مکان‌یابی سایت‌‌های طبیعت‌گردی با کاربرد هم‌زمان تحلیل شبکه و ترکیب خطی وزن‌دار

نوع مقاله : علمی- پژوهشی

نویسندگان

1 دانشجوی دکترای جنگل‌داری، دانشکده منابع طبیعی، دانشگاه گیلان، صومعه‌سرا، ایران

2 دانشیار، دانشکده منابع طبیعی، دانشگاه گیلان، صومعه‌سرا، ایران

3 استادیار، دانشکده منابع طبیعی، دانشگاه گیلان، صومعه‌سرا، ایران

4 استاد، دانشکده علوم ریاضی، دانشگاه گیلان، رشت، ایران

چکیده

DOR: 98.1000/1735-0883.1397.26.421.73.3.1605.1585
 
در راستای دستیابی به اهداف توسعه پایدار، توسعه برنامه‌ریزی شده گردشگری و به‌ویژه طبیعت‌گردی را می‌توان به‌عنوان یکی از مهم‌ترین گزینه‌های درآمدزا مطرح کرد. بنابراین، درنظر گرفتن وضعیت رفاه و آسایش جامعه ذینفع همراه با حفظ سلامت و تضمین عملکرد آینده اکوسیستم از ملزومات مدیریت پایدار گردشگری است. پژوهش پیش‌رو با هدف مکان‌یابی سایت‌‌های طبیعت‌گردی متمرکز در جنگل خیرود نوشهر انجام شد. گام‌های اجرایی این پژوهش عبارت بودند از: 1) انتخاب معیارها از طریق مرور منابع، 2) اولویت‌بندی معیارها با استفاده از فرآیند تحلیل شبکه (در قالب مقایسات زوجی کارشناسی)، 3) نقشه‌‌سازی معیارها با تعیین توابع عضویت فازی، 4) تلفیق نقشه‌‌ها با کاربرد ترکیب خطی وزن‌دار و 5) پهنه‌‌بندی عرصه‌‌های مستعد توسعه. بر این اساس، شناسایی و اولویت‌‌بندی معیارهای مؤثر بر توسعه طبیعت‌گردی از دو جنبه "تنوع معیارهای مورد استفاده" و "وزن یا اهمیت معیارها" بررسی شد. در بخش تنوع معیارهای مورد استفاده، ‌‌مؤلفه‌های آب‌وهوایی و در بخش وزن معیارها نیز ‌‌مؤلفه‌های مرتبط با معیارهای اقتصادی- اجتماعی بیشترین اهمیت را داشتند. در بخش شناسایی عرصه های مستعد، 11 هکتار از وسعت منطقه (0/13 درصد) در طبقه با مطلوبیت کم، 6619 هکتار (80/47 درصد) در طبقه با مطلوبیت متوسط و 1595 هکتار (19/39 درصد) در طبقه با مطلوبیت زیاد  قرار گرفت. لازم به توضیح است که سایت های گردشگری نیز در پهنه با مطلوبیت زیاد گزینش شدند. خروجی معیارهای مستخرج، وزن‌های تعدیل کارشناسی‌شده و همچنین نقشه‌‌های تهیه‌شده در این پژوهش می‌‌تواند به‌عنوان راهنمایی برای مدیران به‌کار برده شوند.

کلیدواژه‌ها


عنوان مقاله [English]

Identifying ecotourism sites using an integrated approach of analytical network process and weighted linear composition

نویسندگان [English]

  • Javad Mirarab Razi 1
  • Iraj Hassanzad Navroodi 2
  • Ismaeil Ghajar 3
  • Maziar Salahi 4
1 Ph.D. Student of Forestry, Faculty of Natural Resources, University of Guilan, Someh Sara, Iran
2 Associate Prof., Faculty of Natural Resources, University of Guilan, Someh Sara, Iran
3 Assistant Prof., Faculty of Natural Resources, University of Guilan, Someh Sara, Iran
4 Prof., Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran
چکیده [English]

Nowadays development of ecotourism is amongst the most profitable industries that requires prudent evaluation, planning, and management based on the sustainable development sterategies. Hence, adopting an approach that guarantees the social well-being and the health of natural ecosystems is a priority for tourism management. This research was conducted with the aim of locating intensive ecotourism sites. The executive steps of this research include 1) selecting the criteria by literature review, 2) prioritizing the criteria using the analytic network process (ANP) (in form of paired expert comparisons), 3) mapping the criteria by defining fuzzy membership functions, 4) integrating maps using the weighted linear composition and 5) delimiting the areas with proper capacity for the development. Accordingly, the identification and prioritization of the effective criteria on the development of ecotourism from the point views of "the variety of criteria used" and "weight or importance of criteria" were investigated. In the variety section of the criteria used in the previous works, the climatic (available in 67% of studies) and the socioeconomic (45% normal weight) components were the most important criteria. In terms of developable areas, 22 ecotourism sites with the total area of 266 hectares and an average suitabiliy of 78% were identified in the Kheyroud experimental forest in Mazandaran province. The outcome of the criteria and their weights as well as the maps produced from this research can be used as a guideline for the ecotourism managers.

کلیدواژه‌ها [English]

  • Fuzzy membership functions
  • Multi-criteria decision making
  • zoning
  • weight of criteria
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