برآورد عملکرد گندم با استفاده از تصاویر ماهواره‌ای در استان گلستان
20.1001.1.23453419.1400.9.1.5.2

نوع مقاله : مقاله پژوهشی

نویسندگان

1 هیأت علمی دانشگاه علوم کشاورزی و منابع طبیعی گرگان

2 دانشگاه علوم کشاورزی و منابع طبیعی گرگان

چکیده

پیش‌بینی زودهنگام عملکرد گندم چند ماه قبل از برداشت که از چالش‌های مهم در بخش کشاورزی و امنیت غذایی است، مستلزم براورد میزان تولید در سطح وسیع و این امری زمان‌بر و پرهزینه می‌باشد. استفاده از سنجش از دور یک رهیافت عملی و نسبتاً دقیق برای رفع این مشکل است. تفاوتی که در بازتاب طیفی پدیده‌ها وجود دارد می‌تواند در شناسایی و اندازه‌گیری آن‌ها مورد استفاده قرار گیرد. مزارع گندم با توجه به شرایط رشد خود می‌توانند عملکردهای متفاوتی داشته باشند این تفاوت عملکرد بازتاب طیفی مزارع مختلف را تحت تأثیر قرار ‌دهد. در پژوهش حاضر 200 مزرعه گندم از شهرستان گنبدکاووس و مزارع زیر سد وشمگیر انتخاب و عملکرد آن‌ها در سال 1396 مدنظر قرار گرفت. پس از تصحیح تصویر ماهواره لندست 8 مربوط به اردیبهشت، اطلاعات باندهای طیفی آن استخراج و به همراه شاخص‌های مختلف مستخرج از آن‌ها 15متغیر مستقل تشکیل شد. رابطه آن‌ها با عملکرد گندم به عنوان متغیر وابسته با استفاده از روش‌های رگرسیون چندمتغیره خطی و رگرسیون درختی M5 جستجو شد. با توجه به غیرخطی بودن رابطه بین عملکرد گندم با بازتاب‌های طیفی، رگرسیون چند متغیره خطی نتایج رضایت‌بخشی را نشان نداد و در بهترین شرایط این رابطه دارای ضریب همبستگی 63/0 و میانگین خطای 425 کیلوگرم در هکتار بود. اما رگرسیون درختی M5، نتایج قابل قبول‌تری را نشان داد به طوری که با برقراری 5 رابطه رگرسیونی، باهمبستگی 89 درصد و خطای 325 کیلوگرم در هتار، عملکرد گندم را برآورد کرد. این میزان دقت با استفاده از باندهای 1، 3 و شاخص‌های NMDI، NDWI و نسبت باندی 4 به 3 بدست آمد. وجود خطا در گزارش عملکرد گندم، عدم یکنواختی مزرعه و کوچک بودن برخی از مزراع از منابع خطا می‌باشند که با رفع آن‌ها، امکان برآورد دقیق‌تر وجود خواهد داشت.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Wheat yield estimation using satellite images in Golestan province

نویسندگان [English]

  • Khalil Ghorbani 1
  • Reza Teimori 2
  • Meysam Salarijazi 1
1 Faculty member of Gorgan University of Agricultural Sciences and Natural Resources
2 Gorgan university of Agricultural sciences and Natural Resources
چکیده [English]

Early prediction of wheat yield is major challenge in agrictultural management and food security. This requires regional estimation of yield which is costly and time consuming. Remote sensing (RS) is a fundamental approach for achieving practical and effective solutions for this problem. The existing differences in the spectral reflectance characteristic of agiven phenomena such as crop canopies, can serve as an identifier attribute . Wheat farms can have different yields based on their various growth and management conditions. These variations can affect the spectral reflectance. In this research, the yields data for year 2017 of 200 wheat farms located in Gonbad-Kavus and Voshmgir Dam regions, Golestan province north of Iran have been studied. After correcting the Landsat 8 satellite images of month of May, spectral bands data were extracted, and 15 spectral indices were calculated. The relation between spectral indices and wheat yield were worked out using multivariate linear regression and M5 regression tree model. According to the nonlinear relation between wheat yield and spectral reflectance, multivariate linear regression did not perform well. The correlation coefficient was about 63%, and the mean error was about 425 kg ha-1. The M5 regression tree model predicted wheat yield with an accuracy of 89 % and root mean square error (RMSE) lower than 325 kg ha-1. This accuracy was obtained using bands 1, 3, and NMDI and NDWI indices and band 4 to band 3 ratios (B43). Inaccurate yield data the non-uniformity and small area of the farms are the main sources of error.

کلیدواژه‌ها [English]

  • Wheat
  • M5 regression tree
  • Remote Sensing
  • Spectral reflectance
  • Yield prediction
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