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Emerging social media data on measuring urban park use
داده های جدید رسانه های اجتماعی در مورد اندازه گیری استفاده از پارک های شهری-2018 Green urban infrastructure, which serves the interests of both human and nature, are considered as essential
assets of urban residents. However, measuring the use of green space has been problematic. Because, most
previously used data on measuring green space use are self-reported or collected via social surveys, which
not only include limited samples, but also are always subjective, costly, and laborious. This study integrates
sensor and positioning technologies and measures the use of green space from an emerging big data per
spective. The hourly real-time Tencent user density (RTUD) data from social media are used to analyze the
time-spatial distribution of urban park users. RTUD data, park attributes, and surrounding landscape fea
tures are incorporated into ArcGIS for spatial analysis. A group of linear regression models is constructed to
determine factors that may be associated with the user density of urban parks. The total accumulated
number of observed users is 3.25 million in 686 urban parks of Shenzhen in two typical sunny days – a work
day and a rest day. Without costly and laborious field investigation, based on RTUD data, we conduct a city
wide analysis regarding all parks. The proposed method is proved to be suitable for measuring urban green
space use at city-level or even large scale. Results show that park user density is relatively high in well
developed areas and community parks. Park attributes and surrounding landscape features are significantly
associated to park use. The findings of this study can help policy makers optimize the construction and
maintenance of urban parks.
Keywords: Green space ، RTUD data ، Shenzhen ، Time-spatial distribution، User density |
مقاله انگلیسی |