کاربرد تصاویر ماهواره‌ای چند زمانه در بهبود دقت مدل‌های پیش‌یابی فنولوژی ذرت

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه تهران

2 گروه مهندسی ابیاری-دانشگاه تهران

3 دانشگاه علوم کشاورزی و منابع طبیعی گرگان

4 موسسه ژئوفیزیک دانشگاه تهران

چکیده

متداول­­ترین شیوه پیش­یابی مراحل فنولوژیکی گیاهان، استفاده از کمیت درجه-روز رشد تجمعی (AGDD) می­باشد. در تحقیق حاضر، مدلی برای تدقیق این روش با تلفیق دو نمایه AGDD و NDVI برای تخمین تاریخ شروع 8 مرحله فنولوژیکی گیاه ذرت رقم K407، با استفاده از داده­های یک دوره 9 ساله در منطقه کرج ارائه شده است. روش هموارسازی نوفه­ها در کاربست نمایه NDVI، ترکیبی از دو روش لجستیک دوگانه و رگرسیون وزنی (WLS-DL) می باشد. نتایج مدل تلفیقی با دو مدل مبتنی بر درجه-روز رشد و تاریخ­ کاشت مقایسه شد. یافته­های پژوهش نشان داد، مدل تلفیقی به طور متوسط، مقدار RMSE تاریخ­های شروع 7 مرحله ابتدایی فنولوژیکی (ظهور تا شیری شدن) را به ترتیب 7/1، 4/1، 8/0، 3/1، 4/2، 4/2 و 3/3 روز نسبت به مدل مبتنی بر تاریخ­های کاشت و 9/2، 7/1، 4/1، 9/2، 6/4، 9/2، 6/3 روز نسبت به مدل درجه- روز رشد، کمتر برآورد می نماید.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Application of multi temporal satellite images for improvement of maize phenology models prediction

نویسندگان [English]

  • Mahdi Ghamghami 1
  • Nozar Ghahreman 2
  • khalil Ghorbani 3
  • Parviz Irannejad 4
1
2
3
4
چکیده [English]

Crop phonological stages are commonly predicted by using accumulated growth degree days(AGDD).In this study a combined model of AGDD and remotely sensed NDVI has been developed for prediction of maize (cv. K407) phenology in Karaj using a nine year (2002 to 2010) dataset. For smoothing the existing noises of image processing, a combination of double logistic and weighing average (DL-WLS) approaches was employed. The results of combined phenology model were compared by two frequently used methods based on AGDD and date of sowing. The findings showed that in general, the developed model predicted the first 7 phenological stages of emergence to milky, more accurately comparing to other approaches (with average 2 and 2.5 days difference with observed dates, respectively) but was inaccurate for maturity stage. Our study highlights the need for further improvements in observations in the region.

کلیدواژه‌ها [English]

  • NDVI
  • Double logistic
  • weighing regression
  • Phenology
  • maize
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