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Geographic Information System (GIS)

Making Sense of Geospatial Data

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Applied Data Science in Tourism

Part of the book series: Tourism on the Verge ((TV))

Abstract

A Geographic Information System (GIS) is a theoretical framework and software for gathering, storing, managing, analyzing, and visualizing spatially distributed data. The GIS approach is especially beneficial when the analysis uses spatial data collected from different sources, requires understanding of a spatial relationship between the data points (distance, time to travel, etc.), deals with spatial patterns (e.g., hot spot analysis), extensively involves mapping, and other similar applications. This chapter thus provides a short introduction to geospatial data, typical GIS problems, and software applications.

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References

  • Anselin, L. (1995). The local indicators of spatial association LISA. Geographical Analysis, 27, 93–115.

    Article  Google Scholar 

  • Bailey, T. C., & Gatrell, A. C. (1995). Interactive spatial data analysis (Vol. 413). Longman Scientific & Technical.

    Google Scholar 

  • Bowman, A. W., & Azzalini, A. (1997). Applied smoothing techniques for data analysis: The kernel approach with S-Plus illustrations (Vol. 18). OUP Oxford.

    Google Scholar 

  • Brewer, C. A. (2015). Designing better maps: A guide for GIS users. ESRI Press.

    Google Scholar 

  • Brunsdon, C., Fotheringham, S., & Charlton, M. (1998). Geographically weighted regression. Journal of the Royal Statistical Society: Series D (The Statistician), 47(3), 431–443.

    Article  Google Scholar 

  • Cliff, A., & Ord, J. K. (1973). Spatial aurocorrection. London: Pion.

    Google Scholar 

  • Gelman, A. (2009). Red state, blue state, rich state, poor state: Why Americans vote the way they do. Princeton University Press.

    Book  Google Scholar 

  • Goodchild, M. F. (2018). Reimagining the history of GIS. Annals of GIS, 24(1), 1–8.

    Article  Google Scholar 

  • Koch, T. (2004). The map as intent: Variations on the theme of John Snow. Cartographica: The International Journal for Geographic Information and Geovisualization, 39(4), 1–14.

    Article  Google Scholar 

  • Kuntz, M., & Helbich, M. (2014). Geostatistical mapping of real estate prices: An empirical comparison of kriging and cokriging. International Journal of Geographical Information Science, 28(9), 1904–1921.

    Article  Google Scholar 

  • MacEachren, A., Bishop, I., Dykes, J., Dorling, D., & Gatrell, A. (1994). Introduction to advances in visualizing spatial data. In H. M. Hearnshaw & D. J. Unwin (Eds.), Visualization in geographical information systems (pp. 51–59). Wiley.

    Google Scholar 

  • Maguire, D. J. (1991). An overview and definition of GIS. Geographical information systems: Principles and applications, 1, 9–20.

    Google Scholar 

  • Monmonier, M. (2018). How to lie with maps. University of Chicago Press.

    Book  Google Scholar 

  • Peterson, G. N. (2020). GIS cartography: A guide to effective map design. CRC Press.

    Book  Google Scholar 

  • Rosenshein L., Scott, L., Pratt, M. (n.d.). Finding a meaningful model. ESRI. https://www.esri.com/news/arcuser/0111/files/findmodel.pdf

  • Sarrión-Gavilán, M. D., Benítez-Márquez, M. D., & Mora-Rangel, E. O. (2015). Spatial distribution of tourism supply in Andalusia. Tourism Management Perspectives, 15, 29–45.

    Article  Google Scholar 

  • Snyder, J. P. (1997). Flattening the earth: Two thousand years of map projections. University of Chicago Press.

    Google Scholar 

  • Stem, J. E. (1989). State plane coordinate system of 1983 (Vol. 5). US Department of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service, Charting and Geodetic Services. https://www.ngs.noaa.gov/PUBS_LIB/ManualNOSNGS5.pdf

  • Su, L., Kirilenko, A. P., & Stepchenkova, S. (2020). The effect of geographical and personal proximity on online discussions of service failure incidents. Current Issues in Tourism, 23(18), 2230–2234.

    Article  Google Scholar 

  • Tobler, W. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46, 234–240.

    Article  Google Scholar 

  • Van der Zee, E., Bertocchi, D., & Vanneste, D. (2020). Distribution of tourists within urban heritage destinations: A hot spot/cold spot analysis of TripAdvisor data as support for destination management. Current Issues in Tourism, 23(2), 175–196.

    Article  Google Scholar 

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Correspondence to Andrei P. Kirilenko .

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Further Readings and Other Sources

Further Readings and Other Sources

1.1 Books

  • Bearman, N. (2020). GIS: Research methods. Bloomsbury Publishing A simple non-technical introduction to GIS for social scientists.

  • Bowman, A. W., & Azzalini, A. (1997). Applied smoothing techniques for data analysis: The kernel approach with S-plus illustrations (Vol. 18). Oxford University Press.

  • Cliff, A. D., & Ord, J. K. (1973). Spatial autocorrelation. Pion.

  • Lovelace, R., Nowosad, J., & Muenchow, J. (2019). Geocomputation with R. CRC Press. https://geocompr.robinlovelace.net – free e-book suitable for those who already know R and want to expand their expertise with GIS methods.

  • Margai, F., & Oyana, T. J. (2015). Spatial analysis: Statistics, visualization, and computation methods: An overview of spatial analysis methods. CRC Press.

  • Peterson, G. N. (2020). GIS cartography: A guide to effective map design. CRC Press.

1.2 Websites

1.3 Tourism Applications

  • Jovanović, V., & NjeguÅ¡, A. (2008). The application of GIS and its components in tourism. Yugoslav Journal of Operations Research, 18(2), 261–272 An introduction to GIS application in tourism.

  • Wei, W. (2012). Research on the application of geographic information system in tourism management. Procedia Environmental Sciences, 12, 1104–1109 An essay on GIS applications in tourism.

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Kirilenko, A.P. (2022). Geographic Information System (GIS). In: Egger, R. (eds) Applied Data Science in Tourism. Tourism on the Verge. Springer, Cham. https://doi.org/10.1007/978-3-030-88389-8_24

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