انتخاب مناسب‌ترین الگوریتم روزنه مجزا در تخمین دمای سطح زمین با استفاده از سنجنده MODIS مطالعه موردی: دشت کرمان

نوع مقاله : مقاله کامل علمی پژوهشی

نویسندگان

دانشگاه شهید باهنر کرمان

چکیده

استفاده از داده‌های سنجش‌ازدور جهت برآورد دمای سطح زمین روش جدیدی به شمار می‌آید که هزینه‌های تخمین دما به روش کلاسیک را به‌طور چشمگیری کاهش می‌دهد. به همین منظور در دشت کرمان برای بررسی دمای سطح زمین از 12 تصویر بدون ابر مربوط به سنجنده MODIS (که در زمینه انطباق جز به جز تصاویر انعکاسی و حرارتی مشکلی ندارد)، در بازه زمانی تابستان 1392 و 10 الگوریتم روزنه مجزا برای تخمین دمای سطح زمین استفاده شد. همچنین برای مقایسه نتایج الگوریتم‌‌های روزنه مجزا، درجه حرارت 5 سانتی‌متری عمق خاک در ساعت گذر ماهواره در 12 روز منتخب، توسط یک دماسنج دیجیتالی در نقاط مشخص با یک دستگاه GPS دستی اندازه‌گیری شد. نتایج نشان داد مدل کول و کاسیلیس (1978) با MAE برابر با 76/4 سانتی‌گراد و MBE برابر با 07/0- بیشترین دقت را در بین مدل‌ها دارا می‌باشد. مدل پرایس (1984) با احتساب MAE مساوی با 98/4 و MBE مساوی با 081/0 در جایگاه دوم با دقتی نسبتا نزدیک به مدل کول قرار گرفته است و مدل بیکرولی (1990) در بین این 10 الگوریتم پایین-تربن دقت را با احتساب MAE برابر با 21/6 و MBE برابر با 73/3 داشته است. R2 برابر با 81/0 بین نتایج حاصل از برداشت زمینی و دمای منتج از داده‌های ماهواره‌ای تیز صحت الگوریتم کول و کاسیلیس (1978) را نشان می‌دهد. در نهایت نقشه طبقه‌بندی دمایی دشت شهرستان کرمان با روش ماشین بردار پشتیبان براساس نمونه‌های تعلیمی در پنج کاربری (شهری، کوهستان، دشت، بایر و کشاورزی) تهیه گردید.

کلیدواژه‌ها


عنوان مقاله [English]

Choosing the most appropriate split-window algorithms for estimating land surface temperature by use of MODIS sensor case study: Kerman Plain

نویسنده [English]

  • Saeed Delgarm
چکیده [English]

Abstract
The use of remote sensing data for land surface temperature estimation is regarded as a new method which significantly reduces costs of temperature estimation in classical method. For this purpose, for checking the land surface temperature in Kerman plain, 12 cloudless images from MODIS sensor in the summertime of 1392 and 10 split-window algorithm were used to estimate the land surface temperature. Also, to compare these split-window algorithms, the temperature in 5cm soil depth at satellite passing moment in 12 selected days was estimated by a digital thermometer and a handheld GPS device in the observed points. The results showed that MODIS sensor has the ability to detect heterogeneous surfaces and peaks and is good at Fractionation compliance reflective and thermal images. The model of Cole and Casillas (1978) with MARE of 4/762 and MBE of -0/075 has the highest accuracy among the other models. The Price model with MAE of 4/987 and MBE of 0/0817 is located on the second place with accuracy close to the Cole model. Bikroly model (1990) has the lowest accuracy among 10 algorithm, with MAE of 6/214 and MBE of 3/739. R2 of 0/8091 also shows the accuracy of Cole and Casillas (1978) algorithm between the results derived from ground conclusion and the temperature derived from satellite data. Then , thermal classification map of Kerman county plain were obtained by use of Support Vector Machine method which is a powerful tool in the Zoning.

کلیدواژه‌ها [English]

  • split-window algorithm
  • MODIS sensor
  • Cole and Casillas
  • Support vector machine
  • Kerman plain
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