برآورد دمای سطح زمین با استفاده از الگوریتم سبال (مطالعه موردی: استان همدان)

نویسندگان

چکیده

تعیین آب مورد نیاز یکی از پارامتر‌های مهم برای استفاده بهینه از منابع موجود آب در بخش کشاورزی است. برای برآورد دقیق آب لازم در سطح دشت‌های کشاورزی،‏ به اطلاعاتی درخصوص وضعیت پوشش گیاهی از قبیل میزان پراکنش و دمای سطح پوشش گیاهی نیاز است که اندازه‌گیری آن با روش‌های سنتی مشکل و هزینه‌بر است. در حالیکه تهیه آن‌ها به کمک سنجش از دور به‌سادگی انجام می‌شود. بنابراین در این پژوهش به کمک روش سنجش از دور،‏ دمای سطح زمین در استان همدان تعیین شد. ابتدا با پیش‌پردازش اطلاعات 12 تصویر ماهواره Landsat 7 ETM+ (1377-1381)،‏ ضریب بازتاب و ضریب تابش پوشش سطح زمین در باندهای مختلف محاسبه و شاخص‌های گیاهی NDVI تعیین و دمای سطح زمین با استفاده از الگوریتم سبال برآورد و با مقدار اندازه‌گیری شده در ایستگاه‌های هواشناسی مقایسه شد. نتایج نشان داد که دمای سطح زمین برآورد شده از اطلاعات سنجش از دور هماهنگی خوبی با آمار ثبت شده در ایستگاه‌های هواشناسی دارد و بین مقدار دمای پوشش سطح برآورد شده و اندازه‌گیری شده اختلاف معنی‌داری وجود ندارد. نتایج کلی نشان داد که الگوریتم سبال با ضریب همبستگی (2R)‎ 75‎/0 و ریشه میانگین مربعات خطا (RMSE)‎ 4‎/5 درجه،‏ دارای دقت خوبی است.

کلیدواژه‌ها


عنوان مقاله [English]

Estimation of surface temperature using the SEBAL algorithm (Case study: Hamedan province)

نویسندگان [English]

  • samira amini bazyani
  • mehdi akbari
  • hamid Zare Abyane
چکیده [English]

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.

کلیدواژه‌ها [English]

  • Surface temperature---ote sensing-Hamedan-Crop density-