Prediction of wheat yield in Uzbekistan by using the CGMS model and SPOT-Vegetation data

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10 Jul 2008 10:00
Unit: Laboratory of Geo-Information Science and Remote Sensing

By Baytiyor Pulatov

Abstract:  

Wheat yield forecast under difficult environmental conditions in Uzbekistan is receiving considerable attention from governmental agencies, commodity traders and farmers. Objectives of this study is to investigate how we can best predict wheat yield early in the season in Uzbekistan. The approach used in this study is based on a crop growth simulation model which is able to quantify the effect of weather conditions on crop growth. Focus was on selection which indicators either from CGMS or SPOT-Vegetation data can be the best predictors for an explanation of year to year variation of wheat yield in Uzbekistan. The Crop Grow Monitoring System (called CGMS) provides a timely, accurate, synoptic and objective estimation for crop growth conditions and issues yield forecasts at regional and national level using remote sensing data. After CGMS and SPOT Vegetation data comparison the results showed that indicators maximum NDVI and maximum DMP which are driven from remote sensing SPOT-Vegetation data are performing the best at regional and at national level. 

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