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.

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Bibliographic Details
Main Authors: Nouvellon, Yann, Moran, M. Susan, Bryant, Ross, Ni, Wanmei, Heilman, Phil, Emmerich, B., Lo Seen, Danny, Bégué, Agnès, Rambal, Serge, Qi, J.
Format: conference_item biblioteca
Language:eng
Published: s.n.
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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spelling dig-cirad-fr-4797382024-01-28T09:07:17Z http://agritrop.cirad.fr/479738/ http://agritrop.cirad.fr/479738/ 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. In : Second International Conference on Geospatial Information in Agriculture and Forestry, Lake Buena Vista, Florida, 10-12 January 2000. s.l. : s.n., 257-264. International Conference on Geospatial Information in Agriculture and Forestry. 2, Lake Buena Vista, États-Unis, 10 Janvier 2000/12 Janvier 2000. 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. eng 2000 s.n. Second International Conference on Geospatial Information in Agriculture and Forestry, Lake Buena Vista, Florida, 10-12 January 2000 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 Arizona http://aims.fao.org/aos/agrovoc/c_615 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. conference_item info:eu-repo/semantics/conferenceObject Conference info:eu-repo/semantics/closedAccess http://catalogue-bibliotheques.cirad.fr/cgi-bin/koha/opac-detail.pl?biblionumber=164665
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic 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
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
spellingShingle 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
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
Nouvellon, Yann
Moran, M. Susan
Bryant, Ross
Ni, Wanmei
Heilman, Phil
Emmerich, B.
Lo Seen, Danny
Bégué, Agnès
Rambal, Serge
Qi, J.
Combining a SVAT model with landsat imagery for a ten year simulation of grassland carbon and water budget
description 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.
format conference_item
topic_facet 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
author Nouvellon, Yann
Moran, M. Susan
Bryant, Ross
Ni, Wanmei
Heilman, Phil
Emmerich, B.
Lo Seen, Danny
Bégué, Agnès
Rambal, Serge
Qi, J.
author_facet Nouvellon, Yann
Moran, M. Susan
Bryant, Ross
Ni, Wanmei
Heilman, Phil
Emmerich, B.
Lo Seen, Danny
Bégué, Agnès
Rambal, Serge
Qi, J.
author_sort Nouvellon, Yann
title Combining a SVAT model with landsat imagery for a ten year simulation of grassland carbon and water budget
title_short Combining a SVAT model with landsat imagery for a ten year simulation of grassland carbon and water budget
title_full Combining a SVAT model with landsat imagery for a ten year simulation of grassland carbon and water budget
title_fullStr Combining a SVAT model with landsat imagery for a ten year simulation of grassland carbon and water budget
title_full_unstemmed Combining a SVAT model with landsat imagery for a ten year simulation of grassland carbon and water budget
title_sort combining a svat model with landsat imagery for a ten year simulation of grassland carbon and water budget
publisher s.n.
url http://agritrop.cirad.fr/479738/
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