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  • 标题:Human-Scale Sustainability Assessment of Urban Intersections Based upon Multi-Source Big Data
  • 本地全文:下载
  • 作者:Zhang, Yuhuan ; Lu, Huapu ; Luo, Shengxi
  • 期刊名称:Sustainability
  • 印刷版ISSN:2071-1050
  • 出版年度:2017
  • 卷号:9
  • 期号:7
  • 页码:1-22
  • 出版社:MDPI, Open Access Journal
  • 摘要:To evaluate the sustainability of an enormous number of urban intersections, a novel assessment model is proposed, along with an indicator system and corresponding methods to determine the indicators. Considering mainly the demands and feelings of the urban residents, the three aspects of safety, functionality, and image perception are taken into account in the indicator system. Based on technologies such as street view picture crawling, image segmentation, and edge detection, GIS spatial data analysis, a rapid automated assessment method, and a corresponding multi-source database are built up to determine the indicators. The improved information entropy method is applied to obtain the entropy weights of each indicator. A case study shows the efficiency and applicability of the proposed assessment model, indicator system and algorithm.
  • 关键词:sustainability; intersection; multi-source big data fusion; human-scale; information entropy method; image recognition
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