Abstract
The emergence of bicycle sharing has greatly impacted the urban transportation structure and residents' travel modes. The massive spatial-temporal data carried by it is of great significance for studying the characteristics of residents' slow travel and guiding the development of green transportation in cities. Through the analysis of Xiamen's bicycle sharing order data, this paper analyzes the riding characteristics of users and explores the urban functional elements that affect the use of bicycle sharing. This paper will use urban bicycle sharing data, Point of Interest (POI) data in internet maps, and population distribution data to carry out mining and analysis on the travel characteristics and spatial distribution features of bicycle sharing.
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