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Human-Scale Sustainability Assessment of Urban Intersections Based upon Multi-Source Big Data

Yuhuan Zhang, Huapu Lu, Shengxi Luo, Zhiyuan Sun and Wencong Qu
Additional contact information
Yuhuan Zhang: Institute of Transportation Engineering, Tsinghua University, Beijing 100084, China
Huapu Lu: Institute of Transportation Engineering, Tsinghua University, Beijing 100084, China
Shengxi Luo: Institute of Transportation Engineering, Tsinghua University, Beijing 100084, China
Zhiyuan Sun: College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China
Wencong Qu: Road Transport Books Center, China Communications Press Co., Ltd., Beijing 100011, China

Sustainability, 2017, vol. 9, issue 7, 1-22

Abstract: 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.

Keywords: sustainability; intersection; multi-source big data fusion; human-scale; information entropy method; image recognition (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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