بررسی تغییرات سطح جنگلی با استفاده از مدل LCM در تصاویر ماهواره‌ای در شمال ایران با رویکرد جغرافیای انسانی
محورهای موضوعی : ارزیابی های زیست محیطی
امین خادمی
1
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مرتضی معدنی پور کرمانشاهی
2
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سیدآرمین هاشمی
3
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بهروز کرد
4
1 - گروه فضای سبز، واحدملایر، دانشگاه آزاد اسلامی، ملایر، ایران
2 - گروه محیط زیست، واحد پرند، دانشگاه آزاد اسلامی، پرند، ایران
3 - گروه جنگلداری، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران
4 - گروه فضای سبز، واحدملایر، دانشگاه آزاد اسلامی، ملایر، ایران
کلید واژه: تغییرات سطح جنگل, سنجش از دور, شهرستان تالش, جنگل انبوه.,
چکیده مقاله :
هدف از این تحقیق مقایسة تغییرات سطح جنگل با استفاده از مدل LCM در تصاویر ماهواره‌ای در جنگل‌های تالش بوده است. روند تغییرات کاربری محدودة مطالعاتی با استفاده از تصاویر ماهواره لندست سنجنده‌های TM، + ETMو OLI در سال‌های 2000، 2010 و 2020 با روش نظارت شده شبکه عصبی پردازش گردید. نقشه طبقه‌بندی کاربری اراضی شامل کاربری مسکونی، زراعت، مراتع، جنگل انبوه، جنگل نیمه‌انبوه، جنگل تنک در منطقه شناسایی شد. برای این منظور از تصاویر نرم‌افزار گوگل ارث و بازدید میدانی در تهیه نقاط تعلیمی استفاده شد. در نهایت ماتریس دقت برای هر نقشه تشکیل شد. تغییرات کاربری اراضی از سال 2000 تا 2020 با روش شبکه عصبی مصنوعی نشان داد، مناطق مسکونی 210 درصد و کاربری زراعت 1500 درصد، کاربری جنگل نیمه‌انبوه 200 درصد و جنگل تنک340 درصد هکتار افزایش و کاربری جنگل انبوه نیز 50 درصد و مرتع 30 درصد کاهش داشته است. صحت نقشه‌های طبقه‌بندی در این پژوهش در سال 2000 و 2010 و 2020 به‌‌ترتیب 88/0، 8950/0، 9150/0 به‌دست آمد که قابل قبول بود. نتایج تحقیق نشان داد که گسترش فعالیت‌های زراعی و ساخت مناطق مسکونی بر روی اکوسیستم‌های مرتعی و جنگل موجب تبدیل مراتع و جنگل‌های تنک به زمین‌های با ارزش کمتر شده است.
Abstract
Introduction: The purpose of this research was to compare the forest level changes using the LCM model in satellite images in Talash forests. Studying the amount of changes and destruction of resources in the past years and the feasibility and prediction of these changes in the coming years can be the necessity of conducting research in line with planning and optimal use of natural resources.
Materials and Methods: The trend of usage changes in the study area was processed using the satellite images of TM, ETM, and OLI sensors in the years 2000, 2010, and 2020 with the supervised neural network method. Land use classification map including residential use, agriculture, pastures, dense forest, semi-dense forest, and thin forest was identified in the region. For this purpose, Google Earth software images and field visits were used to prepare educational points. Multi-layer perceptron neural network was used for image classification.Finally, the accuracy matrix was formed for each map. Modeling with TerrSet2020 software has made it possible to investigate the changes in land use between the researched years and display the results with different charts and maps in a quantitative and qualitative manner.
Results and Discussion: The changes in land use from 2000 to 2020 with the artificial neural network method showed that residential areas increased by 210% and agricultural use by 1500%, semi-dense forest use by 200%, and thin forest by 340% of hectares, and dense forest use by 50% and pasture by 30%. had. The accuracy of the classification maps in this research was 0.88, 0.8950, and 0.9150 respectively in 2000, 2010, and 2020, which was acceptable.
Conclusion: The research showed that the expansion of agricultural activities and the construction of residential areas on pasture and forest ecosystems have turned pastures and thin forests into less valuable land. In general, in this research, it can be concluded that there have been changes in use in the studied area, and according to the results of the studies, the main changes are related to the change of use of pasture to agricultural and residential land, the change of untouched forests and It has been dense to semi-dense and thin forests. Using images with higher resolution in the scope of the research and comparing it with the research results of other researchers can be useful. Therefore, it is necessary to monitor user changes and control user changes within the scope of studies to be paid attention to by officials and planners.
Acknowledgements: The authors of this article appreciate Islamic Azad University for their support.
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