Journal
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
Volume 10, Issue 4, Pages 438-452Publisher
ELSEVIER
DOI: 10.1016/j.jag.2006.12.001
Keywords
Yield forecasting; Regression; Wheat; Morocco; NDVI; AVHRR
Categories
Funding
- Belgian Technical Cooperation
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In Morocco, no operational system actually exists for the early prediction of the grain yields of wheat (Triticum aestivum L.). This study proposes empirical ordinary least squares regression models to forecast the yields at provincial and national levels. The predictions were based on dekadal (10-daily) NDVI/AVHRR, dekadal rainfall sums and average monthly air temperatures. The Global Land Cover raster map (GLC2000) was used to select only the NDVI pixels that are related to agricultural land. Provincial wheat yields were assessed with errors varying from 80 to 762 kg ha(-1), depending on the province. At national level, wheat yield was predicted at the third dekad of April with 73 kg ha(-1) error, using NDVI and rainfall. However, earlier forecasts are possible, starting from the second dekad of March with 84 kg ha(-1) error, at least I month before harvest. At the provincial and national levels, most of the yield variation was accounted for by NDVI. The proposed models can be used in an operational context to early forecast wheat yields in Morocco. (C) 2007 Elsevier B.V. All rights reserved.
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