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  1. AU="Bielik, Martin"
  2. AU="Simon A.F. Darroch"
  3. AU="Suzuki, Kenichi G N"
  4. AU="Hu, Yizhong"
  5. AU=Sasaki Kotaro
  6. AU=Abd-Elsayed Alaa
  7. AU="Jung, Hee-Jun"
  8. AU="Struckmann, Stephan"
  9. AU=Coward Richard
  10. AU="Ghazizadeh, Shabnam"
  11. AU="Rebecca A Butcher"
  12. AU="Kimberlyn Roosa"
  13. AU=Chian Ri-Cheng
  14. AU="Alzalzalah, Sayed"
  15. AU=Kaufman Jonathan J
  16. AU="Kim, Jin K"
  17. AU="Zevakov, S A"
  18. AU="Sui Phang"
  19. AU="Kolomeichuk, Lilia V"
  20. AU="Sabuj Kanti Mistry"
  21. AU="Basurto-Lozada, Daniela"
  22. AU="Takashima, Shin-Ichiro"
  23. AU="Teresinha Leal"
  24. AU="Angélique B van 't Wout"
  25. AU="Roberts, Nicholas J"
  26. AU="Chauhan, Gaurav B"
  27. AU=Hanjaya-Putra Donny
  28. AU=Powell James
  29. AU="Russell, Todd"
  30. AU=Forth Scott
  31. AU="Kreutzer, Susanne" AU="Kreutzer, Susanne"
  32. AU="St John, Maie"
  33. AU=Gerhardy A
  34. AU="Qi, Huixin"
  35. AU="Dobosiewicz, May"
  36. AU="Srivastava, Rakesh"
  37. AU="Grevtsov K.I."

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  1. Buch ; Online ; Dissertation / Habilitation: Form-activity-movement interaction model

    Bielik, Martin Verfasser] / [Schneider, Sven [Akademischer Betreuer] / Nourian, Pirouz Gutachter] / [Plank-Wiedenbeck, Uwe [Gutachter] / Nentwig, Bernd [Gutachter]

    2021  

    Verfasserangabe Martin Bielik ; Gutachter: Pirouz Nourian, Uwe Plank-Wiedenbeck, Bernd Nentwig ; Betreuer: Sven Schneider
    Schlagwörter Sozialwissenschaften, Soziologie ; Social Sciences, Sociology
    Thema/Rubrik (Code) sg300
    Sprache Englisch
    Verlag Bauhaus-Universität Weimar
    Erscheinungsort Weimar
    Dokumenttyp Buch ; Online ; Dissertation / Habilitation
    Datenquelle Digitale Dissertationen im Internet

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  2. Artikel: Examining Trade-Offs between Social, Psychological, and Energy Potential of Urban Form

    Bielik, Martin / Schneider, Sven / Kuliga, Saskia / Griego, Danielle / Ojha, Varun / König, Reinhard / Schmitt, Gerhard / Donath, Dirk

    ISPRS international journal of geo-information. 2019 Jan. 24, v. 8, no. 2

    2019  

    Abstract: Urban planners are often challenged with the task of developing design solutions which must meet multiple, and often contradictory, criteria. In this paper, we investigated the trade-offs between social, psychological, and energy potential of the ... ...

    Abstract Urban planners are often challenged with the task of developing design solutions which must meet multiple, and often contradictory, criteria. In this paper, we investigated the trade-offs between social, psychological, and energy potential of the fundamental elements of urban form: the street network and the building massing. Since formal methods to evaluate urban form from the psychological and social point of view are not readily available, we developed a methodological framework to quantify these criteria as the first contribution in this paper. To evaluate the psychological potential, we conducted a three-tiered empirical study starting from real world environments and then abstracting them to virtual environments. In each context, the implicit (physiological) response and explicit (subjective) response of pedestrians were measured. To quantify the social potential, we developed a street network centrality-based measure of social accessibility. For the energy potential, we created an energy model to analyze the impact of pure geometric form on the energy demand of the building stock. The second contribution of this work is a method to identify distinct clusters of urban form and, for each, explore the trade-offs between the select design criteria. We applied this method to two case studies identifying nine types of urban form and their respective potential trade-offs, which are directly applicable for the assessment of strategic decisions regarding urban form during the early planning stages.
    Schlagwörter case studies ; empirical research ; energy ; geometry ; models ; planning
    Sprache Englisch
    Erscheinungsverlauf 2019-0124
    Erscheinungsort Multidisciplinary Digital Publishing Institute
    Dokumenttyp Artikel
    ZDB-ID 2655790-3
    ISSN 2220-9964
    ISSN 2220-9964
    DOI 10.3390/ijgi8020052
    Datenquelle NAL Katalog (AGRICOLA)

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  3. Artikel ; Online: Machine learning approaches to understand the influence of urban environments on human’s physiological response

    Ojha, Varun Kumar / Griego, Danielle / Kuliga, Saskia / Bielik, Martin / Buš, Peter / Schaeben, Charlotte / Treyer, Lukas / Standfest, Matthias / Schneider, Sven / Koenig, Reinhard / Donath, Dirk / Schmitt, Gerhard

    Information Sciences, 474

    2019  

    Abstract: This research proposes a framework for signal processing and information fusion of spatial-temporal multi-sensor data pertaining to understanding patterns of humans physiological changes in an urban environment. The framework includes signal frequency ... ...

    Abstract This research proposes a framework for signal processing and information fusion of spatial-temporal multi-sensor data pertaining to understanding patterns of humans physiological changes in an urban environment. The framework includes signal frequency unification, signal pairing, signal filtering, signal quantification, and data labeling. Furthermore, this paper contributes to human-environment interaction research, where a field study to understand the influence of environmental features such as varying sound level, illuminance, field-of-view, or environmental conditions on humans’ perception was proposed. In the study, participants of various demographic backgrounds walked through an urban environment in Zürich, Switzerland while wearing physiological and environmental sensors. Apart from signal processing, four machine learning techniques, classification, fuzzy rule-based inference, feature selection, and clustering, were applied to discover relevant patterns and relationship between the participants’ physiological responses and environmental conditions. The predictive models with high accuracies indicate that the change in the field-of-view corresponds to increased participant arousal. Among all features, the participants’ physiological responses were primarily affected by the change in environmental conditions and field-of-view.

    ISSN:0020-0255

    ISSN:1872-6291
    Schlagwörter machine learning ; Data science ; Urban design ; urbanism ; Environmental change ; climate information ; Physiology ; perception
    Thema/Rubrik (Code) 150
    Sprache Englisch
    Verlag Elsevier
    Erscheinungsland ch
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Konferenzbeitrag ; Online: Using Geo statistical analysis to detect similarities in emotional responses of urban walkers to urban space

    Koenig, Reinhard / Scheider, Sven / Hamzi, Ihab / Bielik, Martin / Schmitt, Gerhard / Donath, Dirk

    2014  

    Schlagwörter STADTPHYSIOGNOMIE + STADTBILD + STADTFORMEN (STÄDTEWESEN) ; RAUMWIRKSAMKEIT (ANTHROPOGEOGRAFIE) ; GEOSTATISTIK ; URBAN PHYSIOGNOMY + URBAN FORM + URBAN SETTLEMENT FORMS (URBAN STUDIES) ; REGIONAL IMPACT (HUMAN GEOGRAPHY) ; GEOSTATISTICS ; info:eu-repo/classification/ddc/910 ; Geography & travel
    Sprache Englisch
    Verlag ETH-Zürich
    Erscheinungsland ch
    Dokumenttyp Konferenzbeitrag ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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