Abstract：With the development of big data technology and information tools, more and more post occupancy evaluation studies based on network data, machine learning and other analysis methods have more positive influences on these studies. This study explores an analysis method building the relationship between streetscape elements and kansei evaluation values to achieve post occupancy evaluation of street renewal, combined with online streetscape image data and deep learning technology. The method is then used for evaluations in Shichahai historical districts. Finally, with the heat map and the questionnaire investigation based on street photos, the evaluation conclusions are tested to ensure the reliability of the evaluation method. The meanings of the post occupancy evaluation for historical block renewal based on online photos are summarized. Eventually extended research is discussed to improve the evaluation method.
王昭雨，庄惟敏*. 基于图像深度学习的街区更新后评估方法研究 ——以北京什刹海街区为例[J]. 新建筑, 2022, 40(3): 5-8.
WANG Zhaoyu,ZHUANG Weimin. Research on Block Renewal Post Occupancy Evaluation Methods Based on Image Deep Learning: A Case Study of Shichahai in Beijing. New Architecture, 2022, 40(3): 5-8.
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