اعتبارسنجی و ریزمقیاس سازی داده های رطوبت خاک ماهواره SMAP به روش SMBDA با استفاده از محصولات رادار Sentinel 1 و داده های زمینی در منطقه صالح آباد ایلام

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی و محیط زیست، گروه مهندسی و محیط زیست، دانشکده عمران و محیط زیست، دانشگاه تربیت مدرس.

2 استادیار گروه مهندسی عمران و محیط زیست، دانشکده عمران و محیط زیست، دانشگاه تربیت مدرس.

3 استادیار گروه پژوهشی هواشناسی کشاورزی، پژوهشگاه هواشناسی علوم جو.

چکیده

داده‌های رطوبت خاک سنجش از دور مایکرویو به دلیل پیوستگی زمانی-مکانی، توانایی بالایی برای فراهم نمودن اطلاعات رطوبتی خاک دارند. ماهواره SMAP ناسا در محدوده طیف مایکرویو (باند L-) و تفکیک مکانی حدود 40 کیلومتر از مهم‌ترین روش­‌های تهیه داده‌­های رطوبت خاک است. پایین بودن تفکیک مکانی داده‌‎های رطوبت خاک این ماهواره، سبب محدودیت در کاربردهای عملی و در مقیاس‌‎های محلی می‌‎گردد. در مطالعه حاضر به منظور ریزمقیاس­‌سازی داده‌های روزانه رطوبت خاک سطحی از محصولات سطح 4 ماهواره SMAP (با قدرت تفکیک Km 9) و افزایش قدرت تفکیک آن به 1 کیلومتر، یک الگوریتم ریزمقیاس‌­سازی با استفاده از روش ریزمقیاس‌­سازی SMBDA و تصویر‌ رادار ماهواره Sentinel 1 و مشاهدات زمینی توسعه داده شد. برای این منظور 1037 نمونه زمینی رطوبت خاک در 32 روز مختلف (پاییز و زمستان 1399) همزمان با محدوده گذر زمانی ماهواره Sentinel 1 از منطقه دشت صالح‌آباد (ایلام) اندازه‌‎گیری شد. نتایج نشان داد که ریشه مربعات خطا بین مقادیر رطوبت خاک ریزمقیاس شده با مشاهدات زمینی 085/0 (m3.m-3) است که درمقایسه با تحقیقات مشابه از صحت خوبی برخوردار است. تأثیر چالش‌­های تغییرات پوشش گیاهی و بارندگی بر صحت نتایج الگوریتم استفاده شده بررسی شد. تطویل زمان-مکانی اندازه‌گیری‌های میدانی به دلیل ایجاد تنوع و پراکندگی بیشتر در مقادیر اندازه‌گیری شده و همچنین پیاده‌سازی الگوریتم با استفاده از روش‌های غیرکلاسیک (محاسبات نرم) می‌تواند به بهبود نتایج ریزمقیاس‌­سازی بینجامد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Validation and Downscaling of SMAP Satellite Soil Moisture Data by the SMBDA Method Using Sentinel 1 Radar Products and Ground Data in SalehAbad Region of Ilam

نویسندگان [English]

  • Masoud Saboori Noghabi 1
  • Mohammad Mahdi Rajabi 2
  • Ebrahim Asadi Oskouei 3
1 M.Sc. of Environmental Engineering, Civil & Environmental Engineering Department, University of Tarbiat Modares, Tehran, Iran.
2 Assistant Professor, Civil & Environmental Engineering Department, Tarbiat Modares University, Tehran, Iran.
3 Assistant Professor of Institute for Atmospheric Sciences and Meteorology Research Center.
چکیده [English]

Microwave remote sensing soil moisture data have a high ability to provide soil moisture information due to their spatial-temporal coherence. NASA SMAP satellite is one of the most important methods for preparing soil moisture data within the microwave spectrum (L-band) and spatial separation of about 40 km. The low spatial resolution of the soil moisture data of this satellite causes limitations in practical applications and at local scales. In the present study, to subscale daily surface soil moisture data from SMAP 4 level satellite products (with a resolution of 9 km) and increase its resolution to one kilometer, a downscaling algorithm using SMBDA downscaling method, satellite radar image Sentinel 1, and ground observations were developed. For this purpose, 1037 soil samples of soil moisture in 32 different days (autumn and winter of 1399) were measured simultaneously with the passage of time of Sentinel 1 satellite from SalehAbad plain (Ilam). The results showed that the square root of the error between the values ​​of down-scale soil moisture with ground observations is 0.085 (m3.m-3), which has good accuracy compared to similar studies. The effect of the challenges of vegetation change and rainfall on the accuracy of the algorithm results used was investigated. The temporal-spatial extension of field measurements due to the greater variability and dispersion of the measured values ​​as well as the implementation of the algorithm using non-classical methods (soft computing) can improve the results of downscaling.

کلیدواژه‌ها [English]

  • soil moisture
  • Downscaling
  • SMAP
  • Sentinel 1
  • Ilam
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