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برآورد دماي سطح زمين با استفاده از الگوريتم سبال (مطالعه موردي: استان همدان)
عنوان (انگلیسی): Estimation of surface temperature using the SEBAL algorithm (Case study: Hamedan province)
نشریه: پژوهش آب ايران
شماره: پژوهش آب ايران (دوره: ۱۰، شماره: ۲)
نویسنده: امینی بازیانی، سمیرا ، زارع ابیانه، حمید ، اکبری، مهدی
کلیدواژه‌ها : سنجش از دور ، دماي سطح زمين ، تراكم پوشش گياهي ، همدان.
کلیدواژه‌ها (انگلیسی): Crop density , Hamedan , Remote sensing , Surface temperature
چکیده:

تعيين آب مورد نياز يکي از پارامتر‌هاي مهم براي استفاده بهينه از منابع موجود آب در بخش کشاورزي است. براي برآورد دقيق آب لازم در سطح دشت‌هاي کشاورزي،‏ به اطلاعاتي درخصوص وضعيت پوشش گياهي از قبيل ميزان پراکنش و دماي سطح پوشش گياهي نياز است که اندازه‌گيري آن با روش‌هاي سنتي مشکل و هزينه‌بر است. در حاليکه تهيه آن‌ها به كمك سنجش از دور به‌سادگي انجام مي‌شود. بنابراين در اين پژوهش به كمك روش سنجش از دور،‏ دماي سطح زمين در استان همدان تعيين شد. ابتدا با پيش‌پردازش اطلاعات 12 تصوير ماهواره Landsat 7 ETM+ (1377-1381)،‏ ضريب بازتاب و ضريب تابش پوشش سطح زمين در باندهاي مختلف محاسبه و شاخص‌هاي گياهي NDVI تعيين و دماي سطح زمين با استفاده از الگوريتم سبال برآورد و با مقدار اندازه‌گيري شده در ايستگاه‌هاي هواشناسي مقايسه شد. نتايج نشان داد که دماي سطح زمين برآورد شده از اطلاعات سنجش از دور هماهنگي خوبي با آمار ثبت شده در ايستگاه‌هاي هواشناسي دارد و بين مقدار دماي پوشش سطح برآورد شده و اندازه‌گيري شده اختلاف معني‌داري وجود ندارد. نتايج کلي نشان داد که الگوريتم سبال با ضريب همبستگي (2R)‎ 75‎/0 و ريشه ميانگين مربعات خطا (RMSE)‎ 4‎/5 درجه،‏ داراي دقت خوبي است.

چکیده (انگلیسی):

Determination of water requirements is an important parameter for optimum use of the available water resources in agricultural purposes. Some information about plant cover condition such as plant surface temperature and crop density over the entire area are necessary for accurate estimation of required water in the basin scale. Measurement of these parameters by traditional methods are very difficult and expensive. While estimation of the mentioned parameters by remote sensing (RS) techniques are very easy. Hence, in the present study, ground surface temperature in Hamedan province was determined by RS techniques. For this purpose, a set of 12 Landsat 7 ETM+ images during 1998-2002 were selected and the reflection coefficient of ground surface, ground radiation coefficient, vegetation indexes, such as NDVI were determined. Based on these indicators the surface temperature was estimated using the SEBAL (surface energy balance algorithm for land) algorithm and compared with measured data in meteorological stations of Hamedan province. Results indicated that there is no significant difference between the surface temperature estimated from remote sensing data and that reported by meteorological stations. Overall results showed that the SEBAL algorithm with a correlation coefficient of 0.75 and Root Mean Square Error (RMSE) of 5.4 c○ had a high accuracy in estimating the ground surface temperature.

Determination of water requirements is an important parameter for optimum use of the available water resources in agricultural purposes. Some information about plant cover condition such as plant surface temperature and crop density over the entire area are necessary for accurate estimation of required water in the basin scale. Measurement of these parameters by traditional methods are very difficult and expensive. While estimation of the mentioned parameters by remote sensing (RS) techniques are very easy. Hence, in the present study, ground surface temperature in Hamedan province was determined by RS techniques. For this purpose, a set of 12 Landsat 7 ETM+ images during 1998-2002 were selected and the reflection coefficient of ground surface, ground radiation coefficient, vegetation indexes, such as NDVI were determined. Based on these indicators the surface temperature was estimated using the SEBAL (surface energy balance algorithm for land) algorithm and compared with measured data in meteorological stations of Hamedan province. Results indicated that there is no significant difference between the surface temperature estimated from remote sensing data and that reported by meteorological stations. Overall results showed that the SEBAL algorithm with a correlation coefficient of 0.75 and Root Mean Square Error (RMSE) of 5.4 c○ had a high accuracy in estimating the ground surface temperature.

Determination of water requirements is an important parameter for optimum use of the available water resources in agricultural purposes. Some information about plant cover condition such as plant surface temperature and crop density over the entire area are necessary for accurate estimation of required water in the basin scale. Measurement of these parameters by traditional methods are very difficult and expensive. While estimation of the mentioned parameters by remote sensing (RS) techniques are very easy. Hence, in the present study, ground surface temperature in Hamedan province was determined by RS techniques. For this purpose, a set of 12 Landsat 7 ETM+ images during 1998-2002 were selected and the reflection coefficient of ground surface, ground radiation coefficient, vegetation indexes, such as NDVI were determined. Based on these indicators the surface temperature was estimated using the SEBAL (surface energy balance algorithm for land) algorithm and compared with measured data in meteorological stations of Hamedan province. Results indicated that there is no significant difference between the surface temperature estimated from remote sensing data and that reported by meteorological stations. Overall results showed that the SEBAL algorithm with a correlation coefficient of 0.75 and Root Mean Square Error (RMSE) of 5.4 c○ had a high accuracy in estimating the ground surface temperature.

Determination of water requirements is an important parameter for optimum use of the available water resources in agricultural purposes. Some information about plant cover condition such as plant surface temperature and crop density over the entire area are necessary for accurate estimation of required water in the basin scale. Measurement of these parameters by traditional methods are very difficult and expensive. While estimation of the mentioned parameters by remote sensing (RS) techniques are very easy. Hence, in the present study, ground surface temperature in Hamedan province was determined by RS techniques. For this purpose, a set of 12 Landsat 7 ETM+ images during 1998-2002 were selected and the reflection coefficient of ground surface, ground radiation coefficient, vegetation indexes, such as NDVI were determined. Based on these indicators the surface temperature was estimated using the SEBAL (surface energy balance algorithm for land) algorithm and compared with measured data in meteorological stations of Hamedan province. Results indicated that there is no significant difference between the surface temperature estimated from remote sensing data and that reported by meteorological stations. Overall results showed that the SEBAL algorithm with a correlation coefficient of 0.75 and Root Mean Square Error (RMSE) of 5.4 c○ had a high accuracy in estimating the ground surface temperature.

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صاحب امتیاز:
دانشگاه شهرکرد
مدیر مسئول:
دکتر حسين صمدی
سردبیر:
دکتر منوچهر حيدرپور
مدیر داخلی:
دکتر محمدعلی نصراصفهانی