Combining a SVAT model with landsat imagery for a ten year simulation of grassland carbon and water budget

Nouvellon Yann, Moran M. Susan, Bryant Ross, Ni Wanmei, Heilman Phil, Emmerich B., Lo Seen Danny, Bégué Agnès, Rambal Serge, Qi J.. 2000. Combining a SVAT model with landsat imagery for a ten year simulation of grassland carbon and water budget. In : Second International Conference on Geospatial Information in Agriculture and Forestry, Lake Buena Vista, Florida, 10-12 January 2000. s.l. : s.n., pp. 257-264. International Conference on Geospatial Information in Agriculture and Forestry. 2, Lake Buena Vista, États-Unis, 10 January 2000/12 January 2000.

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Autre titre : La combinaison d'un modèle de transfert sol-végétation-atmosphère (SVAT) avec l'imagerie Landsat pour la simulation sur dix ans du budget carboné et hydrique d'une prairie

Abstract : 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. (Résumé d'auteur)

Mots-clés Agrovoc : Prairie, Télédétection, Modèle de simulation, Zone semi-aride, Taux de croissance, Bilan hydrique, Bilan radiatif, Biomasse, Réflectance, Modélisation

Mots-clés géographiques Agrovoc : Arizona

Classification Agris : U30 - Research methods
U10 - Computer science, mathematics and statistics
F62 - Plant physiology - Growth and development

Auteurs et affiliations

  • Moran M. Susan, USDA (USA)
  • Bryant Ross, USDA (USA)
  • Ni Wanmei, USDA (USA)
  • Heilman Phil, USDA (USA)
  • Emmerich B., USDA (USA)
  • Lo Seen Danny, CIRAD-AMIS-AGRONOMIE (FRA) ORCID: 0000-0002-7773-2109
  • Rambal Serge, CNRS (FRA)
  • Qi J., MSU (USA)

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