Using SPOT data and leaf area index for rice yield estimation in Egyptian Nile delta

Abstract

The objective of the current work is to generate statistical empirical rice yield estimation models under the local conditions of the Egyptian Nile delta. The methodology is based on regressing measured yield with satellite derived spectral information or leaf area index (LAI). LAI field measurements and spectral information from SPOT data collected during two crop seasons are examined against measured yield to generate the yield models. Near-infrared and red bands, six vegetation indices and LAI of 100 points are used as the main inputs for the modeling process while 20 points of the same are used for validation process. Nine models are generated and tested against the observed yield. Comparing the generated models show relatively higher superiority of (LAI-yield) and (infrared-yield) models over the rest of the models with (0.061) and (0.090) as a standard error of estimate and (0.945) and (0.883) as coefficient of determinations between modeled and observed yield. The models are applicable a month before harvest for similar regions with same conditions.

Keywords

• SPOT
• Leaf area index
• Vegetation Indices
• Statistical models