Estimation de la biomasse fourragère des prairies : apports du couplage entre modèles dynamiques de croissance et imagerie satellitaire : exemple de La Réunion et du Kalahari

Abstract : The purpose of this study was to explore the possibility of coupling dynamic models of grass growth with remote sensing data for two contrasting countries: Reunion Island and Kalahari (South Africa). Two phases followed one another. A first exploratory phase, based on SPOT5 and SPOT5take5 images (desorbed satellites under study) allowed us to learn from this experience. In Reunion the adjustment of an empirical model between vegetation indices and biomass generates too much error. However it is possible to estimate the Leaf Area Index (LAI) thanks to the NDVI (Normalized Difference Vegetation Index). More complex Kalahari rangelands with different vegetation strata (grasses, shrubs, trees) failed to estimate grass cover conditions. This phase set the stage to work on a more durable sensor over time, Sentinel-2. Sentinel-2 data made it possible to estimate the LAI of Reunion Island grasslands with a RMSE (Root Mean Square Error) of 0.63 (r² = 0.82). The LAI thus estimated was used in the coupling of the dynamic model, allowing a general decrease of the RMSE of the order of 40% compared to the model without coupling. These results were obtained during the austral winter, the dry season. During the austral summer, the more abundant rains speed up the growth of the plants and the growth cycles become shorter. Satellite images without cloud cover are becoming scarce. Taking into account this combination of factors that may impact predictions of forage biomass will be one of the main perspectives of this work.
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Cyprien Alexandre. Estimation de la biomasse fourragère des prairies : apports du couplage entre modèles dynamiques de croissance et imagerie satellitaire : exemple de La Réunion et du Kalahari. Géographie. Université de la Réunion, 2017. Français. ⟨NNT : 2017LARE0050⟩. ⟨tel-01882044⟩

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