ISPRS International Journal of Geo-Information

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23 pages, 35278 KiB

Open AccessArticle

Density-Based Spatial Clustering and Ordering Points Approach for Characterizations of Tourist Behaviour

by Jorge Rodríguez-Echeverría, Ivana Semanjski, Casper Van Gheluwe, Daniel Ochoa, Harm IJben and Sidharta Gautama

ISPRS Int. J. Geo-Inf. 2020, 9(11), 686; https://doi.org/10.3390/ijgi9110686 - 17 Nov 2020

Cited by 8 | Viewed by 3785

Abstract

Knowledge about the spots where tourist activity is undertaken, including which segments from the tourist market visit them, is valuable information for tourist service managers. Nowadays, crowdsourced smartphones applications are used as part of tourist surveys looking for knowledge about the tourist in [...] Read more.

Knowledge about the spots where tourist activity is undertaken, including which segments from the tourist market visit them, is valuable information for tourist service managers. Nowadays, crowdsourced smartphones applications are used as part of tourist surveys looking for knowledge about the tourist in all phases of their journey. However, the representativeness of this type of source, or how to validate the outcomes, are part of the issues that still need to be solved. In this research, a method to discover hotspots using clustering techniques and give to these hotspots a data-driven interpretation is proposed. The representativeness of the dataset and the validation of the results against existing statistics is assessed. The method was evaluated using 124,725 trips, which have been gathered by 1505 devices. The results show that the proposed approach successfully detects hotspots related with the most common activities developed by overnight tourists and repeat visitors in the region under study. Full article

(This article belongs to the Special Issue Smart Tourism: A GIS-Based Approach)

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23 pages, 2075 KiB

Open AccessArticle

Spatial Intensity in Tourism Accommodation: Modelling Differences in Trends for Several Types through Poisson Models

by Mª Cristina Rodríguez-Rangel, Marcelino Sánchez-Rivero and Julián Ramajo-Hernández

ISPRS Int. J. Geo-Inf. 2020, 9(8), 473; https://doi.org/10.3390/ijgi9080473 - 28 Jul 2020

Cited by 4 | Viewed by 2858

Abstract

The distribution pattern of tourist activity in space represents valuable information to improve the management of a tourist destination. This is why there is a trend in the current literature in proposing modelling that allows for the incorporation of how tourist activity is [...] Read more.

The distribution pattern of tourist activity in space represents valuable information to improve the management of a tourist destination. This is why there is a trend in the current literature in proposing modelling that allows for the incorporation of how tourist activity is distributed in an operational way in order to characterize and measure the patterns identified for tourism management. The present study focuses on carrying out this modelling in an inland territory in an expansion phase which, according to the knowledge available from previous work, presents a strong territorial imbalance in the distribution of its housing pool, the region of Extremadura in Spain. For this reason, tourism intensity is modelled through a Poisson process to determine which model best fits the pattern of accommodation in the region. The results represent a valuable tool for public–private management of the tourism sector in the area under study. Full article

(This article belongs to the Special Issue Smart Tourism: A GIS-Based Approach)

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23 pages, 3843 KiB

Open AccessArticle

Spatial Analysis of Asymmetry in the Development of Tourism Infrastructure in the Borderlands: The Case of the Bystrzyckie and Orlickie Mountains

by Michalina Jędruch, Marek Furmankiewicz and Iwona Kaczmarek

ISPRS Int. J. Geo-Inf. 2020, 9(8), 470; https://doi.org/10.3390/ijgi9080470 - 26 Jul 2020

Cited by 6 | Viewed by 2898

Abstract

This paper discusses the issue of analyzing the development of cross-border tourism infrastructure in the borderlands of countries with diversified administrative divisions and spatial databases, which hinders the use of national statistical units for comparative research. As an example, the ability to use [...] Read more.

This paper discusses the issue of analyzing the development of cross-border tourism infrastructure in the borderlands of countries with diversified administrative divisions and spatial databases, which hinders the use of national statistical units for comparative research. As an example, the ability to use the square grid and kernel density estimation methods for the analysis and spatial visualization of the level of tourism infrastructure development is studied for the Orlickie and Bystrzyckie Mountains, located in the Polish–Czech border area. To synthetically assess and compare the level of diversity, the methodology used in the Human Development Index was adapted using selected component indicators calculated for a square grid clipped to the boundaries of the area under study. This analysis enabled us to quantify the asymmetry in the development of tourism infrastructure in the borderlands via the calculation of the synthetic infrastructure development index. This index is 1.29 times higher in the Czech than in the Polish border area. However, the spatial concentration analysis of infrastructure shows that the diversity in the study area can be assessed as higher than the results using the average density indicators. This paper also discusses the benefits and problems associated with using the square grid method for the representation and analysis of heterogeneous data on tourism infrastructure in two neighboring national states. Full article

(This article belongs to the Special Issue Smart Tourism: A GIS-Based Approach)

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17 pages, 2780 KiB

Open AccessEditor’s ChoiceArticle

Meet the Virtual Jeju Dol Harubang—The Mixed VR/AR Application for Cultural Immersion in Korea’s Main Heritage

by Kwanghee Jung, Vinh T. Nguyen, Diana Piscarac and Seung-Chul Yoo

ISPRS Int. J. Geo-Inf. 2020, 9(6), 367; https://doi.org/10.3390/ijgi9060367 - 2 Jun 2020

Cited by 54 | Viewed by 7843

Abstract

Jeju Island comes second to only Seoul as Korea’s most visited destination, yet most visitors do not have the chance to go beyond brief visits and immerse themselves in the island’s history and cultural heritage. This project introduces the cultural heritage of Jeju [...] Read more.

Jeju Island comes second to only Seoul as Korea’s most visited destination, yet most visitors do not have the chance to go beyond brief visits and immerse themselves in the island’s history and cultural heritage. This project introduces the cultural heritage of Jeju Island to visitors through virtual reality/augmented reality (VR/AR) model visualization technology, namely JejuView, which provides an intuitive way to experience cultural heritage sites on the island. The proposed VR/AR application is designed to introduce a series of heritage spots on Jeju Island through (i) a printed Jeju map with embedded QR code markers that enable viewers to experience the locations without being present at the site, (ii) a mobile device with WebGL supported browser which allows 3D content to be rendered, and (iii) an AR library (A-Frame.io) that enables enthusiasts to recreate similar work. To test the effectiveness of the proposed VR/AR application, the authors conducted an experiment with 251 participants to test the research model based on the technology acceptance model (TAM) and employed generalized structured component analysis (GSCA) for the analysis. Results show that when using sensory new media such as VR/AR, consumers are more focused on the hedonic value than on the utilitarian value of the information. In conclusion, the proposed VR/AR application is complementary to existing studies and provides significant support to researchers, engineers, and designers developing VR/AR technologies for use in cultural education and tourism marketing. Full article

(This article belongs to the Special Issue Smart Tourism: A GIS-Based Approach)

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20 pages, 2447 KiB

Open AccessFeature PaperArticle

Selecting Prices Determinants and Including Spatial Effects in Peer-to-Peer Accommodation

by Rafael Suárez-Vega and Juan M. Hernández

ISPRS Int. J. Geo-Inf. 2020, 9(4), 259; https://doi.org/10.3390/ijgi9040259 - 19 Apr 2020

Cited by 10 | Viewed by 3000

Abstract

Peer-to-peer accommodation has grown significantly during the last decades, supported, in part, by digital platforms. These websites make available a wide range of information intended to help the customers’ decision. All these factors, in addition to the property location, may therefore influence rental [...] Read more.

Peer-to-peer accommodation has grown significantly during the last decades, supported, in part, by digital platforms. These websites make available a wide range of information intended to help the customers’ decision. All these factors, in addition to the property location, may therefore influence rental price. This paper proposes different procedures for an efficient selection of a high number of price determinants in peer-to-peer accommodation when applying the perspective of the geographically weighted regression. As a case study, these procedures have been used to find the factors affecting the rental price of properties advertised on Airbnb in Gran Canaria (Spain). The results show that geographically weighted regression obtains better indicators of goodness of fit than the traditional ordinary least squares method, making it possible to identify those attributes influencing price and how their effect varies according to property locations. Moreover, the results also show that the selection procedures working directly on geographically weighted regression obtain better results than those that take good global solutions as their starting point. Full article

(This article belongs to the Special Issue Smart Tourism: A GIS-Based Approach)

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17 pages, 1253 KiB

Open AccessArticle

Assessing Safety and Suitability of Old Trails for Hiking Using Ground and Drone Surveys

by Shiou Yih Lee, Chengju Du, Zhihui Chen, Hao Wu, Kailang Guan, Yirong Liu, Yongjie Cui, Wenyan Li, Qiang Fan and Wenbo Liao

ISPRS Int. J. Geo-Inf. 2020, 9(4), 221; https://doi.org/10.3390/ijgi9040221 - 7 Apr 2020

Cited by 12 | Viewed by 4980

Abstract

Hiking is a popular recreational activity and to cater to public demand, it is apt to increase the number of hiking trails. Various methodologies have been proposed to evaluate the suitability of forest trails to be constructed as hiking trails, but they can [...] Read more.

Hiking is a popular recreational activity and to cater to public demand, it is apt to increase the number of hiking trails. Various methodologies have been proposed to evaluate the suitability of forest trails to be constructed as hiking trails, but they can be costly and require relevant knowledge in analyzing digital information through a high-throughput dataset. Therefore, there is a need to come up with a simple method to obtain first-hand information on the trail condition, particularly considering the aspects of safety and suitability to hikers, using both on-ground and aerial observations. In this study, we introduce a new assessment approach to analyze and select old forest trails to be reconstructed as new hiking trails. This is useful for park managers who prioritize safety, comfort, and aesthetic features of the recreation site for their visitors. Trail condition assessment was carried out along the trail whereby a 2×2 m sampling plot was constructed at every 100 m. Aerial drone survey was conducted to produce an ortho-mosaic that revealed the percentage of exposed trail from above. Potential phytotourism products and scenic spots were identified and recorded for their locations along the trail to promote the aesthetic value of the recreation site. A strength distribution plot was prepared based on the trail condition, canopy coverage, and aesthetic features along the trail that were categorized using three altitude ranges (n ≤ 150 m, 150 < n < 250 m, n ≥ 250 m a.s.l.). This is to assess the trade-offs in safety, comfort, and aesthetic features along the trail. The development of this methodology offers a direct and cost-effective, yet informative approach to evaluate the quality of a potential hiking trail, thus could effectively aid in the promotion of nature-based tourism. Full article

(This article belongs to the Special Issue Smart Tourism: A GIS-Based Approach)

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35 pages, 4296 KiB

Open AccessArticle

Smart Tour Route Planning Algorithm Based on Naïve Bayes Interest Data Mining Machine Learning

by Xiao Zhou, Mingzhan Su, Zhong Liu, Yu Hu, Bin Sun and Guanghui Feng

ISPRS Int. J. Geo-Inf. 2020, 9(2), 112; https://doi.org/10.3390/ijgi9020112 - 19 Feb 2020

Cited by 16 | Viewed by 4925

Abstract

A smart tour route planning algorithm based on a Naïve Bayes interest data mining machine learning is brought forward in the paper, according to the problems of current tour route planning methods. A machine learning model of Naïve Bayes interest data mining is [...] Read more.

A smart tour route planning algorithm based on a Naïve Bayes interest data mining machine learning is brought forward in the paper, according to the problems of current tour route planning methods. A machine learning model of Naïve Bayes interest data mining is set up by learning a mass of training data on tourists’ interests and needs. Through the recommended interest tourist site classifications from the machine learning module, the optimal tourist site mining algorithm based on the membership degree searching propagating tree of a tourist’s temporary accommodation is set up, which mines and outputs the optimal tourist sites. The mined optimal tourist sites are taken as seed points to set up a tour route planning algorithm based on the optimal propagating tree of a closed-loop structure. Through the proposed algorithm, an experiment is designed and performed to output optimal tour routes conforming to tourists’ needs and interests, including the propagating tree closed-loop structures, a minimum heap of propagating tree weight function value, and a weight function value complete binary tree. We prove that the proposed algorithm has the features of intelligence and accuracy, and it can learn tourists’ needs and interests to output optimal tourist sites and tour routes and ensure that tourists can get the best motive benefits and travel experience in the tour process, by analyzing the experiment data and results. Full article

(This article belongs to the Special Issue Smart Tourism: A GIS-Based Approach)

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15 pages, 4795 KiB

Open AccessArticle

RETRACTED: Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network’s Data from Weibo

by Naimat Ullah Khan, Wanggen Wan and Shui Yu

ISPRS Int. J. Geo-Inf. 2020, 9(2), 70; https://doi.org/10.3390/ijgi9020070 - 21 Jan 2020

Cited by 17 | Viewed by 5027 | Retraction

Abstract

The aim of this study is to analyze and compare the patterns of behavior of tourists and residents from Location-Based Social Network (LBSN) data in Shanghai, China using various spatiotemporal analysis techniques at different venue categories. The paper presents the applications of location-based [...] Read more.

The aim of this study is to analyze and compare the patterns of behavior of tourists and residents from Location-Based Social Network (LBSN) data in Shanghai, China using various spatiotemporal analysis techniques at different venue categories. The paper presents the applications of location-based social network’s data by exploring the patterns in check-ins over a period of six months. We acquired the geo-location information from one of the most famous Chinese microblogs called Sina-Weibo (Weibo). The extracted data is translated into the Geographical Information Systems (GIS) format, and compared with the help of temporal statistical analysis and kernel density estimation. The venue classification is done by using information regarding the nature of physical locations. The findings reveal that the spatial activities of tourists are more concentrated as compared to those of residents, particularly in downtown, while the residents also visited suburban areas and the temporal activities of tourists varied significantly while the residents’ activities showed relatively stable behavior. These results can be applied in destination management, urban planning, and smart city development. Full article

(This article belongs to the Special Issue Smart Tourism: A GIS-Based Approach)

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Other

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1 pages, 173 KiB

Open AccessRetraction

RETRACTED: Khan et al. Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network’s Data from Weibo. ISPRS Int. J. Geo-Inf. 2020, 9, 70

by IJGI Editorial Office

ISPRS Int. J. Geo-Inf. 2020, 9(12), 723; https://doi.org/10.3390/ijgi9120723 - 3 Dec 2020

Viewed by 1994

Abstract

The IJGI Editorial Office has been made aware that the published paper [...] Full article

(This article belongs to the Special Issue Smart Tourism: A GIS-Based Approach)

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