Calibration of leaf area index estimating equations in maize and sugar beet based on MODIS sensor satellite data (Qazvin irrigation network)

Document Type : Research Paper



The most widespread method to determine temporal and spatial variations of LAI in a regional scale is empirical relationships based on the normalized difference of reflectance bands of satellite data. This study was done to evaluate the equations of remotely sensed LAI estimation and optimize their parameters. Therefore, LAI was measured in the field for summer growing season in irrigated fields in the Qazvin irrigation network. Remotely sensed LAI was estimated using the soil adjusted vegetation index (SAVI) that derived from the TERRA-MODIS images. Results of this paper showed that LAI estimating by reference equations for all crops have high value of the root mean square error (RMSE) (3- 4.7). Calibration of LAI according to SAVI was done to determine the best model constants. The modified version of the equation was obtained as the best LAI estimation equation with RMSE equal to 1.57 and coefficient of determination (R2) equal to 0.72.


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