Annotated Bibliography

Todd Montgomery GEOG 560 GI Science 1

This article focuses on how GIS tools can leverage the increasing amount of data in the tourism industry. The emphasis is on visualizing the distribution and travel patterns of tourism to aid sustainable tourism efforts and combat overtourism. It also discusses the potential of Web-GIS versus the polygon-based option. One particularly interesting point of the article relates to using visualization in mapping to illustrate how tourists travel to popular tourist attractions, which can result in traffic issues. This type of spatial analysis has significant potential for the planning and management of tourism, particularly in high-density areas. Though prior to reading this article, I had not considered visualizing the travel patterns of tourists, this approach has multiple applications within my research project.

The article discusses how GIS can contribute to addressing the contentiousness of overdevelopment within tourist destinations. Table 4 in this article provides an example of applying GIS to sustainable tourism issues. This touches on the core issue I hope to address in my research, as it provides an easy and transparent way to illustrate tourism impacts. One fascinating point is item two, “Lack of Ability,” which discusses the opportunity to consolidate multiple data sets to “monitor and control” tourism for the betterment of the destination. The article then concludes with opportunities for destinations to do proactive planning and use GIS data as a foundational resource.

This article offers a fantastic overview of real-world applications of evaluating community carrying capacity for tourist destinations. Trying to estimate carrying capacity is difficult at best. This article is very successful at applying the data and GIS maps in a simple but impactful way that I believe any community member could understand without advanced expertise. The authors discuss the potential to “predict” areas on the island that are suspected of over-tourism and ultimately could be damaged. From a decision support perspective, these processes and maps could build consensus around sustainable tourism planning.

The article provides an applied example of GIS in destination management for the Appalachian Mountains of Virginia. This destination is in an early stage of its lifecycle and engaged GIS tools in its planning stages to provide a foundation for future strategies. McGehee walks us through various planning stages, including community resource assessment, stakeholder interviews, visitor tracking, and multiple scenarios for tourism development. Incorporating the resident surveys into the research process showed how these interviews can provide rich data for the GIS tools and reports. The scenario planning piece, based on community and visitor needs, was also interesting and highlighted an effective way to communicate with stakeholders about tourism options in the long-term.

This article applies GIS to a specific scenario of how wind farm negative externalities could economically impact tourism in Scotland. Speaking from experience, this would be a difficult subject to discuss with community members, so I was interested to learn about their use of GIS maps with the inclusion of survey data. The article includes maps that show zones of the visual impact of wind turbines, presenting residents and tourists with potential scenarios using GIS modeling and asking for their feedback. The researchers even try to calculate a dollar amount on windmill views by asking visitors what they would be willing to pay for an unobstructed view of the landscape.

Gill and Singh focus on the socio-economic impact of tourism leveraging GIS maps. The Pithoragarh District is growing in terms of tourism and faces uncertainty about how to proceed with this industry in ways that enhance residents’ lives while also maximizing economic benefits. With massive tourism potential but little infrastructure, the authors, in coordination with the community leaders, developed growth models represented in GIS maps to anticipate infrastructure and tourists’ needs for amenities. This article supports earlier findings (McGehee et al., 2013) of powerful applications of GIS for destinations in the early stages of their destination lifecycles. This is particularly the case when policy leaders are looking to manage the costs of tourism proactively.

This article provides a timely and relevant application of carrying capacity using GIS and spatial analysis. The ski destination in Vlasic is analyzed and uses spatial analysis to compute the “comfortable capacity” of the ski destination, a figure that lets us measure when a ski resort may feel over capacity and guests’ experience is degraded. It uses a hectare/skier ratio, determining .05 as normal. It then calculates the hectare/skier ratio for Vlasic, which was estimated to be .46 hector per skier. This is a clear indication of overcrowding. Based on this finding, the authors conclude that stricter policies are needed to manage demand and additional infrastructure is needed to ease congestion. It’s rare for a destination to calculate and lay out its methodology for carrying capacity. Although the actual results are irrelevant to my research, the methodology for calculating carrying capacity is potentially useful.

Harun et al. discuss building criteria, based on GIS, for the preservation or holding back for future tourism initiatives. The criteria are based on the coastline, topography, natural resources, and tourism-related facilities. Having visited Langkawi many times, I take issue with the idea that sensitive areas should be leveraged for tourism, but I do appreciate a quantifiable method using GIS and data for planning purposes. The paper proposes a map to identify potential tourist attractions, including both man-made and natural. It goes on to create maps of the island that would be suitable or protected from the “built environment” function of tourism. The authors then use spatial analysis to illustrate potential tourism sites and their locations near existing infrastructure like roads and developed sites. Although this paper is primarily focused on economic development, it does provide a small step towards developing common criteria for tourism development.

Brown and Web introduce a new application of GIS that I had not previously heard of. Calling it Public Participation Geographic Information System PPGIS, the authors provide an example in Southern Australia, Kangaroo Island, where residents can use an online GIS map with an access code to drag and drop markers on the map to highlight their preferences for tourism in the area. This particular case study uses longitudinal data over six years to identify changes in residents’ preferences for tourism on the island. I had not considered this application to gather residents’ sentiments and believe it may prove to be a useful tool in my research. I also appreciate that it tries to gauge the “value” residents place on certain areas, which is useful when trade-offs must be made for finite resources.

Inspired by the previous article, I wanted to see how PPGIS was being used in tourism more generally. This article focuses on managing the conflicts that can happen between tourists and residents, especially in Australia, where bikers and horse riders must share popular trails. Finding that many horse and bike riders have had conflicts on trails, the authors use spatial guidance where participants used markers to indicate where conflicts happen. They then use spatial guidance to understand how physical features such as curves and slopes play a role in these conflicts. In Figure 3, the authors highlight the range of conflicts and their locations on the trail maps. Although a fairly simple process, this promotes informed decision-making and provides policy and management officials clear next steps to improve the trail experience and mitigate conflicts. With my own research, this type of tool could complement existing data collection efforts with the additional benefit of identifying areas within the community that could be addressed to improve relations.

Norwood et al. discuss the unrealized potential of GIS mapping in land use and growth management community discussions. They use a case study from Southern Appalachian county to engage stakeholders in landscape proposals, seeing GIS as a bridge between complex academic research and stakeholders concerns via the visualization of data. Like the other articles I have discussed, they recommend the integration of GIS within a broader data collection effort that includes tools such as surveys and focus groups. The article ends with a discussion about how maps are providing accessibility to residents who normally would not have the time or ability to process detailed and complex information on land use.

As a graduate student in applied economics, I find the use of GIS in econometrics an interesting area. In this article, Kudamatsu attempts to explain practical applications of GIS in this field. He also focuses on how GIS can provide insight into exogenous factors such as weather and geography to explain causal effects more reliably. Large data sets, including geographic and weather data, can be especially difficult to manage and model in non-GIS models. The application of GIS and the understanding of spatial relationships provide additional insight and help refine econometric models. In my research, weather and geography play central roles in why, how and where tourists visit. This paper provides solutions for how these two factors can be utilized to understand the impact of tourism.

Wicaksono et al. provide an interesting case study of determining the carrying capacity on a beach in Indonesia using GIS. Their focus is especially on environment carrying capacity as it attempts to measure the negative impacts based on tourism. Using a Tourism Suitability Index in their analysis to aggregate its community results, they specifically look into soil texture, drainage, groundwater depth, and erosion criteria. Using GIS, they then create several GIS maps illustrating the criteria at the beach. Finally, they improve the results and create a map of land capability to communicate the findings so that residents can understand their suitability. This is a great example and provides insights into how GIS could be leveraged to address larger carrying capacity studies.

This article is not specifically about GIS, but the Sustainable Tourism Index already discussed relies upon GIS fundamentals in its use. With its focus on environmental impacts, such as pollution, floods, overcrowding, and greenhouse gas emissions, to calculate its index score, it finds that developing countries are outperforming developed countries in these key areas. On page 29, Gold breaks down its scoring and weighting. Across each of these categories, GIS has a potential role to play to measure and communicate results better; this is particularly the case on Environmental and Socio-cultural scoring. Scoring and benchmarking are important to my research, and this article provides a great example of an approach that could be enhanced with GIS.

Wei introduces a Tourism Management System utilizing GIS. In previous articles, authors have referred to GIS as a tool. However, Wei goes one step further by recommending the utilization of GIS as the foundation for a tourism management system. Wei also concludes that these systems allow for more detailed maps and more timely updates. Wei also finds that this improved passenger flow by 15%. Although the article concept is quite compelling, I found that the article and experiments don’t live up to the expectations in the title. One compelling takeaway is in section 4.2, which discusses Influential dimensions of social conditions; this could be an interesting input to better understand modeling carrying capacity in rural developments.

  • Beedasy, Jaishree, and Duncan Whyatt. “Diverting the tourists: a spatial decision-support system for tourism planning on a developing island.” International Journal of Applied Earth Observation and Geoinformation 1.3-4 (1999): 163-174. (Must request through OSU Library)

Unlike Wei (2021), Beedasy and Whyatt propose a much more comprehensive decision support for tourism planning using GIS. The authors seek to better model the many factors that can impact tourist planning using GIS as its foundation, concluding that decision makers must have the flexibility to modify key criterion within the GIS to answer specific questions. The paper includes maps that illustrate existing tourist zones. However, it goes much deeper since Mauritius Island offers many tourist activities such as diving, beach activities, sightseeing, etc. Each activity has a different set of environmental factors that would need to be mapped and included in the GIS tool. The article concludes with spatial analysis regarding remoteness, access to infrastructure, slope, and elevation, which could be quite useful in a decision support system.

Krajíčková et al. analyze factors to identify and quantify overtourism using GIS. To do so, they use spatial differentiation to identify “indicators of tourism pressure” and then use these indicators to identify metrics for overtourism, including number of visitors per area and Tourist Density Rate. The challenge the authors face is often these metrics are only available across the entire municipality, whereas overtourism tends to focus on specific areas. Using GIS, they are able to target specific areas and then calculate those metrics for those areas, resulting in greater accuracy and more impactful findings. This article is interesting because it addresses the unevenness of tourism and how using aggregate metrics can lead to misleading results through oversimplification.

This last article focuses on the flow of tourists through a destination taking advantage of various monitoring technologies. These include Internet of Things, big data and GIS. One of the authors’ objectives is to test quantifying tourist flows. With much of this data nonexistent, the authors focus on sensor tools to quantify customer movements. That technology could be used in real-time to alleviate pressure. These data then allow for several 3D application maps with GIS. I find this interesting because I’ve talked to the US Forest Service about monitoring tools in the past to improve congestion and parking within National Parks.