Open access peer-reviewed chapter

The Use of Photos of the Social Networks in Shaping a New Tourist Destination: Analysis of Clusters in a GIS Environment

Written By

Hélder Tiago da Silva Lopes, Paula Cristina Almeida Cadima Remoaldo and Vitor Ribeiro

Submitted: February 19th, 2018 Reviewed: May 10th, 2018 Published: November 5th, 2018

DOI: 10.5772/intechopen.78598

Chapter metrics overview

1,117 Chapter Downloads

View Full Metrics

Abstract

The use of new photo-sharing services in social networks has favoured a perception of the interests of locals and visitors. The photos presented in these networks are geocoded by the users, residents or visitors, allowing extensive databases to be obtained. The research that was conducted between 2015 and 2016 followed an essentially quantitative approach. Based on the georeferenced photos on social networks, the main distribution patterns of places of interest to tourists, visitors and residents were analysed in a rural emergent tourist destination in northeastern Portugal. We used geographical information systems (GISs) to apply various spatial and statistical analysis techniques. One the main conclusions was that there is a high number of natural and cultural heritage locations with tourism potential, and, in some cases, their accessibility standards make them favourable destinations for tourists.

Keywords

  • rural tourism
  • spatial analysis
  • accessibility
  • photo-sharing services
  • GIS

1. Introduction

The development of new methods of analysis of the images of various destinations has accompanied the emergence of extensive research that uses the method of analysing photos [1, 2, 3, 4, 5]. Another fact is due to the massive use of the Internet, which is increasingly introducing significant changes in the way people interact in society [6, 7]. This new dimension of communication has made the expression of multiple cultural values possible [8]. Because of the evolution of the Internet and the advent of smart technology, the proliferation of the number of photos registered per trip has occurred in recent decades [9]. However, the habit of sharing them with co-workers, family and friends, as well as in the broader media, comes as a result of online sharing, often in real time and synchronously on various websites, such as Flickr, Picasa, Facebook, Panoramio and Pinterest [4, 10, 11, 12, 13, 14, 15].

Images have assumed a fundamental role in the dissemination of the dimensions and amplitudes of tourist spaces. The sharing of photos of a place through social networks has an increasingly strong power in promoting tourism, where the dissemination of the tourist image has an effective and lasting role. Different social media platforms have been accommodating new features, and coupled with their simplicity of handling and attractiveness, they are competing increasingly with traditional travel guides or leaflets because they allow people to post photographs on the Internet immediately after they are taken [4, 12, 13, 16, 17, 18, 19, 20, 21]. However, it should be noted that these platforms still tend to be used by the younger age groups and by groups with higher socioeconomic characteristics.

Conversely, research centred on the analysis of online images of rural destinations has not been explored extensively [22, 23, 24]. Increasingly, urban dwellers’ interest in staying overnight and visiting rural areas shows that it is essential to market and promote rural destinations online [18, 25, 26, 27, 28, 29].

With the evolution of geographic information technologies, it is possible to analyse distribution patterns (intensity, concentration and dispersion) of tourism resources in different spaces through density maps, central trend measures or with the use of indicators of distribution patterns (e.g. Getis-Ord General G or Moran’s Index).

Based on these assumptions, the main objectives of this research are (i) to identify the spatial distribution patterns of the photos of visitors and residents; (ii) to characterise the different “looks” of the tourist destination and (iii) to contribute to the development of a tourist image that is closer to the interests of visitors and locals. This study complements other approaches undertaken in the territory, resulting mainly from an exploratory analysis of existing and potential tourism resources, the results of the focus group that was conducted, and the results of a self-administered survey [30, 31].

This chapter consists of four sections. After the introductory section, the second section presents the main methods and sources used to acquire the data that were used. Section 3 is a summary of the main results that were achieved, and it highlights the main potentialities of the analysis of the images and how they can contribute to the segmentation of the visitors. Section 4 presents our discussions. Section 5 presents the conclusions concerning the main results, proposes some challenges for future research and identifies the main limitations that were intrinsic to the study.

Advertisement

2. Materials and methods used in the study area

2.1. Geographical context

The case study was based on the municipality of Boticas, which is located in the Nomenclature of Territorial Units for Statistics (NUTS) III of Alto Tâmega in the northeast of Continental Portugal. According to the Typology of Urban Areas (TIPAU) of 2014, seven of the parishes are considered Medium Urban Areas (MUA) and three as Predominantly Rural Areas (PRA) [32]. The area is subdivided into 10 parishes, with an area of 322 km2 (Figure 1). In 2011 (last census), the population of the municipality of Boticas was 5750, of which 1510 residents (26.3% of the population) lived in Boticas and Granja. In fact, this municipality, like other territories located in the interior of the country, has lost its vitality. One of the municipality’s main potentials is the use of its endogenous resources to attract tourists, associated economic activities and to enhance its population.

Figure 1.

Geographical context of the municipality of Boticas: Population by subsection, TIPAU and MDT. Source: Own elaboration (based on the Census, 2011; TIPAU 2014 (INE) and Atlas of the Environment).

2.2. Materials and methods

The database used in this research was constructed with data from Panoramio’s photo platform, Google Earth. The period from January 2005 to March 2016 was used, and 728 photos were used. The photos were analysed by two quantitative methods, that is, (1) univariate and multivariate statistical analysis using the SPSS 22.0 statistical package and (2) geospatial analysis using the ArcGIS 10.3 package. The data were grouped into several typologies considering the assumptions defined in previous studies [3, 4, 5]:

  1. Four categories—(1) built heritage (e.g. monuments, historic buildings, churches and typical homes), (2) nature (landscape, fauna and flora), (3) culture (combining expressions of local culture, traditions or festivals) and (4) tourist services (comprising all forms of tourism equipment and infrastructures, such as accommodations, catering and signs). The situations in which images with more than one set of elements were verified always opted for the predominant set.

  2. Zoom of the image—this was analysed by checking the following assumptions: (1) if the image is focused on a single element (e.g. a window of a dwelling or a church), (2) in its context (a church in the housing complex) or (3) whether it is a panoramic view or a scenery (e.g. a mountain or a river).

  3. Presence of people.

  4. Origin—whether the image originates from locals or visitors.

After defining the cataloguing criteria of the images, the main assumptions that are inherent to the analysis of the spatial distribution of the photos should be emphasised:

  1. the data were aggregated in hexagons with 150 m of side and 300 m of diameter;

  2. standard distance calculations were performed to infer the degree of concentration or the dispersion of resources around the mean geometric centre;

  3. two indices were used to determine global localization patterns, that is, Getis-Ord General G and Global Moran’s I. These served to identify the degree of agglomeration of high and low values and the spatial correlation based on local resources and attribute values;

  4. Anselin Local Moran’s statistics (LISA statistics) were used, making it possible to determine emerging local trends for the intensification of Boticas’ tourism.

These typologies were the basis of the identification of clusters. This technique allows the identification of groups with high homogeneity within the group as well as intergroup heterogeneity [3]. The k-means method was used considering the following assumptions: (i) the choice of a sample was made based on a sample in each group, from a group of groups (2–5); (ii) minimum loss of information through the merging of the elements and (iii) instead of considering the categories per se, items were used to segment the groups. After obtaining the clusters, an ANOVA test was performed to determine the differences between the groups.

Advertisement

3. Results

The destination image can be promoted based on the sets of photos that residents and visitors take, considering their ability to become souvenirs, postcards or tourists’ objects. Photo density analysis of Sightsmaps (http://www.sightsmap.com/, developed by [33]) clearly showed a density of photos in more urbanised areas (e.g. Oporto Metropolitan Area (OMP), Braga, Guimarães, Viana do Castelo, Chaves and Bragança) in the course of the Douro River (in Portugal, Barca d’Alva to the mouth between Porto and VN Gaia) or in the Peneda and Gerês National Park (PNPG), which was different from what occurs in territories such as Boticas.

In the municipality of Boticas, as with the other municipalities of Alto Tâmega (with the exception of Chaves), there is a density of photos that were much smaller and circumscribed to the central area of the municipality. Figure 2 summarises the distribution of the photographic series, differing according to whether they were taken by residents or visitors. In general, there is a concentration of photos in the northwest and central areas of the municipality of Boticas, although most of the photos are distributed somewhat throughout the municipality, mainly along the main axes of the road network.

Figure 2.

Geographic distribution of photos of visitors and residents. Source: Panoramio photos, collected during the period from January 2003 through March 2015.

However, it is in the parish of Boticas and Granja that there was a greater density of photos, which was due to the amount of equipment available to visitors. For this reason, in all parishes, there are more photos of visitors than residents (258 for locals and 470 for visitors—Table 1).

ParishLocalsVisitorsTotal
No.%No.%No.%
Alturas do Barroso and Cerdedo8532.910522.319026.1
Dornelas72.7163.4233.2
Ardãos and Bobadela155.8153.2304.1
Boticas and Granja4919.020142.825034.3
Beça3814.77215.311015.1
Pinho00.030.630.4
Codessoso, Curros and Fiães do Tâmega155.8143.0294.0
Covas do Barroso103.991.9192.6
Vilar and Viveiro2810.9245.1527.1
Sapiãos114.3112.3223.0
Total258100470100728100

Table 1.

Distribution of photos by parish (in number and percent).

Source: Panoramio photos, collected for the period from January 2003 through March 2015.

The maximum of photos recorded per hexagon for this group was 55 photos (Table 2).

Number of photosD.P.Maximum of photos per hexagon
Total7281.5666
Locals2380.4317
Visitors4901.2255

Table 2.

Statistics of photos taken by visitors and locals.

Source: Panoramio photos, collected for the period from January 2003 through March 2015.

The grouping of the photos in hexagons shows a concentration of photos to the north of the municipality, and the areas with the lower densities of photos are located to the south, especially in the parish of Pinho (three photos—Figure 3).

Figure 3.

Density of photos: (A) locals, (B) visitors, (C) total. Source: Own elaboration, based on Panoramio photos for the period from January 2003 through March 2015.

To identify the clusters, the G-statistics were analysed, and the Moran index was used. The G-statistics indicated that there was a tendency for the concentration of values (high clusters), with high levels of significance (p-value < 0.01). Likewise, the Moran index indicated a very strong spatial correlation for the formation of spatial agglomerates (p-value < 0.01, Figure 4).

Figure 4.

Anselin local Moran’s statistics. Source: Own elaboration, based on Panoramio photos for the period from January 2003 through March 2015.

The Anselin local Moran’s statistic was calculated with the intention of mapping the presence of these groups, and it was found that the number of clusters with High-High (HH) values was not very significant. Concerning the distribution of these clusters, there was a spatial agglomeration in several villages typical of the municipality (e.g. Vilarinho Sêco, Coimbró), in places of landscape-natural interest (e.g. Carvalhelhos, Mosteiró, Vilarinho de Mó) and in the village centre, either by locals or visitors. There are some differences between places photographed by locals and visitors. The former has High-High (HH) clusters in Coimbró, Serra do Barroso Wind Farm and in Fiães do Tâmega, while the latter have an agglomeration in Sapiãos (e.g. anthropomorphic graves, some typical houses, river beach), which are not present in the photographs made by the residents. It should be noted, however, that there were small clusters expressed in Low-High values, which correspond to atypical values.

Figure 6 presents the typologies created for the photos. The concentration of photos is strongly associated with two types of characteristics, that is, built-heritage (57%) and natural elements (35%). Tourism services (5%) and local culture (4%, Figure 5A) appear less often.

Figure 5.

Typologies of photos (%): (A) category, (B) human presence, (C) zoom, and (D) origin. Source: Own elaboration, based on Panoramio photos for the period from January 2003 through March 2015.

The distances from which the images were photographed were very different. In some cases, the person taking the photos focused only on the details, while others sought to take photographs of the entire scene. Therefore, we chose to classify the photographs into three subgroups, as shown in Figure 5(B). The results allowed us to conclude that 57% of the sites/visitors photographed elements in the context, which reflected the demand of visitors and residents to capture what is within a context, so that it can be recognised easily. Another element used for analysis was the degree of the presence of people in the photos (Figure 5C). The most common circumstance for visitors and residents was to take photos without the presence of people (93%; Figure 5D), and only 7% of the photos included people. In addition, 67.3% of the photos were taken by visitors, showing their renewed interest, which is perfectly understandable. In fact, it is surprising that there were a significant number of locals placing Panoramio photos, which may indicate the recognition of the natural and built heritage that exists in the municipality.

Figure 6 represents the temporal distribution of the photos taken by visitors and locals. It should be noted that the figures do not refer to all of the photos sent to the Panoramio platform over the review period; rather, they refer only to the photos that contain information concerning the dates they were taken.

Figure 6.

Temporal patterns of locals’ and visitors’ photos: (A) photos taken per year with registration of the number of photos and cumulative percentage (% cum) for locals, visitors and both; (B) photos taken per month with percent (%) recorded for locals, visitors and both; (C) photos taken per hour with percentage (%) for locals, visitors and both and cumulative percentage (% cum). Source: Panoramio photos collected for the period from January 2003 through March 2015.

There were 528 photos with year-to-year, intra-annual and intra-day information that were included among the 729 previously classified photos. In fact, the year with the highest number of photographs taken by visitors was 2014, while in the case of locals, the highest number of photographs taken occurred in previous years, that is, between 2006 and 2008 (Figure 6A). Thus, in cumulative terms, there has been a redoubled interest in taking photographs by visitors in recent years. However, when analysing the values recorded monthly in the period from 2013 through 2015, there is a seasonality of the photo records, with a concentration in August (Figure 6B). Concerning the hourly range, these photographs generally were taken between 10:00 am and 5:00 pm (Figure 6C).

It should be noted that residents contributed most to post-5:00 pm photographs, which may be due to the return of excursions to the place of departure after an overnight visit to the Boticas municipality, indicating that the municipality had visitors but not tourists. There are some records during the night period, but they should be viewed with caution because there may have been errors associated with the instruments’ recordings of the time when the photographs were taken.

An analysis also was conducted for the areas with the highest concentration of photos (i.e. the areas classified in Figure 7 with High-High (HH) clusters).

Figure 7.

Time patterns in photos in agglomeration areas (high-high (HH) clusters) in comparison with all photographs: (A) cumulative percentage (% cum) of captured photos per year from 2003 through 2015; (B) percentage (%) of photos per month. Source: Own elaboration, based on Panoramio photos for the period from January 2003 through March 2015.

It should be noted that these concentration areas received a larger number of photos than the others, and it was decided to compare the evolutionary rhythms by year and month with respect to the total records of photos in the municipality.

Although there was a trend toward the concentration of photographs in some areas of the Boticas municipality, as was previously indicated, this centralization only began to occur in 2014 (Figure 7A). Even so, these photos were taken mostly in the summer months, with emphasis on the month of August, which should result from visitors to the country (Figure 7B).

Table 3 summarises the results of grouping items into clusters. It was observed that the characteristics of the photographs indicated that there were two types of patterns, that is, tourists and residents. Note that, during the analysis, it was verified that all the items presented a p-value of ≤0.05. The ANOVA test result also showed that the variables included in the model were sufficiently different for their grouping, and, thus, three groups were created. Cluster A (n = 250) essentially presents photographs of nature (100%), and the cluster is associated with photos that focus on scenarios (55.6%) and includes the visitors who most often take this type of photos. Cluster B represents only the class of visitors, highlighting the elements in the context (64.9%) and the built heritage category (89.8%). Cluster C represents the least expressive group and incorporates photographs that focus on elements located in the context (76.5%) and in the category of the built heritage (78.4%). Clusters B and C contain essentially photographs that do not include people.

Cluster A (n = 250)Cluster B (n = 325)Cluster C (n = 153)F-ratiop-value
Built heritage089.878.44698.34800.000*
Local culture02.512.4
Nature10000.7
Tourist services07.78.5
Element1029.217.6163.29400.000*
Element in context34.464.976.5
Scenario55.65.85.9
Without people9693.8853.00800.050**
With people46.215
Residents34010094.40100.000*
Visitors661000

Table 3.

Analysis of the clusters of the photos.

p < 0.01.


p ≤ 0.05.


Source: Own elaboration, based on Panoramio photos for the period from January 2003 through March 2015.

Advertisement

4. Discussion

As demonstrated during the study, Boticas is a tourist destination with seasonal demand, particularly during the summer period (Figure 8), a fact substantiated by the intersection of the number of visitors registered in Interactive Shop Porto and North Tourism and the number of photographs available in Panoramio. In any case, it is important to mention that some of the rural tourism houses in the municipality have a higher number of visitors during the winter period, as was evident from direct observation and discussions with these local agents.

Figure 8.

Photos recorded in the Panoramio (from 2003 through 2015) and visitors (from 2011 through 2015) in comparison with the minimum and maximum temperatures registered in the climatological normal for the period from 1971 through 2000 in Vila Real. Source: Own elaboration, based on Panoramio photos for the period from January 2003 through March 2015, in data from the Interactive Tourism Store and http://www.ipma.pt/pt/oclima/normais.clima/1981-2010/023.

The relationship between the photos that were taken and the promotion conveyed by various means of communication does not always present a direct relationship. In fact, although the Nadir Afonso Arts Center and the Boticas Nature and Biodiversity Park present a significant number of photographs and are key tourist resources for the promotion of the territory, there are other resources that the municipality presents that are underutilised due to the lack of the dissemination of information about their existence.

When the number of photographs is considered with respect to the tourist resources identified in the territory (Figure 9), it was verified that there are villages in which some of the traditional customs have been preserved, for example, Vilarinho Sêco and Coimbró. Although such considerations also are woven by residents and other stakeholders (i.e. [23, 30, 31]) when they identify the valued tourist attributes or those with high potential for appreciation, they are still not as effective in the tourism promotion strategy.

Figure 9.

Relationship between the number of photographs and tourist resources identified in Boticas. Source: Photographs of Panoramio, collected for the period from January of 2003 through March 2015 and in the tourist resources referenced in http://patrimonio.cm-boticas.pt and in loco.

The results also show that visitors and local people more often have photographed patrimonial and natural elements. However, it should be noted that this difference was more significant in the case of the local people. Nevertheless, it is important to mention that these evidences present a high degree of similarity with the results obtained by [3]. The perceived image of Boticas is very much related to the built heritage rather than to nature, although the differences are not so significant when compared with the categories of tourist services and local culture. This was a surprising discovery, and, if it is true that this municipality has a unique built-heritage (especially churches and museums), there also were some atrocities committed during the patrimonial recovery processes with profound changes to the structures of churches and chapels. However, the relevance of nature, especially on the part of the visitors, is consistent with the reading made by the various stakeholders, considering the magnificence of the natural ecosystem, that is, the mountains and valleys, of this territory.

Another element of analysis that allows us to infer the image of visitors is associated with the degree to which people are present in the photographs. While in some European destinations the captured heritage photographs do not have individuals present, in others they appear more frequently, especially in exotic or allocentric destinations. Photographs with the presence of visitors occur commonly in destinations where there is a degree of interaction between the receiving community and visitors [3].

A careful analysis of the photographs allowed us to infer that those taken in the Boticas territory were largely free of the presence of both local people and visitors. This situation is not uncommon, as was evident in the investigations conducted by Girona [3, 34, 35] and Vale de Boí [3]. One of the reasons that support the absence of people in the photos is the ideal of individual consumption of places, which is supported by the assertion that the presence of people in the photographs could represent a kind of alteration of reality [36].

Nevertheless, in most cases, tourists who visit a destination such as Boticas seek to eliminate any vestige of humanity to avoid detracting attention away from the element or the landscape, for example, empty churches or the splendour of the landscape. These photographs usually also have a smaller focus, where the elements in the context (56.9%) are the most photographed, which may be due to the search for a broader framework than they are visiting (global vision of the place), to facilitate their later recognition.

In fact, visitors’ behaviours may be framed in accordance with the photographs that are taken in the sense that the length of stay in the municipality is very small. Most of the photos with a visiting author occur between 10:00 A.M. and 4:00 P.M, which may denote (i) the absence of tourist facilities that are open for a longer time period, (ii) the absence of other interesting activities in the municipality, (iii) the absence of catering services that are open until later hours during the weekly period and (iv) the lack of desirable hotel accommodations that meet visitors’ expectations.

Considering these elements, it would seem reasonable to start some efforts to counteract this trend and to create a precise and accurate image of this territory. This could be done in the form of tourism products, based, for example, on nature, health and well-being. This approach could attract visitors who have an interest in these locations, and it may allow the maintenance of sustainable tourism practices.

Advertisement

5. Conclusion

The photos taken by locals and visitors show that there are certain observable distribution patterns and that these patterns have some similarities and some significant differences. In fact, visitors take photos less concentrated in certain housing areas than in locals, which shows a certain predisposition to value elements of the intangible heritage. It should be noted that 34.5% of the photos that were taken were associated with the natural component.

In some cases, there is a certain disarticulation between the promotion of tourism conducted by the municipality and the image of the destination based on photographs. In this way, there are some clues that can be put forward for future work, namely (i) assessing the seasonality of photographs taken by residents and visitors and, thus, which potential sites to promote and at which time of the year; (ii) verification of the distribution of the photographs at the supra-municipal scale, given that this sample is incipient and that it is possible, based on photographs standards on a broader scale, to develop common strategies with other adjacent territories; and (iii) objectives, goals and strategies that can be outlined in the short term and medium term for the development of tourism.

Such research has some limitations. While it is critical to take into consideration that residents or visitors only share the photos they deem to be most relevant, only some groups are frequent users of these platforms. Nonetheless, these approaches must be used in combination with other approaches, such as surveys, focus groups and interviews, to determine important information concerning the use of the territory’s resources from the perspective of enhancing tourism.

Advertisement

Acknowledgments

This work has the financial support of the Project Lab2PT—Landscapes, Heritage and Territory Laboratory—AUR/04509 and FCT through national funds and when applicable of the FEDER cofinancing, in the aim of the new partnership agreement PT2020 and COMPETE2020—POCI 01 0145 FEDER 007528.

Advertisement

Conflict of interest

The authors declare that there is no conflict of interest.

References

  1. 1. Camprubí R, Guia J, Comas J. The new role of tourists in destination image formation. Current Issues in Tourism. 2013;16:203-209
  2. 2. Choi S, Lehto XY, Morrison AM. Destination image representation on the web: Content analysis of Macau travel related websites. Tourism Management. 2007;28:118-129
  3. 3. Donaire JA, Camprubí R, Galí N. Tourist clusters from Flickr travel photography. Tourism Management Perspectives. 2014;11:26-33
  4. 4. García-Palomares JC, Gutiérrez J, Mínguez C. Identification of tourist hot spots based on social networks: A comparative analysis of European metropolises using photo-sharing services and GIS. Applied Geography. 2015;63:408-417
  5. 5. Santos J. The role of tour operators’ promotional material in the formation of destination image and consumer expectations: The case of the People’s republic of China. Journal of Vacation Marketing. 1998;4:282-297
  6. 6. Buhalis D, Law R. Progress in information technology and tourism management: 20 years on and 10 years after the internet—The state of eTourism research. Tourism Management. 2008;29:609-623
  7. 7. Myhill M, Shoebridge M, Snook L. Virtual research environments–a Web 2.0 cookbook? Library Hi Tech. 2009;27:228-238
  8. 8. Castells M, Espanha R. A era da informação: economia, sociedade e cultura. Paz e terra. 1999
  9. 9. Donaire JA, Galí N. La imagen turística de Barcelona en la comunidad de flickr. Cuadernos de Turismo. 2011:291-303
  10. 10. Kavitha S, Jobi V, Rajeswari S. Tourism recommendation using social media profiles. In: Artificial Intelligence and Evolutionary Computations in Engineering Systems. Springer; 2017. pp. 243-253
  11. 11. Kisilevich S, Krstajic M, Keim D, et al. Event-based analysis of people’s activities and behavior using Flickr and Panoramio geotagged photo collections. In: Information Visualisation (IV), 2010 14th International Conference. IEEE; 2010. pp. 289-296
  12. 12. Lo IS, McKercher B, Lo A, et al. Tourism and online photography. Tourism Management. 2011;32:725-731
  13. 13. Munar AM, Jacobsen JKS. Motivations for sharing tourism experiences through social media. Tourism Management. 2014;43:46-54
  14. 14. Yang L, Wu L, Liu Y, et al. Quantifying tourist behavior patterns by travel motifs and geo-tagged photos from Flickr. ISPRS International Journal of Geo-Information. 2017;6:345
  15. 15. Wood SA, Guerry AD, Silver JM, et al. Using social media to quantify nature-based tourism and recreation. Scientific Reports. 2013;3:2976
  16. 16. Fotis J, Buhalis D, Rossides N. Social Media Use and Impact during the Holiday Travel Planning Process. Springer-Verlag; 2012
  17. 17. Jenkins O. Photography and travel brochures: The circle of representation. Tourism Geographies. 2003;5:305-328
  18. 18. Munar AM. Social media strategies and destination management. Scandinavian Journal of Hospitality and Tourism. 2012;12:101-120
  19. 19. Leung D, Law R, Van Hoof H, et al. Social media in tourism and hospitality: A literature review. Journal of Travel & Tourism Marketing. 2013;30:3-22
  20. 20. Gomez B. La relación clima-turismo: Consideraciones básicas en los fundamentos teóricos y prácticos. Investig Geográficas. 1999:21-34
  21. 21. Xiang Z, Gretzel U. Role of social media in online travel information search. Tourism Management. 2010;31:179-188
  22. 22. Arriaza M, Cañas-Ortega JF, Cañas-Madueño JA, et al. Assessing the visual quality of rural landscapes. Landscape and Urban Planning. 2004;69:115-125
  23. 23. Lopes HT da S. O turismo como alavanca do desenvolvimento de áreas rurais: o caso de estudo do município de Boticas. University of Minho; 2016
  24. 24. Pérez JG. Ascertaining landscape perceptions and preferences with pair-wise photographs: Planning rural tourism in Extremadura, Spain. Landscape Research. 2002;27:297-308
  25. 25. Haven-Tang C, Sedgley D. Partnership working in enhancing the destination brand of rural areas: A case study of made in Monmouthshire, Wales, UK. J Destin Mark Manag. 2014;3:59-67
  26. 26. Hashim NH, Murphy J, Hashim NM. Islam and online imagery on Malaysian tourist destination websites. Journal of Computer and Communications. 2007;12:1082-1102
  27. 27. Juravle AIG, Sasu C, Terec-Vlad L. The destination image of Bucovina among Romanian tourists. Journal of Cross Cultural Management. 2016;10:139-149
  28. 28. Polo Peña AI, Frías Jamilena DM, Rodríguez Molina MÁ, et al. Online marketing strategy and market segmentation in the Spanish rural accommodation sector. Journal of Travel Research. 2016;55:362-379
  29. 29. Zhou L. Online rural destination images: Tourism and rurality. J Destin Mark Manag. 2014;3:227-240
  30. 30. Lopes H, Remoaldo P, Ribeiro V, et al. The creation of a new tourist destination in low density areas: The Boticas case. J Spat Organ Dyn. 2016;4:118-131
  31. 31. Remoaldo P, Freitas I, Matos O, et al. The planning of tourism on rural areas: The stakeholders’ perceptions of the Boticas municipality (Northeastern Portugal). Eur Countrys. 2017;9:504-525
  32. 32. INE. Tipologia de Áreas Urbanas. 2014. Available from: http://smi.ine.pt/Versao/Detalhes/3485%3E [Accessed: February 15, 2018]
  33. 33. Tammet T, Luberg A, Järv P. Sightsmap: Crowd-sourced popularity of the world places. In: Information and Communication Technologies in Tourism 2013. Springer; 2013. pp. 314-325
  34. 34. Galí N. La humanización de las imágenes emitidas por la publicidad de los destinos turísticos monumentales: el Caso de Girona. PASOS Rev Tur y Patrim Cult;3
  35. 35. Galí N, Donaire JA. The social construction of the image of Girona: A methodological approach. Tourism Management. 2005;26:777-785
  36. 36. Urry J. Tourist Gaze: Leisure and Travel in Contemporary Societies (Theory, Culture & Society). Sage Publications; 1990

Written By

Hélder Tiago da Silva Lopes, Paula Cristina Almeida Cadima Remoaldo and Vitor Ribeiro

Submitted: February 19th, 2018 Reviewed: May 10th, 2018 Published: November 5th, 2018