Rapid and accurate identification of potential structural deficiencies is a crucial task in evaluating seismic vulnerability of large building inventories in a region. In the case of multi-story structures, abrupt ver...Rapid and accurate identification of potential structural deficiencies is a crucial task in evaluating seismic vulnerability of large building inventories in a region. In the case of multi-story structures, abrupt vertical variations of story stiffness are known to significantly increase the likelihood of collapse during moderate or severe earthquakes. Identifying and retrofitting buildings with such irregularities—generally termed as soft-story buildings—is, therefore, vital in earthquake preparedness and loss mitigation efforts. Soft-story building identification through conventional means is a labor-intensive and time-consuming process. In this study, an automated procedure was devised based on deep learning techniques for identifying soft-story buildings from street-view images at a regional scale. A database containing a large number of building images and a semi-automated image labeling approach that effectively annotates new database entries was developed for developing the deep learning model. Extensive computational experiments were carried out to examine the effectiveness of the proposed procedure, and to gain insights into automated soft-story building identification.展开更多
With the continuous calls for energy conservation and emission reduction in recent years,more and more people choose walking as their travel mode.The improvement of the quality of street space will directly affect peo...With the continuous calls for energy conservation and emission reduction in recent years,more and more people choose walking as their travel mode.The improvement of the quality of street space will directly affect people's willingness to walk.By sorting out relevant research on street quality measurement,extracting quality keywords with high frequency of reference as impact factors,and using street view image data from different eras,semantic segmentation technology,factor analysis,and questionnaire survey methods,this paper evaluates the street quality of Jingshan East Street,Dongcheng District,Beijing,further explores the impact of different factors on street quality,and analyzes possible ways to improve it.展开更多
Regular evaluation of street space is essential for achieving sustainable development and dynamic maintenance of historic areas.Although quantitative evaluations using street view imagery are precise and efficient,the...Regular evaluation of street space is essential for achieving sustainable development and dynamic maintenance of historic areas.Although quantitative evaluations using street view imagery are precise and efficient,they often fall short in capturing pedestrians’visual experience,largely because images are collected from vehicles.Accordingly,this paper acquires street view imagery in the human visual field before and after the street space renovation by adjusting relevant parameters,and performs image semantic segmentation.From a pedestrian’s viewpoint,the paper develops street space evaluation indicators across four dimensions:comfort,identity,diversity,and walkability.The mean square deviation method is applied to assign weights to these indicators,enabling a comprehensive evaluation of street space in historic areas.In addition to evaluating the renovation results,it proposes improvement suggestions that may provide insights into the evaluation practices of street space renovations in historic areas and contribute to improving street space quality.展开更多
In order to comprehensively and objectively understand the research status of street form at home and abroad,WOS and CNKI database are as the source,and 176 street form papers retrieved from 2010 to 2021 are as sample...In order to comprehensively and objectively understand the research status of street form at home and abroad,WOS and CNKI database are as the source,and 176 street form papers retrieved from 2010 to 2021 are as samples to conduct statistical analysis of the data.The main research hotspots are reviewed systematically,and the research trends in the field of planning and architecture are pointed out.The hot topics of street form research in the past ten years are summarized,such as street spatial form characteristics,street form and thermal environment,air quality correlation,street form and walking,safety,vitality,health and other perceived correlations.The research methods are summarized from two levels of street form data collection and analysis.Finally,the current research trend characteristics and future trends are summarized and prospected to provide reference for the current research of street form.展开更多
基金supported by the US National Science Foundation under Grant No. 1612843. NHERI Design Safe (Rathje et al., 2017)Texas Advanced Computing Center (TACC)。
文摘Rapid and accurate identification of potential structural deficiencies is a crucial task in evaluating seismic vulnerability of large building inventories in a region. In the case of multi-story structures, abrupt vertical variations of story stiffness are known to significantly increase the likelihood of collapse during moderate or severe earthquakes. Identifying and retrofitting buildings with such irregularities—generally termed as soft-story buildings—is, therefore, vital in earthquake preparedness and loss mitigation efforts. Soft-story building identification through conventional means is a labor-intensive and time-consuming process. In this study, an automated procedure was devised based on deep learning techniques for identifying soft-story buildings from street-view images at a regional scale. A database containing a large number of building images and a semi-automated image labeling approach that effectively annotates new database entries was developed for developing the deep learning model. Extensive computational experiments were carried out to examine the effectiveness of the proposed procedure, and to gain insights into automated soft-story building identification.
文摘With the continuous calls for energy conservation and emission reduction in recent years,more and more people choose walking as their travel mode.The improvement of the quality of street space will directly affect people's willingness to walk.By sorting out relevant research on street quality measurement,extracting quality keywords with high frequency of reference as impact factors,and using street view image data from different eras,semantic segmentation technology,factor analysis,and questionnaire survey methods,this paper evaluates the street quality of Jingshan East Street,Dongcheng District,Beijing,further explores the impact of different factors on street quality,and analyzes possible ways to improve it.
文摘Regular evaluation of street space is essential for achieving sustainable development and dynamic maintenance of historic areas.Although quantitative evaluations using street view imagery are precise and efficient,they often fall short in capturing pedestrians’visual experience,largely because images are collected from vehicles.Accordingly,this paper acquires street view imagery in the human visual field before and after the street space renovation by adjusting relevant parameters,and performs image semantic segmentation.From a pedestrian’s viewpoint,the paper develops street space evaluation indicators across four dimensions:comfort,identity,diversity,and walkability.The mean square deviation method is applied to assign weights to these indicators,enabling a comprehensive evaluation of street space in historic areas.In addition to evaluating the renovation results,it proposes improvement suggestions that may provide insights into the evaluation practices of street space renovations in historic areas and contribute to improving street space quality.
基金Sponsored by the Key Project of Humanities and Social Sciences in Higher Education Institutions in Hebei Province(SD201075)the Research and Practice Project of Higher Education Teaching Reform in Hebei Province(2019GJJG249)the Construction Project of Postgraduate Demonstration Courses in Hebei Province(KCJS2019069)。
文摘In order to comprehensively and objectively understand the research status of street form at home and abroad,WOS and CNKI database are as the source,and 176 street form papers retrieved from 2010 to 2021 are as samples to conduct statistical analysis of the data.The main research hotspots are reviewed systematically,and the research trends in the field of planning and architecture are pointed out.The hot topics of street form research in the past ten years are summarized,such as street spatial form characteristics,street form and thermal environment,air quality correlation,street form and walking,safety,vitality,health and other perceived correlations.The research methods are summarized from two levels of street form data collection and analysis.Finally,the current research trend characteristics and future trends are summarized and prospected to provide reference for the current research of street form.