Combining a SVAT model with landsat imagery for a ten year simulation of grassland carbon and water budget
This study investigates the use of high-spatial, low-temporal scale visible remote sensing data for calibration of a Soil-Vegetation-Atmosphere-Transfer (SVAT) model for semi-arid perennial grasslands. The SVAT model is driven by meteorological data and simulates plant growth and water budget on a daily time step. The model was combined with a canopy reflectance model to simulate shortwave radiometric temporal profiles. Landsat Thematic Mapper (TM) images obtained during a series of ten consecutive years were used to refine the model to work on a spatially-distributed basis over a semi-arid grassland watershed. Continuous simulations were used to estimate two spatially-variable initial conditions and model parameters through a calibration procedure which minimized the difference between the surface reflectance simulated by the model and measured by the TM sensor. Accuracy of model products such as daily above-ground biomass and soil moisture was assessed by comparison with field measurements. The promising results suggest that this approach could provide spatially-distributed information about vegetation and soil conditions for day-to-day grassland management.
| Main Authors: | , , , , , , , , , |
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| Format: | conference_item biblioteca |
| Language: | eng |
| Published: |
s.n.
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| Subjects: | U30 - Méthodes de recherche, U10 - Informatique, mathématiques et statistiques, F62 - Physiologie végétale - Croissance et développement, prairie, télédétection, modèle de simulation, zone semi-aride, taux de croissance, bilan hydrique, bilan radiatif, biomasse, Réflectance, 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_6963, http://aims.fao.org/aos/agrovoc/c_16130, http://aims.fao.org/aos/agrovoc/c_8311, http://aims.fao.org/aos/agrovoc/c_6420, http://aims.fao.org/aos/agrovoc/c_926, http://aims.fao.org/aos/agrovoc/c_28538, http://aims.fao.org/aos/agrovoc/c_230ab86c, http://aims.fao.org/aos/agrovoc/c_615, |
| Online Access: | http://agritrop.cirad.fr/479738/ |
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| Summary: | This study investigates the use of high-spatial, low-temporal scale visible remote sensing data for calibration of a Soil-Vegetation-Atmosphere-Transfer (SVAT) model for semi-arid perennial grasslands. The SVAT model is driven by meteorological data and simulates plant growth and water budget on a daily time step. The model was combined with a canopy reflectance model to simulate shortwave radiometric temporal profiles. Landsat Thematic Mapper (TM) images obtained during a series of ten consecutive years were used to refine the model to work on a spatially-distributed basis over a semi-arid grassland watershed. Continuous simulations were used to estimate two spatially-variable initial conditions and model parameters through a calibration procedure which minimized the difference between the surface reflectance simulated by the model and measured by the TM sensor. Accuracy of model products such as daily above-ground biomass and soil moisture was assessed by comparison with field measurements. The promising results suggest that this approach could provide spatially-distributed information about vegetation and soil conditions for day-to-day grassland management. |
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