ArticlePloS one2024
A study of the changing characteristics and influencing factors of holiday visitor vitality in Urban parks: The case of Fuzhou, China.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The vitality of urban parks reflects the intensity of green space utilization, gauging visitors' overall perception of the parks, facilitating integrated park management, and ensuring the parks' sustainable development. But, the park's spatial vitality characteristics change over time, and the factors influencing the differences in vitality have not been conclusively established. Therefore, This study employs Baidu heat map data to examine the spatial and temporal distribution patterns of park visitor vitality on holidays and weekdays in urban parks located in the core urban region of Fuzhou City. Meanwhile, this will be achieved by utilizing a geo-detector and MGWR model to examine the factors influencing visitor vitality and analyze the spatial variations in the impact coefficients. The conclusions are as follows: (1)Park vitality varied dramatically between different periods, with park vitality being higher on holidays than on weekdays. The peaks of vitality are all concentrated at 10:00 and 16:00. The park's vitality on holidays had a pattern of many peaks, with a wave-like fluctuation. On weekdays, there was a notable M-shaped feature. (2)The spatial distribution of vitality has a "bimodal" pattern with two distinct cores and numerous fragmented fragments. There are notable variations in the spatial liveliness of different parks, characterized by a distinct "long-tail effect." In other words, there are just a few parks with high vitality, while many parks have low vitality. (3)The peripheral location features (G2) and the characteristics of transportation infrastructure (G3)are the main factors affecting park vitality; X11 amenities have the highest coefficient of impact on park vitality (0.501 on weekdays and 0.491 on holidays). The factors within the Park attributes (G1) and the park's social media level (G4) showed a two-way interaction strength increase. (4)The coefficients of influence of impact factors on the space heterogeneity of vacation park vitality exhibit significant variation. The positive indicators have a spatial distribution that decreases from the northwest to the southeast, with the old city district having higher coefficients than the new city district. The negative indicators display the reverse pattern. This study offers scientific methodologies and recommendations for improving and designing urban park landscapes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.