Estimating regional wheat yield from the shape of decreasing curves of green area index temporal profiles retrieved from MODIS data
Article
Article Title | Estimating regional wheat yield from the shape of decreasing curves of green area index temporal profiles retrieved from MODIS data |
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ERA Journal ID | 4640 |
Article Category | Article |
Authors | Kouadio, Louis (Author), Duveiller, Gregory (Author), Djaby, Bakary (Author), El Jarroudi, Moussa (Author), Defourny, Pierre (Author) and Tychon, Bernard (Author) |
Journal Title | International Journal of Applied Earth Observation and Geoinformation |
Journal Citation | 18 (1), pp. 111-118 |
Number of Pages | 8 |
Year | 2012 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 0303-2434 |
1569-8432 | |
1872-826X | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.jag.2012.01.009 |
Web Address (URL) | http://www.sciencedirect.com/science/article/pii/S0303243412000116 |
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. |
Keywords | yield estimates; regional scale; green area index; senescence; wheat; MODIS |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 300206. Agricultural spatial analysis and modelling |
300205. Agricultural production systems simulation | |
300207. Agricultural systems analysis and modelling | |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | University of Liege, Belgium |
Catholic University of Leuven, Belgium | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q2qx8/estimating-regional-wheat-yield-from-the-shape-of-decreasing-curves-of-green-area-index-temporal-profiles-retrieved-from-modis-data
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Kouadio_Duveiller_Djaby_ElJarroudi_Defourny_Tychon_IJAEOG_2012_PV.pdf | ||
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