Estimation Rainfed Wheat Yield Using Agro Climatic and Remote Sensing Indices in Kurdistan Province, Iran

The aim of this study is statistical modeling of rainfed wheat yield in Kurdistan province of Iran. In order to do this, multiple linear regression models were used. Dependent variable was rainfed wheat yield and independent variables were three, including climatic, agroclimatic and spectral indices extracted from satellite images. Boot strop method was run on all calculated models and based on this method forecasting values were presented for 2003 to 2006. The results show that the best model is based on Reproductive stage data. In Divandareh County, the best model is based on second growing period and creative process. In Marivan County, the best model established on dormancy stage and in Sanandaj and Ghorveh County calculated based on all growing season data. Also results show that among spectral indices, DVI index is a better predictive variable. Furthermore the accuracy of calculated models is increases based on a combination of agroclimatic and remote sensing indices. Running bootstrap resampling method also increases accuracy of calculated models. Therefore this method can be used for rainfed wheat yield forecasting.