تلفیق تصاویر ماهواره Landsat 8 و سنجنده ی MODISجهت برآورد نیاز آبی ذرت علوفه‌ای در دوره رشد (منطقه مورد مطالعه: ماهیدشت کرمانشاه)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 گروه مهندسی آب- دانشکده علوم و مهندسی کشاورزی- دانشگاه رازی

2 استادیار گروه مهندسی آب دانشگاه رازی

3 دانشیار دانشگاه تونته هلند

چکیده

تبخیر و تعرق به عنوان یکی از مولفه‌های کلیدی چرخه هیدرولوژیکی می‌باشد و کمی کردن مقادیر آن جهت درک فرایندهای اصلی از قبیل تغییرات فنولوژی پوشش گیاهی، خطرات زیست محیطی مانند سیلاب و خشکسالی، و به طور کلی بیلان آب اکوسیستم‌ها امری ضروری می‌باشد. استفاده از روش‌های مبتنی بر بیلان انرژی سطحی با استفاده از سنجش از دور جهت تخمین تبخیر و تعرق بطور روز افزونی افزایش یافته است. هدف از پژوهش حاضر، تلفیق تصاویر لندست 8 و مودیس با استفاده از الگوریتم سبال جهت برآورد تبخیر و تعرق گیاه ذرت در منطقه ماهیدشت کرمانشاه می‌باشد. به منظور تلفیق تصاویر ماهواره‌ای از روش خطی با عرض از مبدا صفر(LinZi) استفاده شد. همچنین همزمان تبخیر و تعرق واقعی ذرت در 15 مزرعه واقع در منطقه مورد مطالعه بر اساس داده‌های زمینی برآورد گردید. نتایج حاصل از الگوریتم سبال با برآوردهای زمینی تبخیر و تعرق با استفاده از آماره‌های MAE، BIAS و RMSE مورد مقایسه قرار گرفتند. نتایج بیانگر این بود که تلفیق تصاویر ماهواره‌ای منجر به بهبود دقت تبخیر و تعرق برآوردی نسبت به تصاویر لندست 8 شده است. میانگین خطای مطلق تبخیر و تعرق برآوردی در طول دوره رشد بر اساس تصاویر لندست و تلفیق تصاویر به ترتیب 44/0 و 42/0 میلی‌متر در روز تعیین گردید. به طور کلی نتایج این تحقیق نشان داد که برآورد تبخیر و تعرق با استفاده از الگوریتم سبال و براساس تلفیق تصاویر با دقت‌های متفاوت زمانی و مکانی می‌تواند نتایج قابل قبولی را ارائه دهد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Integration of Landsat 8 satellite images and MODIS sensor to estimate the water requirement of maize during the growth period (Case study: Mahidasht, Kermanshah province)

نویسندگان [English]

  • Hadi Varvani 1
  • Bahman Farhadi Bansouleh 2
  • Mohammad Ali Sharifi 3
1 Department of Water Engineering, Faculty of Agriculture Sciences and Engineering, Razi University
2 Department of Water Engineering, Faculty of Agriculture Sciences and Engineering, Razi University
3 Associate Professor at the University of Toledo, Netherlands
چکیده [English]

Evapotranspiration is one of the key components of the hydrological cycle and its quantification is essential to understand the processes such as vegetation phenological changes, environmental hazards such as floods and droughts, and, in general, the ecosystem water balance. The use of remote sensing methods based on surface energy balance has been increased to estimate evapotranspiration. The purpose of this study was to estimate the evapotranspiration of corn based on integration of Landsat 8 and MODIS satellite images using the SEBAL algorithm in in Mahidasht, Kermanshah province. Linear with Zero Intercept (LinZi) method was used to integrate satellite images. Also, actual evapotranspiration of corn in 15 farms in the study area was estimated based on ground data. The results of the SEBAL algorithm were compared with ground-based evapotranspiration using MAE, BIAS and RMSE indices. The results indicated that the combination of satellite images has led to an improvement in the accuracy of estimated evapotranspiration compared to Landsat 8 images. The mean absolute error of estimated evapotranspiration during the growth period was determined as 0.44 and 0.42 mm.day -1 respectively based on Landsat 8 and combined images. In general, the results of this study showed that the estimation of evapotranspiration using the SEBAL algorithm and based on the integration of satellite images with different spatial and temporal resolutions could have acceptable results.

کلیدواژه‌ها [English]

  • Energy balance
  • evapotranspiration
  • Linzi
  • Remote Sensing
  • SEBAL

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