نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه مهندسی ماشین‌های کشاورزی، دانشکده مهندسی و فن‌آوری کشاورزی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران
2 موسسه تحقیقات فنی و مهندسی کشاورزی، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران
چکیده
سنجش از دور و به‌کارگیری تصاویر ماهواره‌ها به‌علت سرعت کار و گستردگی سطح پوشش بسیار مورد توجه قرار گرفته است. کلزا به‌دلیل گل‌های زرد آن دارای رنگ پوشش گیاهی متفاوتی با سایر محصولات است و تحقیقات کمی در زمینه ارزیابی شاخص‌های طیفی به‌منظور پیش‌بینی عملکرد آن انجام گردیده است. در سال زراعی 96-95 با هدف پیش‌بینی عملکرد کلزا ده شاخص طیفی سنجنده سنتینل-2، مورد ارزیابی قرار گرفت. این تحقیق به شکل پیکسل‌مبنا در سه مزرعه انجام شد و محدوده شبکه‌ای پیکسل‌های مزارع با کمک سیستم موقعیت‌یابی جهانی سینماتیک زمان واقعی (RTKGPS) تعیین گردید. در این تحقیق مدل‌های رگرسیونی خطی ساده و چند متغیره و نیز شبکه عصبی به‌کار رفت. نتایج نشان داد براساس مدل رگرسیون خطی ساده، بین مراحل مختلف رشد، بیشترین ضریب تبیین (R2) در هر یک از شاخص‌های گیاهی در یکی از دو مرحله اوج گل‌دهی و رسیدگی سبز رخ می‌دهد. براساس این مدل، در مرحله اوج گل‌دهی، شاخص تفاضل نرمال شده زردی (NDYI) با 73 درصد بیشترین ضریب تبیین را نسبت به سایر شاخص‌ها احراز کرد. با به‌کارگیری مدل رگرسیون خطی چند متغیره گام به گام با ورودی چهار باند، سه باند مرئی و باند مادون قرمز نزدیک، بهترین مدل در مرحله اوج گل‌دهی با ضریب تبیین 76 درصد و اعتبارسنجی 73 درصد با ریشه میانگین مربعات خطا (RMSE) به‌میزان 0.641 به‌دست آمد. همچنین با استفاده از مدل شبکه عصبی و ورود چهار باند مذکور نیز بهترین مدل در مرحله اوج گل‌دهی با ضریب تبیین 92 درصد (آموزش) و اعتبارسنجی (آزمون) 77 درصد با RMSE به‌میزان 0.612 احراز شد.
کلیدواژه‌ها
Open Access
©2020 The author(s). This article is licensed under Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source.
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