Ye Yu, Zhang Zhaoxi, Zhang Xiaohu, Zeng Wei

Keywords： Street Quality; Accessibility; Machine Learning; Human-centered Perspective; Street View Image; Street

Abstract：

This study provides an operational framework about street quality measurement by the means of large-scale data analysis at the humanistic scale and the results can be regarded as the benchmark for the renewal of urban street space. Taking Hongkou District and Yangpu District of Shanghai as an example, based on Street View Images (SVI) data, this paper takes advantage of machine learning to extract spatial feature, then uses neural network (ANN) to measure the quality of street places with wide distribution and fine resolution. Besides that, an evaluation matrix established by overlapping analysis will combine quality evaluation with network accessibility analysis (sDNA). Finally, we find out those “potential streets” and provide fine theoretical foundation for urban micro-renewal.

Funds：

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