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Ecotourism spatial-time planning model using ecosystem approaches and landscape ecology

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Abstract

Tourism industry is one of the new fields and new fields studied by various sciences and today it has been considered by countries in various ways. Because the use of tourism potential and capabilities in each region can provide a dynamic and active ground for the development of that region, the study of the potential of these capabilities in terms of geography will be a special necessity. Therefore, the aim of the study was to evaluate and validate a variety of criteria and methods of land capability assessment for tourism and ecotourism. In this study, the aesthetic value of the landscape, the value of the landscape, and the quality of the habitat and the rarity of the habitat effect were studied from 2000 to 2020 and were predicted for 2040. The result of this study showed that the four criteria used in the decision system with fuzzy gamma method will improve the model from 0.42 to 0.776. The 8 most common criteria for reviewing resources by overlap** methods in ecotourism decision-making systems were not accurate enough or could not be referenced for other areas.

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All data were obtained during the research by the authors of the article.

Notes

  1. Interspersion and juxtaposition index

  2. Perimeter-area fractal dimension

  3. Shannon’s diversity index

  4. Mean area per disjunction core

  5. Contrast-weighted edge density

  6. Proximity index

  7. Disjunct core area density

  8. Connectance index

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Authors and Affiliations

  1. Department of Environmental Science, Faculty of Natural Science and Environment, Science and Research Branch, IAU, Tehran, Iran

    Mahtab Tavakoli, Masoud Monavari, Forough Farsad & Maryam Robati

Authors
  1. Mahtab Tavakoli
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  2. Masoud Monavari
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  3. Forough Farsad
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  4. Maryam Robati
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All authors contributed equally.

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Correspondence to Masoud Monavari.

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Tavakoli, M., Monavari, M., Farsad, F. et al. Ecotourism spatial-time planning model using ecosystem approaches and landscape ecology. Environ Monit Assess 194, 116 (2022). https://doi.org/10.1007/s10661-021-09558-1

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