Reference : Estimating regional wheat yield from the shape of decreasing curves of green area index ...
Scientific journals : Article
Life sciences : Environmental sciences & ecology
Life sciences : Agriculture & agronomy
http://hdl.handle.net/2268/115721
Estimating regional wheat yield from the shape of decreasing curves of green area index temporal profiles retrieved from MODIS data
English
Kouadio, Amani Louis mailto [Université de Liège - ULg > DER Sc. et gest. de l'environnement (Arlon Campus Environ.) > Agrométéorologie (relation agriculture-environ. physique) >]
Duveiller, Gregory mailto [European Joint Research Centre > Institute for the Environment and Sustainability > Monitoring Agricultural Resources Unit > >]
Djaby, Bakary mailto [Université de Liège - ULg > DER Sc. et gest. de l'environnement (Arlon Campus Environ.) > DER Sc. et gest. de l'environnement (Arlon Campus Environ.) >]
El Jarroudi, Moussa mailto [Université de Liège - ULg > DER Sc. et gest. de l'environnement (Arlon Campus Environ.) > Agrométéorologie (relation agriculture-environ. physique) >]
Deforuny, Pierre mailto [Université Catholique de Louvain - UCL > Earth and Life Institute > > >]
Tychon, Bernard mailto [Université de Liège - ULg > DER Sc. et gest. de l'environnement (Arlon Campus Environ.) > Agrométéorologie (relation agriculture-environ. physique) >]
2012
International Journal of Applied Earth Observation and Geoinformation
Elsevier Science
18
111-118
Yes (verified by ORBi)
International
0303-2434
1569-8432
Amsterdam
The Netherlands
[en] Yield estimates ; Regional scale ; Green area index ; Senescence ; Wheat ; MODIS
[en] Earth observation data, owing to their synoptic, timely and repetitive coverage, have been recognized as a valuable tool for crop monitoring at different levels. At the field level, the close correlation between green leaf area (GLA) during maturation and grain yield in wheat revealed that the onset and rate of senescence appeared to be important factors for determining wheat grain yield. Our study sought to explore a simple approach for wheat yield forecasting at the regional level, based on metrics derived from the senescence phase of the green area index (GAI) retrieved from remote sensing data. This study took advantage of recent methodological improvements in which imagery with high revisit frequency but coarse spatial resolution can be exploited to derive crop-specific GAI time series by selecting pixels whose ground-projected instantaneous field of view is dominated by the target crop: winter wheat. A logistic function was used to characterize the GAI senescence phase and derive the metrics of this phase. Four regression-based models involving these metrics (i.e., the maximum GAI value, the senescence date and the thermal time taken to reach 50% of the green surface in the senescent phase) were related to official wheat yield data. The performances of such models at this regional scale showed that final yield could be estimated with an RMSE of 0.57 ton ha−1, representing about 7% as relative RMSE. Such an approach may be considered as a first yield estimate that could be performed in order to provide better integrated yield assessments in operational systems.
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/2268/115721
10.1016/j.jag.2012.01.009
http://dx.doi.org/10.1016/j.jag.2012.01.009

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