Measuring resiliencce, economy, sustainability, and human well-being in multiple scales for urban diagnostics

Michael Tobey, Soowon Chang, Takahiro Yoshida, Robert Binder, Yoshiki Yamagata

Proceedings of the 11th International Conference on Applied Energy 0904 2019年

研究論文（国際会議プロシーディングス）, 共著, 査読有り

Individual level heat risk evaluation using GPS towards smart navigation system

Takahiro Yoshida, Yoshiki Yamagata, Daisuke Murakami

Proceedings of the International Cartographic Association 2   152 2019年

研究論文（国際会議プロシーディングス）, 共著, 査読有り

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Experiential modelling of urban street: a combining approach with neural image assessment and street experiment

Yoshiki Yamagata, Takahiro Yoshida, Haruna Matsui, Perry Yang, Chen Helen

Proceedings of the 15th International Conference on Geocomputation 8.6 2019年

研究論文（国際会議プロシーディングス）, 共著, 査読有り

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Cost-optimal pathways to decarbonize urban energy systems with PV, batteries, and electric vehicles: A case study for Kyoto, Japan

Takuro Kobashi, Takahiro Yoshida, Katsuhiko Naito, Stefan Pfenninger, Yoshiki Yamagata

Proceedings of the 11th International Conference on Applied Energy 0107 2019年

研究論文（国際会議プロシーディングス）, 共著, 査読有り

Carbon emission intensities of each building typology: Towards a standardized framework

Takahiro Yoshida, Michael Tobey, Soowon Chang, Yoshiki Yamagata

Proceedings of the 16th International Conference on Computers in Urban Planning and Urban Management 799185 2019年

研究論文（国際会議プロシーディングス）, 共著, 査読有り

A sustainability provision system of energy demands and indoor thermal comfort by integrating building energy models with IoT: Focusing on residential building in Kyojima, Tokyo

Soowon Chang, Takahiro Yoshida, Kanae Matsui, Daniel Castro-Lacouture, Yoshiki Yamagata

Proceedings of the CIB World Building Congress 2019    137 - 146 2019年

研究論文（国際会議プロシーディングス）, 共著, 査読有り

Optimization of local microgrid model for energy sharing considering daily variations in supply and demand

Murakami D., Yamagata Y., Yoshida T., Matsui T.

Energy Procedia （Energy Procedia）  158   4109 - 4114 2019年

ISSN  18766102

　概要を見る

This study develops an approach for optimizing the size/scale of microgrids used in electricity sharing around each residence by considering the uncertainty between the electricity supply from photovoltaics and electricity demand. Uncertainties are quantified using simulations that consider actual daily variations in supply and demand. The developed approach is applied to microgrid optimization in Sumida-ku, Tokyo, Japan, and results suggests that large-scale microgrids are required in central districts but small microgrids are sufficient in old residential areas. Results also show the statistically significant effect of optimizing microgrids to enhance energy self-sufficiency.

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Estimation of gridded population and GDP scenarios with spatially explicit statistical downscaling

Murakami D., Yamagata Y.

Sustainability (Switzerland) （Sustainability (Switzerland)）  11 （ 7 ）  2019年

　概要を見る

This study downscales the population and gross domestic product (GDP) scenarios given under Shared Socioeconomic Pathways (SSPs) into 0.5-degree grids. Our downscale approach has the following features. (i) It explicitly considers spatial and socioeconomic interactions among cities, (ii) it utilizes auxiliary variables, including road network and land cover, (iii) it endogenously estimates the influence from each factor by a model ensemble approach, and (iv) it allows us to control urban shrinkage/dispersion depending on SSPs. It is confirmed that our downscaling results are consistent with scenario assumptions (e.g., concentration in SSP1 and dispersion in SSP3). Besides, while existing grid-level scenarios tend to have overly-smoothed population distributions in nonurban areas, ours does not suffer from the problem, and captures the difference in urban and nonurban areas in a more reasonable manner. Our gridded dataset, including population counts and gross productivities by 0.5 degree grids by 10 years, are available from http://www.cger.nies.go.jp/gcp/population-and-gdp.html.

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Energy demand estimation using quasi-real-time people activity data

Yoshida T., Yamagata Y., Murakami D.

Energy Procedia （Energy Procedia）  158   4172 - 4177 2019年

ISSN  18766102

　概要を見る

This study proposes an approach to estimate quasi-real-time electricity/energy demand in each commercial building using Google's Populartime data. The Populartime data records real-time human locations/activities that are collected from users of Google's maps on smartphones. The proposed approach considering changes by hour and by day of the week is applied to Sumida-ward, Tokyo, Japan. The result suggests the usefulness of our approach for energy demand monitoring considering quasi-real-time human activities.

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Big-data analysis for carbon emission reduction from cars: Towards walkable green smart community

Yamagata Y., Murakami D., Wu Y., Yang P.P.J., Yoshida T., Binder R.

Energy Procedia （Energy Procedia）  158   4292 - 4297 2019年

ISSN  18766102

　概要を見る

To achieve low carbon cities or green smart city, it is very important to foresee how we can reduce the number of cars in the residential communities without losing convenience and comfort of people. For that purpose, walkability is one of the key performance indicators expressing the environmental quality of a district. As the first step for creating a low-carbon smart community, this study attempts to evaluate the influence of walkability on traffic behavior of people by using mobile GPS data. Specifically, we statistically analyze the relationship between various walkability indices (centrality, betweenness, angularity, etc.) evaluated by road network data, and pedestrian movement estimated by mobile GPS data in the six main wards in Tokyo, Japan. The result suggests the usefulness of our approach for low-carbon smart community design rousing people's walking activity. The walkability results and data are then compared to the results of a macrosimulation traffic model for the Sumida Ward of Tokyo to understand the impact that walkability may have on emissions if built environment conditions are improved in favor of a lesser automobile mode share.

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Spatially detail urban carbon mapping: Integration of top-down and bottom-up approaches

Takahiro Yoshida, Yoshiki Yamagata, Daisuke Murakami

Proceedings of the 15th International Conference on Geocomputation 7.3 2019年

研究論文（国際会議プロシーディングス）, 共著, 査読有り

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Urban systems design: A conceptual framework for planning smart communities

Michael B. Tobey, Robert B. Binder, Soowon Chang, Takahiro Yoshida, Yoshiki Yamagata, Perry P. J. Yang

Smart Cities 2 （ 4 ） 522 - 537 2019年

研究論文（学術雑誌）, 共著, 査読有り

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