TANG Luliang, ZOU Qianqian, ZHANG Xia, REN Chang, LI Qingquan. Online and Offline Trajectory Data Fusion and Evaluation of Landscape Attractions[J]. Geomatics and Information Science of Wuhan University, 2018, 43(11): 1704-1711. DOI: 10.13203/j.whugis20170043
Citation: TANG Luliang, ZOU Qianqian, ZHANG Xia, REN Chang, LI Qingquan. Online and Offline Trajectory Data Fusion and Evaluation of Landscape Attractions[J]. Geomatics and Information Science of Wuhan University, 2018, 43(11): 1704-1711. DOI: 10.13203/j.whugis20170043

Online and Offline Trajectory Data Fusion and Evaluation of Landscape Attractions

  • In real space and cyberspace, people leave both online and offline traces of their daily lives, which might affect the behavior of other people.This pattern is similar to insect foraging behaviors based on pheromone reaction.Previous landscape evaluation only used questionnaires, network data, or GPS data, ignoring the relationship between online and offline activities in this mobile internet era, as well as overlooking the influence of previous activities on future behaviors.In this paper, the new model, based on the idea of pheromone, couples big website data with GPS trajectory data to analyze spatio-temporal recreational behaviors in real space and cyberspace, and finally evaluates the attractiveness of locations.To test the method, twenty-eight landscapes in Beijing were evaluated, using big website data and GPS trajectory datasets collected from 181 users over a period of about five years.The results show that this new method could be very promising, which outperforms the methods that only consider online data or offline data.
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