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Within-field wheat yield prediction from IKONOS data: a new matrix approach

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This study demonstrates a unique matrix approach to determine within-field variability in wheat yields using fine spatial resolution 4 m IKONOS data. The matrix approach involves solving a system of simultaneous equations based on IKONOS data and post-harvest yields available at entire field scale. This approach was compared with a regression-based modelling approach involving field-sensor measured yields and the corresponding IKONOS measured indices and wavebands. The IKONOS data explained 74-78% variability in wheat yield. This is a significant result since the finer spatial resolution leads to capturing greater spatial variability and detail in landscape relative to coarser spatial resolution data. A pixel-by-pixel mapping of wheat yield variability highlights the fine spatial detail provided by IKONOS data for precision farming applications.
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Document Type: Research Article

Affiliations: 1: Center for Earth Observation (CEO) Yale University, 21 Sachem St., New Haven Connecticut 06520-8109 USA prasad.thenkabail@yale.edu, Email: eden.enclona@yale.edu 2: International Center for Agriculture in the Dry Areas (ICARDA), P.O. Box 5466, Aleppo Syria j.diekmann@cgiar.org, Email: d.celis@cgiar.org

Publication date: 2004-01-01

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