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Study on the methodology of landscape guidelines for green environment based on physiology

Research Project

Project/Area Number 15K14092
Research Category

Grant-in-Aid for Challenging Exploratory Research

Allocation TypeMulti-year Fund
Research Field Town planning/Architectural planning
Research InstitutionRitsumeikan University

Principal Investigator

MUNEMOTO Shinsaku  立命館大学, 理工学部, 教授 (20581490)

Research Collaborator YAMADA Satoshi  立命館大学, 理工学部, 任期制講師 (00551524)
Project Period (FY) 2015-04-01 – 2018-03-31
Project Status Completed (Fiscal Year 2017)
Budget Amount *help
¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2015: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Keywords緑環境 / 緑視率 / 感性評価 / ベイジアンネットワーク / 確率モデル / 自己組織化マップ / 印象評価推定 / 全方位
Outline of Final Research Achievements

The purpose of this paper is to provide the method for landscape guidelines for green environment based on physiology. We provided the method for the construction of the probabilistic model of the evaluation for the amount of green. We applied Bayesian networks to construct graphical models that represented the correlation between the ratio of the evaluation for the amount of green and the visible green of a close-to-mid-range view, a distant view, and other elements which green environment was composed.
By using Self-Organizing Maps (SOM), we created a map reflecting the characteristics of the green environment with the impression by sensibility evaluation. In this case the characteristics and the sensibility evaluation data of green environment were easily understood by visual analysis. Thus, we provided the method for the method for landscape guidelines for green environment in Kyoto City.

Report

(4 results)
  • 2017 Annual Research Report   Final Research Report ( PDF )
  • 2016 Research-status Report
  • 2015 Research-status Report
  • Research Products

    (5 results)

All 2017 2016 2015

All Journal Article (3 results) (of which Peer Reviewed: 3 results,  Acknowledgement Compliant: 2 results) Presentation (2 results)

  • [Journal Article] GISを用いた木造密集市街地における袋路の避難経路の抽出方法に関する研究2017

    • Author(s)
      雪谷亮太・宗本晋作・山田悟史・北本英里子
    • Journal Title

      歴史都市防災論文集

      Volume: 11 Pages: 143-150

    • NAID

      120006355865

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed
  • [Journal Article] A STUDY ON PROBABILISTIC MODEL OF EVALUATION OF GREEN ENVIRONMENT BASED ON RATIO OF VISIBLE GREEN USING BAYESIAN NETWORK2016

    • Author(s)
      宗本晋作,山田悟史
    • Journal Title

      Journal of Architecture and Planning (Transactions of AIJ)

      Volume: 81 Issue: 729 Pages: 2411-2419

    • DOI

      10.3130/aija.81.2411

    • NAID

      130005171685

    • ISSN
      1340-4210, 1881-8161
    • Related Report
      2016 Research-status Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Journal Article] DEVELOPMENT AND VERIFICATION OF THE IMPRESSION DEDUCTION MODEL FOR GREEN SPACE WITH RATIO OF OMNIDIRECTIONAL VISIBILITY GREEN SPACE2016

    • Author(s)
      山田悟史,藤井健史,宗本晋作
    • Journal Title

      Journal of Architecture and Planning (Transactions of AIJ)

      Volume: 81 Issue: 727 Pages: 2083-2093

    • DOI

      10.3130/aija.81.2083

    • NAID

      130005266178

    • ISSN
      1340-4210, 1881-8161
    • Related Report
      2016 Research-status Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Presentation] 全方位緑視率と心理評価実験を用いた緑地環境に対する感性 評価予測に関する研究2015

    • Author(s)
      山田悟史,藤井健史,宗本晋作
    • Organizer
      第38回情報・システム・利用・技術シンポジウム
    • Place of Presentation
      建築会館ホール(東京都港区)
    • Year and Date
      2015-12-10
    • Related Report
      2015 Research-status Report
  • [Presentation] 全方位緑視率と心理評価実験を用いた感性評価予測に関する研究2015

    • Author(s)
      山田悟史,藤井健史,宗本晋作
    • Organizer
      日本建築学会大会学術講演梗概集2015
    • Place of Presentation
      東海大学(神奈川県平塚市)
    • Year and Date
      2015-09-04
    • Related Report
      2015 Research-status Report

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Published: 2015-04-16   Modified: 2019-03-29  

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