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.