پایش تغییرات ساختاری در مقیاس زمانی- فضایی بیوم زاگرس ایران با استفاده از مبانی بوم شناسی سیمای سرزمین

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد، گروه برنامه‌‌ریزی و طراحی محیط، پژوهشکده علوم محیطی، دانشگاه شهید بهشتی، تهران، ایران

2 دانشیار، گروه برنامه‌‌ریزی و طراحی محیط، پژوهشکده علوم محیطی، دانشگاه شهید بهشتی، تهران، ایران

چکیده

اطلاع از روند تغییر الگوهای ترکیب محتوایی و چیدمان فضایی ساختار اکوسیستم در مقیاس فضایی سیمای‌‌سرزمین بیوم‌‌ها، جهت مدیریت بهینه آن‌‌ها در گذر زمان حایز اهمیت است. در پژوهش حاضر، مطابق با مدل مفهومی برگرفته از اصول بوم‌‌شناسی سیمای‌‌سرزمین، شامل: ساختار، عملکرد و تغییر در مقیاس مکانی، تغییرات چیدمان فضایی عناصر سیستم سیمای‌‌سرزمین بیوم زاگرس ایران با مطالعه 26 حوضه‌‌آبخیز منتهی به استان کهگیلویه ‌‌و ‌‌بویر‌‌احمد انجام شد. تصاویر سنجنده‌‌هایTM و OLI /TIRS ماهواره‌‌ای لندست 5 و 8 برای سال‌های 1987 و 2017 پیش‌‌پردازش شد و باندهای مناسب با استفاده از آزمون تجزیه مولفه‌های اصلی انتخاب شد و طبقه‌‌بندی کاربری ‌‌اراضی با استفاده از دو روش حداکثر احتمال (MLE) و شبکه عصبی مصنوعی پرسپترون (MLP) با 7 لایه ورودی، 6 لایه میانی و 5 لایه خروجی انجام گرفت. اعتبار‌‌سنجی و انتخاب کاربری مناسب با مقایسه ضرایب کاپای‌‌کلی، صحت‌‌کلی، خطای‌‌کاهنده و خطای‌‌فزاینده بررسی شد. کاربری اراضی طبقه‌بندی ‌شده روش MLP، با توجه به قدرت تفکیک عوارض و صحت بیشتر، انتخاب گردید و بارز‌‌سازی زمانی- مکانی تغییرات انجام شد. نتایج نشان می‌‌دهد بیشترین میزان کاهش اراضی بین سال‌‌های 2017- 1987 در کاربری اراضی جنگلی و بیشترین میزان افزایش در کاربری مرتع دیده می‌شود. مساحت کاربری‌‌های منابع آب و طبقه انسان‌‌ساخت، دو برابر شده است. گر‌‌چه توسعه‌‌های انسان‌‌ساخت نقش کمتری در این تغییرات دارند، لیکن آثار اقدامات انسانی، به‌خصوص تغییر اراضی جنگلی به کشاورزی و همچنین ساخت سدهای بزرگ، بسیار وسیع بوده‌‌ است. از این‌رو مدیریت مبتنی بر مبانی بوم‌‌شناسی سیمای‌‌سرزمین در ارتباط فی‌مابین ساختارشناسی، عملکردشناسی و تغییرپذیری می‌‌تواند در جهت پایداری دارایی‌‌های طبیعی و تنوع‌‌زیستی بیوم‌‌ زاگرس ایران مورد ‌‌استفاده قرار گیرد.
 

کلیدواژه‌ها


عنوان مقاله [English]

The Structural Detection of Spatial-Temporal Changes in Zagros Biome of Iran Using Landscape Ecology Principles

نویسندگان [English]

  • Mostafa Keshtkar 1
  • Shahindokht Barghjelveh 2
  • Naghmeh Mobarghei Dinan 2
1 MSc, Department of Planning and Designing the Environment, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, Iran
2 Assoc. Profe. Department of Planning and Designing the Environment, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, Iran
چکیده [English]

The Structural Detection of Spatial-Temporal Changes in Zagros Biome of Iran Using Landscape Ecology Principles
It is important to know the process of changing the patterns of content composition and spatial configuration of the landscape structure of biomes, in order to optimally manage them over time. In this study, in accordance with the conceptual model of the principles of landscape ecology, including: structure, function and change, changes in the spatial configuration of the elements of Zagros Biome of Iran was studied by studying 26 catchment basins leading to Kohgiluyeh and Boyerahmad Province. The TM and OLI /TIRS images of Landsat 5 and 8 satellites were pre-processed for 1987-2017, appropriate bands were selected using the principal component analysis test and land-use classification was performed using two methods of maximum probability (MLE) and Perceptron Artificial Neural Network (MLP) with 7 input, 6 intermediate and 5 output layers. Classified land-use of MLP method was selected according to the resolution of features and greater accuracy and temporal-spatial identification of changes was performed. The results show that between 2017 and 1987 the highest rate of land reduction is seen in forest land-use and the highest rate of land increase is seen in pasture land-use. Landscape sustainability management based on landscape ecology principles in relations between structure, function and change can be used.
 

کلیدواژه‌ها [English]

  • Zagros forests
  • Artificial Neural Network
  • Ecosystem structure
  • landscape ecology
  • Remote Sensing
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