Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine
Winter wheat crop yield forecasting at national, regional and local scales is an extremely important task. This paper aims at assessing the efficiency (in terms of prediction error minimization) of satellite and biophysical model based predictors assimilation into winter wheat crop yield forecasting...
Main Authors: | , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2015-04-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-7-W3/39/2015/isprsarchives-XL-7-W3-39-2015.pdf |
Summary: | Winter wheat crop yield forecasting at national, regional and local scales is an extremely important task. This paper aims at
assessing the efficiency (in terms of prediction error minimization) of satellite and biophysical model based predictors assimilation
into winter wheat crop yield forecasting models at different scales (region, county and field) for one of the regions in central part of
Ukraine. Vegetation index NDVI, as well as different biophysical parameters (LAI and fAPAR) derived from satellite data and
WOFOST crop growth model are considered as predictors of winter wheat crop yield forecasting model. Due to very short time
series of reliable statistics (since 2000) we consider single factor linear regression. It is shown that biophysical parameters (fAPAR
and LAI) are more preferable to be used as predictors in crop yield forecasting regression models at each scale. Correspondent
models possess much better statistical properties and are more reliable than NDVI based model. The most accurate result in current
study has been obtained for LAI values derived from SPOT-VGT (at 1 km resolution) on county level. At field level, a regression
model based on satellite derived LAI significantly outperforms the one based on LAI simulated with WOFOST. |
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ISSN: | 1682-1750 2194-9034 |