Yoshiki YAMAGATA

写真a

Affiliation

Graduate School of System Design and Management Graduate School of System Design and Management (Hiyoshi)

Position

Professor

E-mail Address

E-mail address

Related Websites

Contact Address

Kyousei-kan, 4-1-1, Hiyoshi, Kohoku-ku, Yokohama

Telephone No.

+81-45-564-2458

External Links

Profile 【 Display / hide

  • YOSHIKI YAMAGATA graduated from the University of Tokyo (PhD in System Science) in 1985. Since 1991, he works at the National Institute for Environmental Studies (NIES). Currently, he is studying about the climate risk management as Principal Researcher of Center for Global Environmental Research (CGER). He is also actively coordinating international project as the Head of Global Carbon Project which is one of core project of Future Earth and nominated as a member of Science Council of Japan (SCJ). He is also afflicted as a visiting scholar at International Institute for Applied Systems Analysis (IIASA, Vienna) and Institute of Statistical Mathematics (ISM, Tokyo). His recent research topics include: Land use scenario analysis, Urban resilience modeling, Urban systems design for smart communities. He has many lecture series at the University of Tokyo, Tsukuba, Hokkaido, Keiko and Sophia university. Internationally, he is serving as Lead author for IPCC (SR/Climate change and land use and AR6/WG3/Urban systems etc.) as well as “Applied Energy” and “Environmental Planning B” as editorial board.

Profile Summary 【 Display / hide

  • Aiming to co-create a future society which address the issues of "environment" and "health", we will develop a new urban system design framework that integrates architecture, transportation, and human behavior in cities. Research topics include: Sustainable future societies, Urban resilience, Zero carbon cities, Bigdata and AI

Other Affiliation 【 Display / hide

  • National Institute for Environmental Studies (NIES) , Visiting Researcher

  • The University of Tokyo , Visiting Researcher

  • Hokkaido University , Visiting Professor

  • The Institute of Statistical Mathematics , Visiting Professor

  • IIASA, Research scholar

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Career 【 Display / hide

  • 1985.04
    -
    1991.03

    National Institute for Agro-Environmental Sciences(NIAES), Environmental Management Department , Researcher

  • 1991.04
    -
    1999.03

    National Institute for Environmental Studies (NIES), Social and Environmental Systems Research, Senior Researcher

  • 1999.04
    -
    2006.03

    National Institute for Environmental Studies (NIES), Center for Global Environmental Reseach, Reseach Director

  • 2006.04
    -
    2021.03

    National Institute for Environmental Studies (NIES), Center for Global Environmental Reseach, Senior Researcher

  • 2021.04
    -
    Present

    National Institute for Environmental Studies (NIES), Center for Global Environmental Reseach, Visiting Reseacher

Academic Background 【 Display / hide

  • 1980.04
    -
    1985.03

    The University of Tokyo, College of Arts and Sciences, Natural Sciences Ⅰ

    University, Graduated

Academic Degrees 【 Display / hide

  • Doctor(General System Studies), The University of Tokyo, Dissertation, 1998.03

 

Research Areas 【 Display / hide

  • Design and evaluation of sustainable and environmental conscious system (Sustainable Smart City)

  • Environmental dynamic analysis

  • Environmental impact assessment

Research Keywords 【 Display / hide

  • Smart City

  • Climate-change mitigation

  • low-carbon society

  • Sustainability

  • Urban systems

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Research Themes 【 Display / hide

  • 未来社会共創イノベーション研究室では、持続可能な未来社会の実現に向けて、社会課題解決や新たな価値を創造するための分野横断的な社会システムのイノベーションに関する研究に取組みます。, 

    2021.04
    -
    Present

 

Books 【 Display / hide

  • Urban Systems Design

    Yoshiki Yamagata, Takahiro Yoshida, Perry PJ Yang, Helen Chen, Daisuke Murakami, Leena Ilmola, Elsevier, 2020

    Scope: Chapter 12 - Measuring quality of walkable urban environment through experiential modeling

  • Urban systems design : creating sustainable smart cities in the Internet of Things era

    Yamagata Y.;Yang, Perry, Elsevier, 2020

  • Spatial analysis using big data: Methods and urban applications

    Yamagata Y., Seya H., Spatial Analysis Using Big Data: Methods and Urban Applications, 2019.11

     View Summary

    Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems. The methods represent a cluster of potentially transformational socio-economic modeling tools that allow researchers to capture real-time and high-resolution information to potentially reveal new socioeconomic dynamics within urban populations. Each method, written by leading exponents of the discipline, uses real-time urban big data to solve research problems in spatial science. Urban applications of these methods are provided in unsurpassed depth, with chapters on surface temperature mapping, view value analysis, community clustering and spatial-social networks, among many others.

  • Special Report "Climate Change and Land"

    Review Editors, Abdulla A, Noble I, Yamagata Y, Zatari T, IPCC (Intergovernmental Panel on Climate Change), 2019.08

    Scope: ch.6 “Interlinkages between desertification, land degradation, food security and GHG fluxes: synergies, trade-offs and integrated response options”

  • Spatial analysis using big data : methods and urban applications

    Yamagata Y.;Seya S., Academic Press, 2019

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Papers 【 Display / hide

  • Rapid rise of decarbonization potentials of photovoltaics plus electric vehicles in residential houses over commercial districts

    Takuro Kobashia, Younghun Choia, Yujiro Hiranob, Yoshiki Yamagataa, Kelvin Sayc

    Applied Energy (Elsevier)  306 2022.01

    Research paper (scientific journal), Joint Work

     View Summary

    Rooftop photovoltaics (PVs) integrated with electric vehicles (EVs) has the potential to deeply decarbonize urban energy systems in a cost-effective way. The SolarEV City Concept suggested that the rooftop PV plus EV systems can supply up to 95% of electricity demand within cities in Japan. However, it was not clear which district in city could consume, generate, and store the PV electricity, as each district has different load patterns, building structures, and number of parked cars. In this study, we performed techno-economic analyses on rooftop PV systems integrated with stand-alone batteries or EVs in residential and commercial districts in Japan from 2020 to 2040. We found that rooftop PV systems in 2020 are already cost competitive relative to existing energy systems. However, “PV + EV” systems in residential houses rapidly increases its economic advantage over commercial districts due to greater rooftop space and higher number of available vehicles. Moreover, energy sharing significantly improved the decarbonization potential. By 2025, energy cost savings, payback periods, and internal rate of return (IRR) of residential “PV + EV” systems respectively reached 23%, 9 years, and 11%, and continued improving in subsequent years. CO2 emissions from electricity and gasoline consumption was reduced by 88%, and the system was capable to supplying 89% of electricity demand. The results indicate that residential “PV + EV” systems are a potential source for significant renewable energy generation and storage that can also produce increasingly dispatchable electricity. Policy makers, industries, and communities should prepare to establish these systems through regulatory reform and demonstration projects to scale-up after 2025.

  • Diverse values of urban-to-rural migration: A case study of Hokuto City, Japan

    YasuoTakahashi, Hiroyuki Kubota, Sawako Shigeto, TakahiroYoshida, Yoshiki Yamagata

    Journal of Rural Studies (Elsevier)  87   292 - 299 2021.10

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  0743-0167

     View Summary

    The global population is concentrating unprecedentedly into urban areas, raising concerns on global sustainability and human well-being. There also exists a niche trend of migration from urban to rural areas particularly in countries with post-industrial economies. This paper investigated values of migration expressed by the migrants arrived in Hokuto City, a Japanese rural municipality experiencing pervasive population decline but is also a popular destination for migrants from urban areas. Statistical analyses of 868 responses to a Hokuto City's migrant survey between April 2017 and January 2019 identified their common values of migration, i.e., nature, housing and food. In addition to these common values, households with different demographic characteristics had different priorities: employment for singles in ages between 16 and 29; favorable environment for raising children for married couples in their 30s and 40s; not specific or ‘lifestyle’ for migrants in 50s; and staying with or near family for retirees over 60 years. Knowledge of heterogeneity in migrants and of their values, as described herein, will enable targeted policies and public services concerning migration. Widespread acceptance of teleworking after experiencing the COVID-19 pandemic might offer people of working age, particularly in their 20s and younger, a wider range of options of places to work and live, and thus is likely to influence future urban-rural population flow. A more detailed analysis of the region's natural attributes which are central to the values of migration to rural areas, such as Hokuto City, will be useful to inform regional land use planning that is salient to the values of migrants.

  • The Need for Urban Form Data in Spatial Modeling of Urban Carbon Emissions in China: A Critical Review

    Cai, Meng, Yuan Shi, Chao Ren, Takahiro Yoshida, Yoshiki Yamagata, Chao Ding, and Nan Zhou

    Journal of Cleaner Production (Elsevier)   2021.08

    Joint Work, Except for reviews

     View Summary

    Cities produce over 70% of global carbon emissions and are thus crucial in driving climate change. Urban carbon emissions may continue to increase especially in those less-developed countries and regions which are still under rapid urban development. Policymakers need to find ways to effectively control and reduce carbon emissions. Thus, spatial modeling methods to map and predict urban carbon emissions have been developed to meet these needs. This paper examines the progress of the spatial modeling of carbon emissions and the relationship between urban form and carbon emissions in China by reviewing more than 100 peer-reviewed journal articles in the Scopus database. The latest prediction methods and techniques are described in the paper. Their advantages and limitations are then discussed. Urban forms have a significant influence on carbon emissions and have been applied in spatial modeling studies in other countries. However, this review has identified the lack of urban form data and high-resolution inventories from existing studies in China. Future developments in the spatial modeling in China should therefore have a fine spatial resolution and incorporate open and high-quality urban form data, including urban morphology and land use/land cover.

  • Machine learning model for predicting out-of-hospitalcardiac arrests using meteorological and chronological data

    Takahiro Nakashima , Soshiro Ogata , Teruo Noguchi , Yoshio Tahara , Daisuke Onozuka , Satoshi Kato , Yoshiki Yamagata , Sunao Kojima , Taku Iwami , Tetsuya Sakamoto , Ken Nagao , Hiroshi Nonogi , Satoshi Yasuda , Koji Iihara , Robert Neumar , Kunihiro Nishimura

     2021.05

    Joint Work, Except for reviews

     View Summary

    Objectives: To evaluate a predictive model for robust estimation of daily out-of-hospital cardiac arrest (OHCA) incidence using a suite of machine learning (ML) approaches and high-resolution meteorological and chronological data.

    Methods: In this population-based study, we combined an OHCA nationwide registry and high-resolution meteorological and chronological datasets from Japan. We developed a model to predict daily OHCA incidence with a training dataset for 2005-2013 using the eXtreme Gradient Boosting algorithm. A dataset for 2014-2015 was used to test the predictive model. The main outcome was the accuracy of the predictive model for the number of daily OHCA events, based on mean absolute error (MAE) and mean absolute percentage error (MAPE). In general, a model with MAPE less than 10% is considered highly accurate.

    Results: Among the 1 299 784 OHCA cases, 661 052 OHCA cases of cardiac origin (525 374 cases in the training dataset on which fourfold cross-validation was performed and 135 678 cases in the testing dataset) were included in the analysis. Compared with the ML models using meteorological or chronological variables alone, the ML model with combined meteorological and chronological variables had the highest predictive accuracy in the training (MAE 1.314 and MAPE 7.007%) and testing datasets (MAE 1.547 and MAPE 7.788%). Sunday, Monday, holiday, winter, low ambient temperature and large interday or intraday temperature difference were more strongly associated with OHCA incidence than other the meteorological and chronological variables.

    Conclusions: A ML predictive model using comprehensive daily meteorological and chronological data allows for highly precise estimates of OHCA incidence.

  • Carbon analytics for net-zero emissions sustainable cities

    Anu Ramaswami, Kangkang Tong, Josep G. Canadell, Robert B. Jackson, Eleanor (Kellie) Stokes, Shobhakar Dhakal, Mario Finch, Peraphan Jittrapirom, Neelam Singh, Yoshiki Yamagata, Eli Yewdall, Leehi Yona & Karen C. Seto

    Nature sustainability (Springer)  4 ( 6 ) 460 - 463 2021.05

    Joint Work, Except for reviews

     View Summary

    Consensus on carbon accounting approaches at city-level is lacking and analytic frameworks to systematically link carbon mitigation with the Sustainable Development Goals are limited. A new accounting approach anchored upon key physical provisioning systems can help to address these knowledge gaps and facilitate urban transitions.

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Reviews, Commentaries, etc. 【 Display / hide

  • Carbon analytics for net-zero emissions sustainable cities

    Ramaswami A, Tong K, Canadell J.G, Jackson R.B, Stokes E, Dhakal S, Finch M, Jittrapirom P, Singh N, Yamagata Y, Yewdall E, Yona L, Seto K.C

    Nature Sustainability (Nature Sustainability)   2021

    Other article, Joint Work

  • A “Smart Lifestyle” for the re-design of the “After Corona” urban form

    Yamagata Y, Yoshida T

    Environment and Planning B: Urban Analytics and City Science (Environment and Planning B: Urban Analytics and City Science)  47 ( 7 ) 1146 - 1148 2020.09

    Other article, Joint Work,  ISSN  23998083

  • Developing sustainable bioenergy systems with local bio-resources: cases in Asia

    Goh C.S, Saito O, Yamagata Y

    Sustainability Science (Sustainability Science)  15 ( 5 ) 1449 - 1453 2020.09

    Other article, Joint Work,  ISSN  18624065

     View Summary

    The concept of sustainability science is paramount to establish a development thinking with deep and thorough considerations of hybridized on-ground realities shaped by the interplay of energy, land, economic, and climatic elements. This special feature intends to engage sustainability science in understanding the role of bioenergy in sustainable development, particularly for cases in East Asia. Especially, it encourages potential works that carefully consider perspectives of different stakeholders, including communicating with both experts and non-experts and integrating knowledge from different disciplines like forestry, social studies, or energy system sciences. It aims to create the context for motivating the society in tackling the sustainability issues related to energy, forest, and society.

  • Corrigendum to ‘Pathway using WUDAPT's Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling’ (Urban Climate (2019) 28, (S2212095519300975), (10.1016/j.uclim.2019.100459))

    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)  30 2019.12

    Other article, Joint Work,  ISSN  22120955

     View Summary

    Jason Ching jksching@gmail.com, Dan Aliaga , Gerald Mills , Valery Masson , Linda See , Marina Neophytou , Ariane Middel , Alexander Baklanov , Chao Ren , Ed Ng , Jimmy Fung , Michael Wong , Yuan Huang , Alberto Martilli , Oscar Brousse , Iain Stewart , Xiaowei Zhang , Aly Shehata , Shiguang Miao , Xuemei Wang , Weiwen Wang , Yoshiki Yamagata , Denise Duarte , Luciana Schwandner Ferreira , Yuguo Li , Johan Feddema , Benjamin Bechtel , Julia Hidalgo , Yelva Roustan , YoungSeob Kim , Helge Simon , Tim Kropp , Michael Bruse , Fredrik Lindberg , Sue Grimmond , Matthias Demuzure , Fei Chen , Chen Li , Jorge Gonzales-Cruz , Bob Bornstein , Qiaodong He , Tzu-Ping , Adel Hanna , Evyatar Erell , Nigel Tapper , R.K. Mall , Dev Niyogi Institute for the EnvironmentUNC at Chapel HillNC, United States Department of Computer SciencesPurdue UW, Lafayette, IN, United States School of GeographyUniversity College of DublinDublin, Ireland Meteo France, Toulouse, France IIASA, Laxemburg, Austria Civil and Environmental Engineering, U of Cyprus, Nicosia, Cyprus Arizona State U, Tempe, AZ, United States World Meteorological Organization (WMO), Geneva, Switzerland Hong Kong U, Hong Kong Department of Architecture, CUHK, Hong Kong Hong Kong Science and Technology U, Hong Kong Department of Architecture, SW Jiatong U, Chengdu, China CIEMAT, Madrid, ES, Spain Dept Earth, Environmental Science, KU Leuven, Leuven, Belgium University of Toronto, Canada Department of Computer Sciences, Purdue U, W. Lafayette, IN, United States Institute of Urban Meteorology, Beijing, China Institute Environmental, Climate Research Jinan U, Guangzhou, China National Institute for Environmental Sciences, Tsukuba, Japan School of Architecture, Urbanism, U of São Paulo, Sao Paolo, Brazil Luciana Schwander, U, São Paulo, São Paulo, Brazil Department of Mechanical Engineering, HKU, Hong Kong Department of Geography, U of Victoria, British Columbia, Canada Institute of Geography, U Hamburg, Hamburg, DE, Germany Toulouse Federal U, Toulouse, France CEREA, Joint Laboratory Ecole des Ponts Paris Tech Marne, France Johannes Gutenberg Universitat- Mainz, Mainz, DE, Germany Department of Earth Sciences, U Gothenberg, Goteborg, Sweden Dept of Meteorology, U Reading, Reading, UK K U Leuven, Belgium The authors regret missing the following corrections: The affiliation of Dr. Luciana Schwandner Ferreira should read “School of Architecture and Urbanism, University of São Paulo, Sao Paolo, Brazil and and Dr. Luciana Schwandner Ferreira is the 24th author in the author list. Affiliation for Benjamin Bechtel is “Department of Geography, Ruhr-University Bochum, Bochum, Germany”. The surname of Dr. Matthias Demuzure is “Demuzere”. Affiliation is “Department of Geography, Ruhr-University Bochum, Bochum, Germany”. The authorname “Ed Ng” should be “Edward Ng”. The authorname “Qiaodong He” should be “Xiaodong He” and affiliation is “Institute of Urban Meteorology, CMA, Beijing, China.” Affiliation q should be the same as this affiliation. The authorname “Tzu-Ping” should be “Tzu-Ping Lin”. Affiliation for Nigel Tapper should be “School of Earth, Atmosphere and Environment, Monash University, Melbourne, Australia”. The authorname “Shen Li” to “Li Shen” and his affiliation is ae “Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China”. The affiliation for Yelva Roustan is “CEREA, Joint Laboratory Ecole des Ponts ParisTech – EDF R&D, Champs-Sur-Marne, France”. The affiliation for Youngsoeb Kim is also “CEREA, Joint Laboratory Ecole des Ponts ParisTech – EDF R&D, Champs-Sur-Marne, France”. Miscellaneous within text changes are as follows: (1) Table A2, Please change in first column “Banaras” to “Varanasi”.(2) Paragraph before acknowledgement, “Passive Low Energy Architecture (PLEA)” should read “Passive and Low Energy Architecture (PLEA)”.(3) Correction 1. The word “pana;” in the last sentence of first paragraph to be removed.(4) Correction 2. Fig. 1 caption; change “Rpouse” should read “Rouse”.(5) In Section 3.4, second paragraph, 5th line “APP; and sampling” to be removed.(6) Section 4.1, second para, 5th line. The sentence “In particular, the horizontal axis……range divided” to be removed.(7) Section 4.4, second line, “paradigms” should be replaced with “tools”.The authors would like to apologise for any inconvenience caused. a,⁎ b c d e f g h i j k k l m n o p p q r r s t t u v w x y y z z z aa ab ac ad ae af ag ah ai aj ak al am an a b c d e f g h i j k l m n o p q r s t u v w x y z aa ab ac

  • Introduction

    Yamagata Y, Seya H

    Spatial Analysis Using Big Data: Methods and Urban Applications (Spatial Analysis Using Big Data: Methods and Urban Applications)     1 - 5 2019.11

    Other article, Joint Work,  ISSN  9780128131275

     View Summary

    Section 1.1 of this chapter introduces the definition of spatial data as the realizations of spatial processes. Three types of spatial data-geostatistical data, lattice data, and spatial point patterns-are defined there. Section 1.2 explains the characteristics of spatial data-spatial autocorrelation (subsection 1.2.1) and spatial heterogeneity (subsection 1.2.2).

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Research Projects of Competitive Funds, etc. 【 Display / hide

  • Monitoring the bio-economy in Asia: Impacts, synergies and trade-offs on land-use and carbon stock change

    2017.10
    -
    2020.03

    National Institute for Environmental Studies, 山形 与志樹, GOH CHUN SHENG, Grant-in-Aid for JSPS Fellows

     View Summary

    Bioenergy in Japan: Two papers were recently completed in May and July 2019, respectively, after a few round of internal revisions, with the content mainly based upon (i) a workshop was organised at UNU attended by 35 experts from governments, academia, industries and NGOs and (ii) an international workshop was co-organized by IEA Bioenergy and NEDO in September 2018, which received about 100 international participants. Two papers were recently accepted to be published on Sustainability Science (Springer).
    Bio-economy in Borneo: A paper was recently completed in July 2019, based upon extensive field trips made in Indonesia, Malaysia and Singapore in October 2018, which include multiple interviews and meetings were made with a large number of stakeholders from various background and sectors to investigate the latest development of bio-economy in the region. The paper was submitted in July 2019 to Environmental Development (Elsevier), and then revised after the first round of review. It is currently under the second round of review.
    For the entire period of the fellowship, three (3) papers have been accepted / published in peer-reviewed journals, one (1) were submitted and currently under 2nd round of review, and one (1) book chapter (Springer) which is currently in editing.

  • Study on spacial-temporal analysis of ground surface temperature for global warming countermeasures

    2017.04
    -
    2020.03

    The Institute of Statistical Mathematics, 松井 知子, 村上 大輔, 山形 与志樹, AMES MATTHEW, Grant-in-Aid for Scientific Research (B)

     View Summary

    本研究は、空間的かつ時間的に粒度の異なる計測データを統合的に活用して、大都市圏での地球温暖化対策を実現することを目指し、地表面温度の高度な時空間解析技術の開発に取り組む。低分解能の地上気象観測による気象要素の時系列計測データに加えて、高分解能の人工衛星による地表面温度の時系列計測データを用い、統計解析手法を高度に融合させることによって、これまで捉えられなかった大都市圏における地表面温度分布の時空間変動の高精度な推定方法と、厳しい熱波状況などの極端な極値事象発生に関与する要因の高度な検出方法の開発を行う。将来的に本技術は大都市圏での地球温暖化対策立案に貢献することが期待される。
    当該年度は、クラスタリングとSpatial Best Linear Unbiased Estimator (Spatial-BLUE)を組み合わせた解析を行うことで、熱波状況の背後に潜む分布構造、具体的には期待値、分散、歪度、尖度が異なることを明らかにした。さらに、この結果を発展させて、上記解析のパラメータを、熱波の時空間過程とともに場所毎に推定する方法を新規開発した。ここでは局所空間過程の高速推定手法であるlocal approximate Gaussian process(laGP)とTukey g-and-h (TGH)modelを組み合わせた。それにより、衛星観測熱画像のような高解像度データから、各地の暑熱特性(期待値、分散、歪度、尖度)を現実的な時間スケールで推定することができた。この結果、真夏日の暑熱特性には尖度や歪度といった分布の裾の特徴量が顕著となることがわかった。
    本研究課題については、①高度解析手法の開発、②計測データの収集と観測実験、③地表面温度の高度な時空間解析技術の開発、④熱波状況のシミュレーションと解析実験の四つの検討を実施する計画であった。
    ①については、物理モデルを想定しない場合について、クラスタリングとSpatial Best Linear Unbiased Estimator (Spatial-BLUE)を組み合わせた解析手法を開発した。物理モデルを想定する場合については未着手である。②については、MODISデータ(気象関連)を整備した。③については、上記①の手法、上記②のデータを用いて、熱波状況の背後に潜む分布構造、具体的には期待値、分散、歪度、尖度が異なることを明らかにした。さらに、この結果を発展させて、上記解析のパラメータを、熱波の時空間過程とともに場所毎に推定する方法を新規開発した。ここでは局所空間過程の高速推定手法であるlocal approximate Gaussian process(laGP)とTukey g-and-h (TGH)modelを組み合わせた。④については、上記③の成果をもとに、各地の暑熱特性(期待値、分散、歪度、尖度)を現実的な時間スケールでシミュレーションした。この結果、真夏日の暑熱特性には尖度や歪度といった分布の裾の特徴量が顕著となることがわかった。
    以上、概ね順調に進展していると自己評価する。
    方法と応用の2チーム体制で実施する。方法チームは、前年度に引き続いてモデリングの研究を行って、共変量の組み込みなどによるモデルの洗練化をはかるとともに、キャリブレーションの研究を行う。具体的には、物理モデルを想定する/しない場合に分けてモデリング、キャリブレーションを行う。物理モデルを想定する場合、並列計算効率に優れた局所アンサンブル変換カルマンフィルタなどの高速なデータ同化手法を適用する。物理モデルを想定しない場合には、状態空間モデルの観測、状態方程式は、表現力の優れたノンパラメトリックなガウス過程を用いて表す。計算コストが非常に小さいST-BLUEのアルゴリズムを新たに組み込むことについて検討する。
    また、応用チームは、応用チームは前年度に引き続き計測データの取得・整備、地表面温度の観測実験を行う。
    さらに、方法と応用の両チームとの協働のもと、GCPの海外の主要関連研究者の協力を得て、各種センサーからの計測データを用い、上記高度解析手法を応用して、衛星熱画像を高精度に時空間補間し、地表面温度分布の時空間変動を高精度に推定する方法を開発する。その際、計測データの時空間解像度、種類、精度を反映させた地表面温度分布のモデルを設計する。また、厳しい熱波状況などの極端な極値事象発生に関与する要因を高度に検出する方法を開発する。

  • Development of methodology for designinig flood risk informarion dissimination service

    2016.04
    -
    2019.03

    National Institute for Environmental Studies, YAMAGATA YOSHIKI, HIROI Kei, YOSHIDA Takahiro, Grant-in-Aid for Scientific Research (B)

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    We developed a simulation technique of flood damage risk using geographic information data. The time-period of this study is from September 9, 2015 to 16, including the period of heavy rain in the Kanto and Tohoku regions. We focused on the estimation and reproduction of people's movements during the target period. This study examined a method for estimating spatially detailed evacuation behavior from mobile GPS data whose capture rate is not sufficient (about 1%). And then, we developed a method for spatio-temporal interpolation of the number of people using kernel function. By applying the spatial interpolation method to the actual data of Joso City, Ibaraki prefecture, it was confirmed that the evacuation behavior at the time of flood disaster could be reproduced.

Awards 【 Display / hide

  • 優秀研究発表賞

    吉田 崇紘;山形 与志樹, 2019.11, Center for Spatial information Science, The University of Tokyo, ビッグデータを活用した空間詳細なCO2マッピング

    Type of Award: Awards of National Conference, Council and Symposium

  • Best Paper Award of Applied Regional Science Conference

    Hajime SEYA;Yoshiki YAMAGATA, 2013.12, Applied Regional Science Conference, Applying weighted-average least squares estimator to spatial econometric models

    Type of Award: Awards of National Conference, Council and Symposium

  • ノーベル平和賞受賞への貢献を証明する感謝状

    IPCC代表執筆者(Lead Author)として, 2008.04, IPCC

    Type of Award: International Academic Awards

  • Best Paper Award of Japan Society for Simulation Technology

    山形 与志樹;中村仁也, 2006.06, JAPAN SOCIETY FOR SMILATION TECHNOLOGY, Dynamic Gaming Simulation on the International Climate Regime Formation

    Type of Award: Awards of National Conference, Council and Symposium

  • 1998 1st OZE prize

    Yoshiki YAMAGATA, 1998.06, 尾瀬保護財団, 湿原に関する学術研究においてリモートセンシング画像を用いた環境特性を把握する手法の開発

    Type of Award: Awards of Publisher, Newspaper Company and Foundation

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Other 【 Display / hide

  • 2021年05月

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    Earthquake Risk Reduction and Residential Land Prices in Tokyo 報告者:河端 瑞貴1、直井 道生2、安田 昌平3(1.慶應義塾大学、2.慶應義塾大学、3.日本大学) 討論者:山形 与志樹 日本経済学会(春季大会)2021年5月15-16日

 

Courses Taught 【 Display / hide

  • SUSTAINABLE URBAN SYSTEMS 2

    2021

  • SUSTAINABLE URBAN SYSTEMS 1

    2021

  • STUDIOS FOR URBAN SYSTEMS DESIGN

    2021

  • RESEARCH ON SYSTEM DESIGN AND MANAGEMENT

    2021

  • RESEARCH ON PROJECT DESIGN AND MANAGEMENT

    2021

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