اصلاح اثرات ابرناکی بر محصول پوشش برف روزانه سنجنده مودیس (مطالعه موردی: شمال غرب ایران)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری مهندسی منابع آب گروه علوم مهندسی آب، دانشکده کشاورزی، دانشگاه بوعلی سینا، همدان.

2 استاد گروه علوم مهندسی آب، دانشکده کشاورزی، دانشگاه بوعلی سینا، همدان

3 استادیار گروه مهندسی عمران، دانشکده فنی و مهندسی، دانشگاه بوعلی سینا، همدان.

چکیده

با توجه به دشواری تهیه داده‌های برف‌سنجی به‌صورت میدانی، سنجش از دور به‌عنوان یک راه‌حل سریع و مقرون به صرفه در تهیه این داده‌ها و ارائه آن‌ها به مدل‌های اقلیمی شناخته شده‌است. یکی از مشکلات استفاده از داده‌های ماهواره‌ای در برف‌سنجی، وجود ابر در این تصاویر است که موجب گسستگی زمانی-مکانی داده‌ها، و در نتیجه کاهش کارایی آن‌ها می‌شود. هدف از این تحقیق، ارائه چارچوب مناسبی برای حذف اثر ابر در تصاویر ماهواره‌ای و تولید داده‌های برف‌سنجی ماهواره‌ای بدون مزاحمت ابر است. بدین‌منظور با کمک داده‌های زمینی عمق برف، متوسط دما و بارش روزانه در ایستگاه‌های زمینی برف‌سنجی در حوضه آبریز دریاچه ارومیه و بخش غربی حوضه دریای مازندران، تصاویر روزانه MOD10A1 سنجنده مودیس در دو مرحله به‌صورت زمانی-مکانی مورد پردازش قرار گرفتند. نتایج مدل رگرسیون خطی چند متغیره نشان داد که مقادیر شاخص تفاضلی نرمال شده برف (NDSI) با داده‌های زمینی ایستگاه‌های برف‌سنجی موجود همبستگی بالا (047/0=RMSE و 85/0=r) دارد. بر همین اساس مناطق پوشیده شده با ابر در تصاویر مودیس با مقادیر حاصل از مدل جایگزین شدند. در مرحله دوم، با کمک روش‌های زمین آماری و با لحاظ کردن موقعیت مکانی هر پیکسل، مقادیر جدید NDSI محاسبه شد. با بررسی رابطه بین NDSI و میزان بارش تجمعی برف در بازه زمانی دی تا اسفند ماه سال 1397، مشخص شد که جایگزینی تصاویر ماهواره‌ای اولیه با تصاویر تصحیح شده موجب افزایش ضریب تببین (R2) از 63/0 به 81/0 شده است. این امر نشان‌دهنده بهبود دقت در برف‌سنجی ماهواره‌ای با استفاده از روش حاضر است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

The MODIS daily produces snow cover modification based on cloudy effects analysis (case study: northwest of Iran(

نویسندگان [English]

  • Razie Ebrahimi 1
  • Safar Marofi 2
  • Hossein Torabzadeh Khorasani 3
1 PhD candidate in Water Resources Engineering, Department of Water Science Engineering, Faculty of Agriculture, Bu Ali Sina University, Hamedan, Iran.
2 Professor, Department of Water Science Engineering, Faculty of Agriculture, Bu Ali Sina University, Hamedan, Iran
3 Assistant Professor, Department of Civil Engineering, Faculty of Engineering, Bu Ali Sina University, Hamedan, Iran.
چکیده [English]

Remote sensing is a fast and cost-effective solution in preparing and presenting this data to climate models due to the difficulty of preparing snow meteorological data in the field. The presence of clouds is one of the problems of satellite images that cause temporal-spatial fragmentation of snow data and increase its resolution efficiency. This study aims to provide a suitable framework for removing the effect of clouds on satellite images and generating the satellite snow metering data without disturbing cloud effects. For this purpose, first, daily MOD10A1 images of the MODIS sensor products were refined (temporally and spatially) using local snow depth data, average temperature, and daily rainfall of the Lake Urmia catchment and western part of the Caspian Sea basin. A multivariate linear regression model application showed that the normalized snow differential index (NDSI) values correlate with existing snow metering station data (r= 0.85 and RMSE= 0.047). Accordingly, the cloud-covered areas in the MODIS images were replaced with the values obtained from the model. Then, new NDSI values were calculated using geostatistical methods and the location of each pixel's location. By examining the relationship between the NDSI and the cumulative snowfall from January to March 2016, it was found that replacing the primary satellite images with corrected images can increase the R2 from 0.63 to 0.81. Therefore the proposed methodology could improve the accuracy of satellite snow metering.

کلیدواژه‌ها [English]

  • Snow Metering
  • Local Stations
  • linear Regression
  • Satellite Image Correction
  • Spatio-Temporal Discontinuity

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علوم و مهندسی آبیاری
دوره 47، شماره 1
خرداد 1403
صفحه 67-81

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سابقه مقاله

  • تاریخ دریافت: 13 اسفند 1400
  • تاریخ بازنگری: 25 مرداد 1401
  • تاریخ پذیرش: 29 مرداد 1401
  • تاریخ انتشار: 01 خرداد 1403

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