Combining remote sensing and plant growth modeling to describe the carbon and water budget of semi-arid grasslands
In this paper we investigate the opportunity of coupling a vegetation growth model developed for semi-arid perennial grasslands, with a soil/vegetation reflectance model in order to use remote sensing data to improve the model simulations. The vegetation functioning model developed for this purpose has been validated in Southeastern Arizona and Northeastern Sonora on several semiarid grassland sites. The assimilation of radiometric data into the shortgrass prairie ecosystem model is based on an iterative numerical procedure that recalibrates the combined model until model simulations match radiometric observations. For this purpose, a prior sensivity analysis was carried out for the vegetation growth model in order to determine the most important input parameters or initial conditions on which to base the recalibration procedure. The results obtained and the potentiel of such an approach are discussed.
| Main Authors: | , , , , , , , |
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| Format: | conference_item biblioteca |
| Language: | eng |
| Published: |
IEEE
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| Subjects: | U30 - Méthodes de recherche, U10 - Informatique, mathématiques et statistiques, F60 - Physiologie et biochimie végétale, prairie, télédétection, modèle de simulation, croissance, bilan hydrique, matière organique du sol, bilan radiatif, productivité primaire, modélisation, http://aims.fao.org/aos/agrovoc/c_6154, http://aims.fao.org/aos/agrovoc/c_6498, http://aims.fao.org/aos/agrovoc/c_24242, http://aims.fao.org/aos/agrovoc/c_3394, http://aims.fao.org/aos/agrovoc/c_8311, http://aims.fao.org/aos/agrovoc/c_35657, http://aims.fao.org/aos/agrovoc/c_6420, http://aims.fao.org/aos/agrovoc/c_34328, http://aims.fao.org/aos/agrovoc/c_230ab86c, http://aims.fao.org/aos/agrovoc/c_615, http://aims.fao.org/aos/agrovoc/c_7238, |
| Online Access: | http://agritrop.cirad.fr/390377/ |
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| Summary: | In this paper we investigate the opportunity of coupling a vegetation growth model developed for semi-arid perennial grasslands, with a soil/vegetation reflectance model in order to use remote sensing data to improve the model simulations. The vegetation functioning model developed for this purpose has been validated in Southeastern Arizona and Northeastern Sonora on several semiarid grassland sites. The assimilation of radiometric data into the shortgrass prairie ecosystem model is based on an iterative numerical procedure that recalibrates the combined model until model simulations match radiometric observations. For this purpose, a prior sensivity analysis was carried out for the vegetation growth model in order to determine the most important input parameters or initial conditions on which to base the recalibration procedure. The results obtained and the potentiel of such an approach are discussed. |
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