Online and Offline Trajectory Data Fusion and Evaluation of Landscape Attractions

TANG Luliang; ZOU Qianqian; ZHANG Xia; REN Chang; LI Qingquan

doi:10.13203/j.whugis20170043

Volume 43 Issue 11

Nov. 2018

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Geomatics and Information Science of Wuhan University > 2018 > 43(11): 1704-1711. > DOI: 10.13203/j.whugis20170043

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

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Online and Offline Trajectory Data Fusion and Evaluation of Landscape Attractions

1.
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2.
School of Urban Design, Wuhan University, Wuhan 430072, China
3.
Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China

Funds:

The National Key Research and Development Program of China 2017YFB0503604

the National Natural Science Foundation of China 41671442

the National Natural Science Foundation of China 41571430

the National Natural Science Foundation of China 41271442

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Author Bio:
TANG Luliang, PhD, professor, specializes in spatio-temporal GIS, big data mining & spatio-temporal modeling and GIS for tansportation geography.E-mail:tll@whu.edu.cn
Corresponding author:
ZOU Qianqian, master.E-mail:zqq77@whu.edu.cn
Received Date: July 16, 2017
Published Date: November 04, 2018

Graphical Abstract

Abstract

Abstract

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.
- data fusion,
- spatio-temporal behavior,
- landscape evaluation,
- big data,
- web hotspots

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References

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