پایش و مدل سازی تغییرهای زمانی - مکانی پوشش گیاهی با استفاده از NDVI و مدل Markov-CA ( مطالعه موردی: شهرستان کرمانشاه)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه سنجش از دور و سیستم اطلاعات جغرافیایی، دانشکده علوم محیطی، موسسه آموزش عالی آبان هراز آمل، مازندران، ایران

2 گروه مهندسی ابخیزداری، دانشکده منابع طبیعی، دانشگاه علوم کشاورزی و منایع طبیعی ساری، مازندران، ایران

چکیده

سابقه و هدف: امروزه با رشد جمعیت اکثر فضاهای طبیعی دستخوش تغییرات کاربری اراضی شده‌اند. در این میان اراضی پوشش‌ گیاهی به دلیل تأثیر دیگر اراضی بر روند تخریب آن و پیامدهای نامطلوب آن بر زندگی انسان و جانوران از اهمیت ویژه‌ای برخوردار می‌باشد. توسعه مناطق شهری به‌منظور برآوردن نیازهای ساخت‌وساز جمعیت رشد یافته و همچنین رشد اراضی کشاورزی برای تأمین امنیت غذایی انسان و پاسخگویی به نیاز‌های مصرف‌کنندگان از مهم‌ترین دلایل تخریب اراضی پوشش‌گیاهی در یک منطقه است. امروزه رشد سریع فناوری سنجش‌ازدور، GIS و همچنین علوم کامپیوتری موجب ظهور مدل‌های زیادی جهت ارائه الگوهای گذشته، حال و آینده تغییرات کاربری اراضی‌ به‌خصوص اراضی پوشش‌گیاهی شده است. شهرستان کرمانشاه به‌عنوان یکی از مناطق روبه رشد در سالیان اخیر دچار رشد جمعیت زیادی شده است و با توجه به نقش جمعیت در تغییرات کاربری اراضی و پوشش‌گیاهی لذا این مسئله ضرورت آگاهی از وضعیت پوشش‌گیاهی این ناحیه را جهت مدیریت صحیح منابع طبیعی می‌طلبد. پیرو این مسئله هدف مطالعه حاضر پایش و پیش‌بینی تغییرات پوشش‌گیاهی شهرستان کرمانشاه با استفاده از شاخص NDVI و مدل CA-Markov است.
مواد و روش ها: در این مطالعه تراکم پوشش‌گیاهی شهرستان کرمانشاه با استفاده از شاخص NDVI در چهار کلاس بدون پوشش‌گیاهی، ضعیف، متوسط و متراکم از تصاویر Landsat در سال‌های 1987، 2002 و 2017 استخراج گردید و سپس نتایج با استفاده از نقاط کنترل زمینی اعتبارسنجی گردیدند. همچنین به‌منظور پیش‌ بینی تراکم پوشش‌ گیاهی برای سال 2032 ابتدا نقشه پوشش‌ گیاهی سال 2017  با اعمال مدل CA-Markov شبیه‌سازی گردید و سپس نتایج با استفاده از نقشه واقعی پوشش‌ گیاهی همان سال با کمک ماژول validate  در نرم‌افزار IDRISI Terrset اعتبارسنجی گردید و در ادامه پیرو نتایج اعتبارسنجی و با اعمال مدل مذکور نقشه تراکم پوشش‌ گیاهی در سال 2032 پیش‌ بینی گردید
 نتایج و بحث: نتایج بررسی نقشه‌های پوشش‌گیاهی با دقت بیش از 87 درصد نشان می‌دهد که مساحت طبقات بدون پوشش‌گیاهی،0 ضعیف و متراکم در دوره‌ی 1987 تا 2017 روند کاهشی و پوشش‌گیاهی متوسط دارای روند افزایشی بوده است. تغییرات مکانی پوشش‌گیاهی طی دور‌ه‌ی 30 سال نشان می‌دهد که‌ نواحی بدون پوشش‌گیاهی، پوشش‌گیاهی ضعیف و متوسط در طبقات ارتفاعی 1042 تا 1587، 1587 تا 2133 و 2133 تا 2678متری روند افزایشی و پوشش‌گیاهی متراکم نیز در طبقات 1042 تا 1587 روند افزایشی اما در طبقات 1587 تا 2133 و 2678 تا 3224 متری روند کاهشی داشته است. همچنین تراکم پوشش‌گیاهی در طبقات شیب نشان می‌دهد که شیب 0 تا 25 درصد بیشترین و شیب‌های 50 تا 75 درصد و بیشتر از 75 درصد کمترین تراکم پوشش‌گیاهی را داشته است و تغییرات پوشش‌گیاهی در شیب 0 تا 25 درصد بیشترین و در شیب‌های 50 تا 75 و بیشتر از 75 درصد کمترین مقدار بوده است. همچنین نتایج مدل CA-Markov با دقت بیش از 80 درصد در سال 2032 نشان می‌دهد که پوشش‌گیاهی ضعیف بیشترین مساحت پوشش‌گیاهی را در شهرستان کرمانشاه خواهند داشت. روند افزایشی و کاهشی طبقات پوشش‌گیاهی نسبت به سال 2017 نشان می‌دهد که پوشش‌گیاهی ضعیف کاهش و طبقات بدون پوشش‌گیاهی، پوشش‌گیاهی متوسط و متراکم روند افزایشی خواهند یافت. همچنین بررسی طبقات پوشش‌گیاهی در طبقات ارتفاعی و شیب نشان می‎ دهد که در ارتفاعات 1042 تا 1587، 1587 تا 2133 و 2133 تا 2678 متری و طبقات شیب 0 تا 25 درصد پوشش‌گیاهی متوسط و متراکم پوشش غالب است اما در ارتفاعات 2678 تا 3224 متری و شیب 50 تا 75 و بیشتر از 75 درصد مساحت پوشش‌گیاهی ضعیف و نواحی بدون پوشش بیشتر از طبقات دیگر خواهد بود
نتیجه‌گیری: به‌طورکلی یافته‌های این مطالعه نشان داد طبقه‌بندی شاخص NDVI با استفاده مقادیر میانگین، انحراف معیار شاخص مذکور و داده‌های جانبی مانند داده‌های کنترل زمین برای تهیه نقشه پوشش‌گیاهی و همچنین مدل CA-Markov برای پیش‌بینی این تغییرات روش‌های دقیق به شمار می‌روند. 

کلیدواژه‌ها

عنوان مقاله [English]

Monitoring and prediction spatiotemporal vegetation changes using NDVI index and CA-Markov model (case study: Kermanshah city)

نویسندگان [English]

  • Shadman Darvishi 1
  • Karim Solaimani 2
1 Department of Remote Sensing and Geographic Information Systems, Faculty of Environmental Sciences, Aban Haraz Institute of Higher Education, Amol, Mazandaran, Iran
2 Department of Watershed Management, Faculty of Natural Resources, Sari Agricultural Sciences and Natural Resources University, Mazandaran, Iran
چکیده [English]

Introduction: Monitoring and evaluation of land surface condition is one of the basic needs in investigating the changes occurring at different levels, including global, regional and local, which include environmental changes. Today, the rapid growth of remote sensing technology, GIS and computer science has led to the emergence of many models to present current and future patterns of land use change. In order to high population growth in large cities and the population's need for land resources, this provides for the destruction of land use, especially vegetation. Kermanshah city as one of the growing areas in recent years has experienced a large population growth and due to the role of population in land use changes and vegetation cover, this issue requires awareness of the vegetation status of this area for proper management of natural resources. The purpose of this study is to monitor and predict vegetation changes in Kermanshah city using NDVI index and CA-Markov model.
Material and methods: In this study, vegetation density of Kermanshah city using NDVI index in four classes of low, medium, dense and highest dense vegetation was extracted from Landsat images in 1987, 2002 and 2017 and then the results were validated using ground control points. Also, in order to predict vegetation density for 2032, vegetation map of 2017 was first simulated by applying CA-Markov model and then results were validated using actual vegetation map of the same year using validate module in IDRISI Terrset software followed by validation results and by applying the mentioned model, vegetation density map was predicted in 2032.
Results and discussion: The results of vegetation maps with over 85% accuracy show that the area with low, medium and highest dense vegetation classes had a decreased and dense vegetation class had an increased trend during the period of 1987 to 2017. Changes in vegetation classes in elevation classes over the 30 year period show low vegetation in classes of 1042 to 1587 and 2133 to 2678 meters, medium vegetation in classes of 1042 to 1587, 1587 to 2133 and 2678 to 3224 meters, dense vegetation in classes of 2133 to 2678 meters and highest dense vegetation in classes of 1042 to 1587 and 1587 to 2133 meter had a decreased trend. Also, vegetation density in slope classes showed that slope of 0-25% had the highest and slopes of 50-75% and more than 75% had the lowest vegetation density. Also, CA-Markov model results with more than 80% accuracy show that vegetation density in 2032 will be similar to previous periods and medium vegetation cover will have the highest vegetation area in Kermanshah city. The increasing and decreasing trend of vegetation classes indicates that the medium vegetation class will decrease compared to 2017 and the classes with low, dense and high dense vegetation will increase and assessment of vegetation classes in elevation and slope classes shows that at altitudes of 1042 to 1587, 1587 to 2133 and 2133 to 2678 meters and slopes of 0 to 25 percent, the highest vegetation density was related to medium and dense vegetation classes but at altitudes of 2678 to 3224 meters and the slope of 50 to 75 and more than 75 percent the highest vegetation density will be the low vegetation class.
Conclusion: In general, the results of this study showed that using NDVI and CA-Markov models with respect to the validation results of these methods can provide acceptable results from the vegetation status of an area.

کلیدواژه‌ها [English]

  • Vegetation density
  • Slope
  • Cellular automata
  • Elevation classes
  • Kermanshah

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فصلنامه علوم محیطی
دوره 18، شماره 4
دی 1399
صفحه 161-182

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