Article ID Journal Published Year Pages File Type
4464916 International Journal of Applied Earth Observation and Geoinformation 2012 8 Pages PDF
Abstract

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 rate 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.

► Wheat-specific GAI time series were retrieved from MODIS daily reflectance data. ► A modified logistic function was fitted to the decreasing GAI curves in order to calculate the metrics characterizing these shapes. ► Regression-based models are developed relying on these metrics ► Wheat yields were satisfactorily estimated using these models at a high EU NUTS level.

Related Topics
Physical Sciences and Engineering Earth and Planetary Sciences Computers in Earth Sciences
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