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Assimilation of remote sensed data for improved latent and sensible heat flux prediction: a comparative synthetic study / R. Pipunic in Remote sensing of environment, vol 112 n° 4 (15/04/2008)
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Titre : Assimilation of remote sensed data for improved latent and sensible heat flux prediction: a comparative synthetic study Type de document : Article/Communication Auteurs : R. Pipunic, Auteur ; J. Walker, Auteur ; A. Western, Auteur Année de publication : 2008 Article en page(s) : pp 1295 - 1305 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] chaleur
[Termes IGN] filtre de Kalman
[Termes IGN] flux de rayonnement
[Termes IGN] humidité du sol
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle numérique de surface
[Termes IGN] SMOSRésumé : (Auteur) Predicted latent and sensible heat fluxes from Land Surface Models (LSMs) are important lower boundary conditions for numerical weather prediction. While assimilation of remotely sensed surface soil moisture is a proven approach for improving root zone soil moisture, and presumably latent (LE) and sensible (H) heat flux predictions from LSMs, limitations in model physics and over-parameterisation mean that physically realistic soil moisture in LSMs will not necessarily achieve optimal heat flux predictions. Moreover, the potential for improved LE and H predictions from the assimilation of LE and H observations has received little attention by the scientific community, and is tested here with synthetic twin experiments. A one-dimensional single column LSM was used in 3-month long experiments, with observations of LE, H, surface soil moisture and skin temperature (from which LE and H are typically derived) sampled from truth model run outputs generated with realistic data inputs. Typical measurement errors were prescribed and observation data sets separately assimilated into a degraded model run using an Ensemble Kalman Filter (EnKF) algorithm, over temporal scales representative of available remotely sensed data. Root Mean Squared Error (RMSE) between assimilation and truth model outputs across the experiment period were examined to evaluate LE, H, and root zone soil moisture and temperature retrieval. Compared to surface soil moisture assimilation as will be available from SMOS (every 3 days), assimilation of LE and/or H using a best case MODIS scenario (twice daily) achieved overall better predictions for LE and comparable H predictions, while achieving poorer soil moisture predictions. Twice daily skin temperature assimilation achieved comparable heat flux predictions to LE and/or H assimilation. Fortnightly (Landsat) assimilations of LE, H and skin temperature performed worse than 3-day moisture assimilation. While the different spatial resolutions of these remote sensing data have been ignored, the potential for LE and H assimilation to improve model predicted LE and H is clearly demonstrated. Copyright Elsevier Numéro de notice : A2008-089 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.02.038 En ligne : https://doi.org/10.1016/j.rse.2007.02.038 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29084
in Remote sensing of environment > vol 112 n° 4 (15/04/2008) . - pp 1295 - 1305[article]Assimilation of SPOT-Vegetation NDVI data into a Sahelian vegetation dynamics model / Lionel Jarlan in Remote sensing of environment, vol 112 n° 4 (15/04/2008)
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Titre : Assimilation of SPOT-Vegetation NDVI data into a Sahelian vegetation dynamics model Type de document : Article/Communication Auteurs : Lionel Jarlan, Auteur ; S. Mangiarotti, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 1381 - 1394 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] flore locale
[Termes IGN] image SPOT-Végétation
[Termes IGN] intégration de données
[Termes IGN] modèle dynamique
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] SahelRésumé : (Auteur) This paper presents a method to monitor the dynamics of herbaceous vegetation in the Sahel. The approach is based on the assimilation of Normalized Difference Vegetation Index (NDVI) data acquired by the VEGETATION instrument on board SPOT 4/5 into a simple sahelian vegetation dynamics model. The study region is located in the Gourma region of Mali. The vegetation dynamics model is coupled with a radiative transfer model (the SAIL model). First, it is checked that the coupled models allow for a realistic simulation of the seasonal and interannual variability of NDVI over three sampling sites from 1999 to 2004. The data assimilation scheme relies on a parameter identification technique based on an Evolution Strategies algorithm. The simulated above-ground herbage mass resulting from NDVI assimilation is then compared to ground measurements performed over 13 study sites during the period 1999–2004. The assimilation scheme performs well with 404 kg DM/ha of average error (n = 126 points) and a correlation coefficient of r = 0.80 (to be compared to the 463 kg DM/ha and r = 0.60 of the model performance without data assimilation). Finally, the sensitivity of the herbage mass model estimates to the quality of the meteorological forcing (rainfall and net radiation) is analyzed thanks to a stochastic approach. Copyright Elsevier Numéro de notice : A2008-093 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.02.041 En ligne : https://doi.org/10.1016/j.rse.2007.02.041 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29088
in Remote sensing of environment > vol 112 n° 4 (15/04/2008) . - pp 1381 - 1394[article]Multi-sensor model-data fusion for estimation of hydrologic and energy flux parameters / L. Renzullo in Remote sensing of environment, vol 112 n° 4 (15/04/2008)
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Titre : Multi-sensor model-data fusion for estimation of hydrologic and energy flux parameters Type de document : Article/Communication Auteurs : L. Renzullo, Auteur ; D. Barett, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 1306 - 1319 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] Australie
[Termes IGN] évapotranspiration
[Termes IGN] flux de rayonnement
[Termes IGN] fusion de données
[Termes IGN] humidité du sol
[Termes IGN] image Aqua-AMSR
[Termes IGN] image Aqua-MODIS
[Termes IGN] image multicapteur
[Termes IGN] modèle conceptuel de données
[Termes IGN] savane
[Termes IGN] température au solRésumé : (Auteur) Model-data fusion offers considerable promise in remote sensing for improved state and parameter estimation particularly when applied to multi-sensor image products. This paper demonstrates the application of a ‘multiple constraints’ model-data fusion (MCMDF) scheme to integrating AMSR-E soil moisture content (SMC) and MODIS land surface temperature (LST) data products with a coupled biophysical model of surface moisture and energy budgets for savannas of northern Australia. The focus in this paper is on the methods, difficulties and error sources encountered in developing an MCMDF scheme and enhancements for future schemes. An important aspect of the MCMDF approach emphasized here is the identification of inconsistencies between model and data, and among data sets. The MCMDF scheme was able to identify that an inconsistency existed between AMSR-E SMC and LST data when combined with the coupled SEB-MRT model. For the example presented, an optimal fit to both remote sensing data sets together resulted in an 84% increase in predicted SMC and 0.06% increase for LST relative to the fit to each data set separately. That is the model predicted on average cooler LST's (not, vert, similar 1.7 K) and wetter SMC values (not, vert, similar 0.04 g cm- 3) than the satellite image products. In this instance we found that the AMSR-E SMC data on their own were poor constraints on the model. Incorporating LST data via the MCMDF scheme ameliorated deficiencies in the SMC data and resulted in enhanced characterization of the land surface soil moisture and energy balance based on comparison with the MODIS evapotranspiration (ET) product of Mu et al. [Mu, Q., Heinsch, F.A, Zhao, M. and Running, S.W. (in press), Development of a global evapotranspiration algorithm based on MODIS and global meteorology data, Remote Sensing of Environment.]. Canopy conductance, gc, and latent heat flux, ëE, from the MODIS ET product were in good agreement with RMSEs for gc = 0.5 mm s- 1 and for ëE = 18 W m- 2, respectively. Differences were attributable to a greater canopy-to-air vapor pressure gradient in the MCMDF approach obtained from a more realistic partitioning of soil surface and canopy temperatures. Copyright Elsevier Numéro de notice : A2008-090 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.06.022 En ligne : https://doi.org/10.1016/j.rse.2007.06.022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29085
in Remote sensing of environment > vol 112 n° 4 (15/04/2008) . - pp 1306 - 1319[article]Retrieving ocean surface current by 4D variational assimilation of Sea Surface Temperature images / G. Korotaev in Remote sensing of environment, vol 112 n° 4 (15/04/2008)
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Titre : Retrieving ocean surface current by 4D variational assimilation of Sea Surface Temperature images Type de document : Article/Communication Auteurs : G. Korotaev, Auteur ; E. Huot, Auteur ; F.X. Le Dimet, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 1295 - 1305 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] champ de vitesse
[Termes IGN] courant marin
[Termes IGN] image NOAA-AVHRR
[Termes IGN] température de surface de la mer
[Termes IGN] variation
[Termes IGN] visualisation 4DRésumé : (Auteur) In this article, we propose a new method to estimate ocean mesoscale structures of the surface current velocity by processing sea surface satellite images. Assuming that the intensity level can be described by a transport–diffusion equation, the proposed approach is based on variational assimilation of image observations within a simple transport–diffusion model. This approach permits to retrieve the current velocity field from a sequence of satellite images. Results of processing synthetic data and real NOAA-AVHRR satellite images are presented and commented. Copyright Elsevier Numéro de notice : A2008-094 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.04.020 En ligne : https://doi.org/10.1016/j.rse.2007.04.020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29089
in Remote sensing of environment > vol 112 n° 4 (15/04/2008) . - pp 1295 - 1305[article]Retrieving soil temperature profile by assimilating MODIS LST products with ensemble Kalman filter / C. Huang in Remote sensing of environment, vol 112 n° 4 (15/04/2008)
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Titre : Retrieving soil temperature profile by assimilating MODIS LST products with ensemble Kalman filter Type de document : Article/Communication Auteurs : C. Huang, Auteur ; X. Li, Auteur ; L. Lu, Auteur Année de publication : 2008 Article en page(s) : pp 1320 - 1336 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] chaleur terrestre
[Termes IGN] filtre de Kalman
[Termes IGN] image Aqua-MODIS
[Termes IGN] mise à jour automatique
[Termes IGN] Mongolie
[Termes IGN] prédiction
[Termes IGN] température au solRésumé : (Auteur) Proper estimation of initial state variables and model parameters are vital importance for determining the accuracy of numerical model prediction. In this work, we develop a one-dimensional land data assimilation scheme based on ensemble Kalman filter and Common Land Model version 3.0 (CoLM). This scheme is used to improve the estimation of soil temperature profile. The leaf area index (LAI) is also updated dynamically by MODIS LAI production and the MODIS land surface temperature (LST) products are assimilated into CoLM. The scheme was tested and validated by observations from four automatic weather stations (BTS, DRS, MGS, and DGS) in Mongolian Reference Site of CEOP during the period of October 1, 2002 to September 30, 2003. Results indicate that data assimilation improves the estimation of soil temperature profile about 1 K. In comparison with simulation, the assimilation results of soil heat fluxes also have much improvement about 13 W m- 2 at BTS and DGS and 2 W m- 2 at DRS and MGS, respectively. In addition, assimilation of MODIS land products into land surface model is a practical and effective way to improve the estimation of land surface variables and fluxes. Copyright Elsevier Numéro de notice : A2008-091 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.03.028 En ligne : https://doi.org/10.1016/j.rse.2007.03.028 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29086
in Remote sensing of environment > vol 112 n° 4 (15/04/2008) . - pp 1320 - 1336[article]Use of a Kalman filter for the retrieval of surface BRDF coefficients with a time-evolving model based on the ECOCLIMAP land cover classification / O. Samain in Remote sensing of environment, vol 112 n° 4 (15/04/2008)
PermalinkArtificial immune-based supervised classifier for land-cover classification / M. Pal in International Journal of Remote Sensing IJRS, vol 29 n° 7 (April 2008)
PermalinkASTER DEMs for geomatic and geoscientific applications: a review / Thierry Toutin in International Journal of Remote Sensing IJRS, vol 29 n° 7 (April 2008)
PermalinkEffects of spatial resolution ratio in image fusion / Y. Ling in International Journal of Remote Sensing IJRS, vol 29 n° 7 (April 2008)
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PermalinkReducing edge effects in the classification of high resolution imagery / Guiyun Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 4 (April 2008)
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PermalinkThe early explanatory power of NDVI in crop yield modelling / L. Wall in International Journal of Remote Sensing IJRS, vol 29 n° 7 (April 2008)
PermalinkVers la prochaine génération de bases de données et de cartes / Françoise de Blomac in SIG la lettre, n° 96 (avril 2008)
PermalinkTwo-scale surface deformation analysis using the SBAS-DInSAR technique: a case study of the city of Rome, Italy / M. Manunta in International Journal of Remote Sensing IJRS, vol 29 n° 6 (March 2008)
PermalinkMapping the height and above-ground biomass of a mixed forest using lidar and stereo Ikonos images / Benoît Saint-Onge in International Journal of Remote Sensing IJRS, vol 29 n° 5 (March 2008)
PermalinkAnalyse spatio-temporelle de l'occupation du sol dans le parc national de Waza entre 1986 et 2001 (Nord Cameroun) / G. Wafo Tabopda in Revue Française de Photogrammétrie et de Télédétection, n° 189 (Mars 2008)
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PermalinkIntérêt des images radar ERS pour la géologie en Afrique tropicale : application à la cartographie lithostructurale dans la région de Ferkessédougou / B.G. Koffi in Photo interprétation, vol 44 n° 1 (Mars 2008)
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PermalinkLarge-scale errors in ERS altimeter data / J.Y. Cherniawsky in Marine geodesy, vol 31 n° 1 (March - May 2008)
PermalinkPotential of Cartosat-1 images for topographic mapping / Costas Armenakis in Geomatica, vol 62 n° 1 (March 2008)
PermalinkA robust biased estimator for exterior orientation of linear array pushbroom satellite imagery / Y. Zhang in Geomatica, vol 62 n° 1 (March 2008)
PermalinkTexture feature fusion with neighborhood oscillating tabu search for high resolution image classification / L. Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 3 (March 2008)
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