Seasonal Spatial Activity Patterns of Visitors with a Mobile Exercise Application at Seoraksan National Park, South Korea

Kim, Jinwon; Thapa, Brijesh; Jang, Seongsoo; Yang, Eunjung

doi:10.3390/su10072263

Cited by 29 publications

(12 citation statements)

References 41 publications

(53 reference statements)

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“…Natural (or physical) seasonality represents the temporal variation in the natural environment. The influencing factors of natural seasonality can be the climate and weather in national parks and their effects on particular seasonal qualities (such as leaf colour), and visitors' personal preferences [14,15]. Another dimension of tourism variation Sustainability 2021, 13, 1681 2 of 17 is the institutional seasonality, which has three driving factors, including holidays, travel motivations and events held at the destination [12,16].…”

Section: Introductionmentioning

confidence: 99%

Seasonal Variation in Visitor Satisfaction and Its Management Implications in Banff National Park

Geng

Innes

et al. 2021

Sustainability

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Seasonal variations in tourist satisfaction is an important issue for the sustainable management of national parks worldwide. Visitors should have high-quality experiences in both the high season and the off-season. This research investigated visitor satisfaction patterns and determinants in Banff National Park in different seasons. The study was conducted through a face-to-face questionnaire survey that collected visitor demographic, expectation and satisfaction data in July 2019 (high season) and December 2019 (off-season) in Banff National Park. The data analyses were based on a sample of 741 respondents and were processed using principal component analysis, correlation analysis and logistic regression models for different seasons. There were significant differences in visitor satisfaction levels and their determinants in different seasons. The quality of the park’s natural characteristics and the park’s activities were the most important determinant of visitor satisfaction in the high season and off-season, respectively. The correlation between visitor satisfaction and expectations in the high season was generally negative, whereas all correlations in the off-season were positive. The results fill a knowledge gap by examining the seasonal differences in visitor experience and their determinants in the national park, and by building a bridge between visitor experience and tourism seasonality. The findings may assist both practitioners and scholars in understanding visitor expectations and satisfaction in different seasons. They may assist in the prioritization and effective management of the park to optimize the visitor experience in both seasons and achieve tourism sustainability.

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Section: Introductionmentioning

confidence: 99%

Seasonal Variation in Visitor Satisfaction and Its Management Implications in Banff National Park

Geng

Innes

et al. 2021

Sustainability

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“…When analyzing spatial data, it is essential to define the unit of analysis because the results of spatial data analysis are influenced by the size and nature of the areal unit employed (Kim, Jang, Kang, and Kim ; Kim, Thapa, Jang, and Yang ; Xu, Pennington‐Gray, and Kim ). Previous studies have assessed the environmental justice of POSs at the CB (Lotfi and Koohsari ), CBG (Abercrombie et al.…”

Section: Methodsmentioning

confidence: 99%

Environmental Justice and Public Beach Access

Kim

Lyu²,

Song

2019

City & Community

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Beaches are an important recreational setting due to their provision of ideal open spaces for diverse water‐ and land‐based recreation opportunities. Despite the importance of assessing the environmental justice of public beach access, few empirical studies have been conducted in community recreation. Using an environmental justice framework, this study examined whether inequities exist for certain racial/ethnic and socioeconomic groups with respect to the distribution of public beach access in the Detroit Metropolitan Area. Results indicated that inequitable public beach access is associated with population density, median housing value, elderly population, and nonvehicle ownership. Such findings can help public leisure agencies to assess environmental justice, a first step in developing more effective community recreation planning and management policies. Study implications, limitations, and recommendations for further research are also discussed.

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“…As questionnaire-based methods are limited by a lack of data, it is difficult to use this traditional method to explore human mobility deeply and accurately. With collection of large volumes of individual trajectory data [3][4][5]. Currently, such data have been widely applied in human mobility pattern research [6][7][8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Revealing Spatial-Temporal Characteristics and Patterns of Urban Travel: A Large-Scale Analysis and Visualization Study with Taxi GPS Data

Huang

Zeng

2019

IJGI

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Mobility and spatial interaction data have become increasingly available due to the widespread adoption of location-aware technologies. Examples of mobile data include human daily activities, vehicle trajectories, and animal movements. In this study we focus on a special type of mobility data, i.e., origin–destination (OD) pairs, and propose a new adapted chord diagram plot to reveal the urban human travel spatial-temporal characteristics and patterns of a seven-day taxi trajectory data set collected in Beijing; this large scale data set includes approximately 88.5 million trips of anonymous customers. The spatial distribution patterns of the pick-up points (PUPs) and the drop-off points (DOPs) on weekdays and weekends are analyzed first. The maximum of the morning and the evening peaks are at 8:00–10:00 and 17:00–19:00. The morning peaks of taxis are delayed by 0.5–1 h compared with the commuting morning peaks. Second, travel demand, intensity, time, and distance on weekdays and weekends are analyzed to explore human mobility. The travel demand and high-intensity travel of residents in Beijing is mainly concentrated within the 6th Ring Road. The residents who travel long distances (>10 km) and for a long time (>60 min) mainly from outside the 6th Ring Road and the surrounding new towns of Beijing. The circular structure of the travel distance distribution also confirms the single-center urban structure of Beijing. Finally, a new adapted chord diagram plot is proposed to achieve the spatial-temporal scale visualization of taxi trajectory origin–destination (OD) flows. The method can characterize the volume, direction, and properties of OD flows in multiple spatial-temporal scales; it is implemented using a circular visualization package in R (circlize). Through the visualization experiment of taxi GPS trajectory data in Beijing, the results show that the proposed visualization technology is able to characterize the spatial-temporal patterns of trajectory OD flows in multiple spatial-temporal scales. These results are expected to enhance current urban mobility research and suggest some interesting avenues for future research.

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Seasonal Spatial Activity Patterns of Visitors with a Mobile Exercise Application at Seoraksan National Park, South Korea

Cited by 29 publications

References 41 publications

Seasonal Variation in Visitor Satisfaction and Its Management Implications in Banff National Park

Seasonal Variation in Visitor Satisfaction and Its Management Implications in Banff National Park

Environmental Justice and Public Beach Access

Revealing Spatial-Temporal Characteristics and Patterns of Urban Travel: A Large-Scale Analysis and Visualization Study with Taxi GPS Data

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