مدل‏سازی ارزیابی کیفیت زیباشناختی بصری منظر به منظور توسعه گردشگری در مناطق تحت حفاظت

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه محیط زیست، دانشکده منابع طبیعی، دانشگاه تهران، کرج، ایران

2 پژوهشکده محیط زیست و توسعه پایدار، سازمان حفاظت محیط زیست، تهران، ایران

10.48308/envs.2024.1335

چکیده

سابقه و هدف: زمین سیما در مناطق تحت حفاظت، یک مزیت گردشگری در طبیعت است و به همین علت سنجش زیباشناختی و ارزیابی کیفیت منظر در این مناطق ضرورت دارد. با وجود اینکه در سایر گردشگاه‌ها نیز این موضوع از اهمیت برخوردار است اما در مناطق تحت حفاظت که شکل گردشگری به صورت اکوتوریسم و بر پایه بازدید است، این امر بیشتر اهمیت دارد. از این رو این پژوهش با هدف مدل‌سازی ارزیابی کیفیت زیباشناختی بصری منظر با هدف گردشگری در مناطق تحت حفاظت با استفاده از شبکه عصبی مصنوعی جهت پیش‌بینی ارزش زیباشناختی مناظر و اولویت‌بندی متغیرهای تاثیرگذار بر مدل صورت پذیرفت.
مواد و روش‌ها: پژوهش حاضر در منطقه حفاظت شده البرز مرکزی تحت مدیریت استان البرز انجام شده است. در این مطالعه جهت ارزیابی کیفیت زیباشناختی بصری مناظر مناطق تحت حفاظت با هدف گردشگری، ترکیب رویکرد ارزیابی جامع و روش مدل‌سازی شبکه عصبی مصنوعی به‌کار گرفته شد، رویکرد ارزیابی جامع شامل دیدگاه کاربر محور با تکمیل پرسشنامه و استفاده از 19 عنصر عینی شامل 15 معیار عینی منظر (تنوع پوشش‌های طبیعی و انسانی، تنوع فرم رویشی، فرم ترکیب درختان، فرم بدنه آبی، تنوع رنگی، منظره آب، منظره سنگ و صخره، منظره جاده و مسیرهای عبوری، منظره پوشش گیاهی درختی و درختچه‌ای، منظره پوشش گیاهی علفی و بوته‌ای، منظره سطوح لخت و بدون پوشش، منظره ساختمان‌ها و سازه‌ها، منظره آسمان، نسبت سطوح سخت و نسبت سطوح نرم) و 4 معیار مربوط به ویژگی نقاط چشم‌انداز (ارتفاع، شیب، تیپ پوشش گیاهی و انبوهی پوشش گیاهی) بود. بدین منظور، ابتدا واحدهای همگن ارزیابی منظر با استفاده از 6 شاخص مکانی (شامل ارتفاع از سطح دریا، درصد شیب، منظر گیاهی، قابلیت دید روستا، قابلیت دید رودها دائمی و فصلی)، شناسایی شد. سپس 100 عکس از مناظر منطقه تهیه و مدل‌سازی به روش شبکه پرسپترون چندلایه انجام شد. در گام بعدی به آنالیز حساسیت مدل ارزیابی کیفیت زیباشناختی منظر جهت اولویت‌بندی و نیز تعیین موثرترین معیارهای زیباشناختی بصری در ارزیابی کیفیت زیباشناختی بصری مناظر در منطقه پرداخته و در نهایت سامانه پشتیبان تصمیم‌گیری ارزیابی کیفیت زیباشناختی بصری مناظر مناطق تحت حفاظت با هدف گرشگری طراحی شد.
نتایج و بحث: مدل دارای ساختار 1-6-19 (19 متغیر ورودی، 6 نورون در لایه مخفی و یک متغیر خروجی) با توابع انتقال لگاریتم سیگموئید در لایه پنهان و خطی در لایه خروجی و الگوریتم بهینه‌سازی لونبرگ-مارکوارت، با ضرایب تبیین در سه دسته داده آموزش، اعتبارسنجی و آزمون معادل 72/0، 75/0 و 70/0 به عنوان ساختار بهینه مدل ارزیابی کیفیت زیباشناختی بصری مناظر مناطق تحت حفاظت با هدف گردشگری معرفی شد. بر اساس نتایج آنالیز حساسیت، منظره آب، فرم ترکیب درختان، انبوهی پوشش گیاهی، با ضرایب اثرگذاری 233/0، 147/0و 104/0 به ترتیب بیشترین تاثیر را در کیفیت زیباشناختی بصری مناظر مناطق تحت حفاظت از خود نشان دادند. روند تغییرات کیفیت زیباشناختی منظر بر حسب تغییرات منظره آب و فرم ترکیب درختان بیان‌کننده این امر بود که با افزایش معیارهای مذکور در مناظر منطقه، کیفیت زیباشناختی بصری به صورت غیرخطی افزایش می‌یابد؛ به صورتی که با 23/8 درصد افزایش سطوح آب در منظر و تغییر فرم ترکیب درختان از تکی به گروهی، به ترتیب افزایش 46/0 و 48/0 واحدی کیفیت زیباشناختی بصری منظر مشاهده شد. همچنین روند تغییر معیار انبوهی پوشش گیاهی کاهش کیفیت زیباشناختی بصری مناظر منطقه را با افزایش معیار مذکور نشان داد.
نتیجه‌گیری: آنالیز حساسیت و شناسایی تأثیرگذارترین عناصر و معیارها بر کیفیت زیباشناختی بصری مناظر مناطق تحت حفاظت با هدف گردشگری نشان داد جهت دستیابی به ارزش زیباشناختی بصری منظر بالا و تعیین زون‌های گردشگری متمرکز و گسترده در مناطق تحت حفاظت، منظر آب می‌بایست در اولویت اول برنامه‌ریزی قرار ‌گیرد. مدل ارائه شده در این پژوهش به عنوان یک سیستم پشتیبان تصمیم‌گیری در ارزیابی کیفیت زیباشناختی بصری مناظر در مناطق تحت حفاظت با هدف گردشگری است و امکان پیش‌بینی کیفیت زیباشناختی بصری مناظر در مناطق تحت حفاظت با شرایط اکولوژیک مشابه و نیز بوم‌سازگان‌های مشابه را فراهم می‌کند. همچنین از مدل ارائه شده در این مطالعه، می‌توان در تهیه طرح مدیریت و زون‌بندی مناطق تحت حفاظت بویژه در زون‌های گردشگری استفاده نمود.

کلیدواژه‌ها

عنوان مقاله [English]

Modeling landscape visual aesthetic quality assessment towards tourism development in protected areas

نویسندگان [English]

  • Farnoush Attar Sahragard 1
  • Afshin Danehkar 1
  • Ali Jahani 2
1 Department of Environmental Science, Faculty of Natural Resources, University of Tehran, Karaj, Iran
2 Research Center of Environment and Sustainable Development, Department of Environment, Tehran, Iran
چکیده [English]

Introduction: Landscape in protected areas is an advantage of tourism in nature, and as a result, aesthetic assessment and landscape quality assessment are necessary in these areas. Although this issue is important in other outdoor recreation sites, but in protected areas where the form of tourism is eco-tourism and based on visits, it is more important. Therefore, this study was done with the aim of modeling landscape visual aesthetic quality assessment with the purpose of tourism in protected areas using artificial neural network to predict the aesthetic value of the landscape and prioritize the influential variables of the model.
Material and methods: The current research was carried out in the Central Alborz protected area under the management of Alborz province. In this study, in order to assess the landscape visual aesthetic quality of protected areas with the aim of tourism, a combination of comprehensive assessment perspective and the artificial neural network modeling method was used; a comprehensive assessment perspective includes the user perspective by completing the questionnaire and using 19objective variables including 15landscape objective criteria (diversity of natural and human covers,vegetation form diversity,trees composition form,water body form,color diversity,water landscape,rock landscape,roads and trails landscape,tree and shrub vegetation landscape,grassy and bushy vegetation landscape,bare and uncovered surfaces landscape,buildings and structures landscape,sky landscape,hard surface ratio,soft surface ratio) and 4criteria related to viewpoints characteristics (altitude,slope,vegetation type,vegetation coverage). For this purpose, first, homogeneous landscape assessment units were characterized using six spatial indicators (elevation,slope(%),vegetation landscape,village visibility, permanent and seasonal river visibilities). Then 100photos of the scenery of the area were taken and modeling was done using the multilayer perceptron network method. In the next step, the sensitivity analysis of the model for assessing the aesthetic quality of the landscape was done in order to prioritize and determine the most effective visual aesthetic criteria in the assessment of the visual aesthetic quality of the landscapes in the region. Finally, the decision support system for assessing the landscape visual aesthetic quality in protected areas for the purpose of tourism was designed.
Results and discussion: The model with the structure of 19-6-1 (19input variables, 6neurons in the hidden layer, and one output variable) with Log-Sigmoid transfer functions in the hidden layer and linear in the output layer and Levenberg–Marquardt optimization algorithm, with explanatory coefficients in the three data sets, namely training, validation and test equal to 0.7, 0.75 and 0.70 were introduced as the optimal structure of the model for assessing the landscapes visual aesthetic quality of protected areas with the purpose of tourism.
According to the sensitivity analysis results, the parameters of the water landscape, the composition of trees, and the vegetation coverage with the sensitivity coefficients of 0.223, 0.147, and 0.104, respectively, showed the most significant impact on the landscapes visual aesthetic quality in protected areas. The trend of the changes in the landscape aesthetic quality according to the changes in the water landscape and the trees’ composition form was that, with the increase of the mentioned variables in the landscapes of the region, the visual aesthetic quality increases in a non-linear way; thus, with 8.23% increase in the water landscape and in changing the trees’ composition form from single to group, an increase of 0.46 and 0.48 units, respectively, was observed in the landscape visual aesthetic quality. Also, the process of changing the variable of vegetation coverage showed a decrease in the landscape visual aesthetic quality of the region with the increase of the said variable.
Conclusion: The sensitivity analysis and identification of the most significant variables and criteria on the visual aesthetic quality of the landscapes of protected areas with the purpose of tourism showed that in order to achieve a high landscape visual aesthetic value and determine the intensive and extensive recreational zones in the protected areas, the water landscape should take the first priority of planning. The model presented in this research is a decision support system for assessing the landscapes visual aesthetic quality in protected areas for tourism and provides the possibility of predicting the visual aesthetic quality of landscapes in protected areas with similar ecological conditions and ecosystems. Also, the model presented in this study can be used in preparing the management plan and zoning of protected areas, especially in recreational zones.

کلیدواژه‌ها [English]

  • Artificial neural network
  • Landscape
  • Landscape Assessment
  • Homogeneous landscape unit
  • Southern Alborz protected area

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فصلنامه علوم محیطی
دوره 22، شماره 1
فروردین 1403
صفحه 123-144

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