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   پایش سطح زیرکشت برنج با استفاده از سیستم اطلاعات جغرافیایی و تکنیک سنجش از دور  
   
نویسنده مصری آرش ,رحیمی اجدادی فاطمه ,باقری ایرج
منبع ماشين هاي كشاورزي - 1401 - دوره : 12 - شماره : 4 - صفحه:515 -527
چکیده    سنجش از دور، یکی از ابزارهای کارآمد برای بررسی روند تغییرات سطح زیرکشت محصولات کشاورزی و باغی در سطوح وسیع و زمان کوتاه است. سیاست‌گذاران با آگاهی از این اطلاعات، می‌توانند تصیمات صحیح و به‌موقعی داشته باشند. مطالعه‌ی حاضر، با هدف تخمین سطح زیرکشت شالیزارهای برنج در بخش کیاشهر استان گیلان انجام شد. از تصاویر سنجنده tm ماهواره لندست 5 و سنجنده oli ماهواره لندست 8 به‌منظور تهیه نقشه‌های کاربری اراضی استفاده شد. ابتدا، تصحیح هندسی و اتمسفری بر روی تصاویر صورت گرفت. سپس، با استفاده از الگوریتم طبقه‌بندی نظارت شده حداکثر احتمال، نقشه‌های کاربری اراضی منطقه با هفت کاربری شامل اراضی برنج، جنگل نیمه‌انبوه، جنگل تنک، مناطق مسکونی، مناطق آبی، پهنه‌های ماسه‌ای و سایر اراضی تهیه شد. در ادامه، مساحت هر یک از کاربری‌ها محاسبه شد و روند تغییرات، مورد مقایسه قرار گرفت. دقت کلّی و ضریب کاپای طبقه‌بندی به‌ترتیب معادل 98.45% و 0.98 برای سال 2000، 97.59% و 0.97 برای سال 2010 و 98.72% و 0.98 برای سال 2020 به‌دست آمد. نتایج نشان داد که اراضی برنج در یک بازه 20 ساله، با کاهش 6.94 درصدی همراه بوده، به‌طوری‌که مساحت آن از 11080.66 هکتار در سال 2000 به 10311.69 هکتار در سال 2020 رسیده است. همچنین، در این مدّت مناطق مسکونی و جنگل‌های تنک به‌میزان 67.94 و 18.73 درصد رشد کرده‌اند، اما جنگل‌های نیمه‌انبوه، مناطق آبی و پهنه‌های ماسه‌ای به‌ترتیب 61.32، 4.91 و 61.48 درصد کاهش داشتند. با توجه به نتایج، توجه جدّی به تغییر کاربری اراضی برنج و تخریب جنگل‌ها ضروری می‌باشد.
کلیدواژه حداکثر احتمال، جنگل تنک، طبقه‌بندی نظارت‌شده، کاربری اراضی
آدرس دانشگاه گیلان, گروه مهندسی بیوسیستم, ایران, دانشگاه گیلان, گروه مهندسی بیوسیستم, ایران, دانشگاه گیلان, گروه مهندسی بیوسیستم, ایران
پست الکترونیکی irajbagheri@guilan.ac.ir
 
   monitoring rice land changes using gis and rs  
   
Authors mesri a. ,rahimi-ajdadi f. ,bagheri i.
Abstract    introductionrice is the fourth most consumed grain worldwide. in recent years, monitoring the area under rice cultivation; as a strategic crop in gilan province has become more important because of the uncontrolled migration of residents of the southern provinces to it. remote sensing is one of the practical tools to study the trend of changes in the area under cultivation of agricultural and horticultural products on a large scale and in a short time. this technique can help policymakers to make true and timely decisions. the aim of this study is to estimate the area under rice cultivation in kiashahr county of gilan province.materials and methodsthe images of the tm sensor of landsat 5 satellite and the oli sensor of landsat 8 satellite were used to prepare land use maps. first, geometric and atmospheric corrections were made to the images. then, supervised classification using the maximum likelihood algorithm was used to prepare land use maps for each year. seven main classes/land covers, based on the available data of the area were determined: rice-land, semi-dense forest, sparse forest, built-up area (towns and other urbanized areas), waterbody, sandy area and other areas. then, the area of each land use was calculated by gis, and their changes were compared.results and discussionoverall accuracy and kappa coefficient of classification were 98.45% and 0.98 for 2000, 97.59% and 0.97 for 2010, and 98.72% and 0.98 for 2020, respectively. according to the results, rice land area decreased by 4.42% from 2000 to 2010. it also had a decrease of 2.64% between 2010 and 2020. in total, rice lands decreased by 6.94% between 2000 and 2020, so its area has decreased to 10311.69 hectares. this downward trend can be due to the conversion of rice land to the built-up area. the area of semi-dense forest decreased by 47.48% between 2000 and 2010, but its downward trend decreased to 26.36% between 2010 and 2020. in total, semi-dense forest area decreases by 61.32%, equal to 682.25 hectares over a period of 20 years. this is due to the uncontrolled cutting of trees and the change of land use from semi-dense forests to sparse forests and built-up areas. also, during this period, built-up areas and sparse forests have grown by 67.94% and 18.73%, respectively. but, semi-dense forests, water bodies and sandy areas have decreased by 61.32%, 4.91% and 61.48%, respectively.conclusionthe reduction rate in the area of rice land and semi-dense forest classes between 2010 and 2020 was lower than the ten-year period before, which can be attributed to the adoption of restrictive laws and more inspections by relevant organizations. however, the downward trends in these land uses have continued over the past decade. meanwhile, the increase of 67.94% of built-up lands indicates that the lost lands in the forest and rice land classes have been converted into the built-up area. the rate of land-use change in the built-up class has the highest rate among the studied classes. this result indicates the need for serious attention to land-use change in the rural area more than before. another point is that there was a growth in sparse forests between 2000 and 2010, and then a reverse trend was observed between 2010 and 2020, which shows that in a period of 10 years, deforestation has taken place, and in 10 years later, the lands from these destructions have been converted to the built-up area. as a result, serious attention to natural resource organizations is necessary. it is considered that there was a deliberate destruction of forests over time with the aim of personal profit.
Keywords land use ,maximum likelihood ,sparse forest ,supervised classification
 
 

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