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Evaluation of seasonal variations of remotely sensed leaf area index over five evergreen coniferous forests / Rong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 130 (August 2017) . - pp 187 - 201 Titre : Evaluation of seasonal variations of remotely sensed leaf area index over five evergreen coniferous forests Type de document : Article/Communication Auteurs : Rong Wang, Auteur ; Jing M. Chen, Auteur ; Zhili Liu, Auteur ; Altaf Arain, Auteur Année de publication : 2017 Article en page(s) : pp 187 - 201 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] aiguille [Termes IGN] atmosphère terrestre [Termes IGN] image Envisat-MERIS [Termes IGN] indice foliaire [Termes IGN] Leaf Area Index [Termes IGN] phénologie [Termes IGN] Pinophyta [Termes IGN] placette d'échantillonnage [Termes IGN] surface du sol [Termes IGN] surveillance forestière [Termes IGN] teneur en chlorophylle des feuilles [Termes IGN] Tracing Radiation and Architecture of Canopies [Termes IGN] variation saisonnière Résumé : (Auteur) Seasonal variations of leaf area index (LAI) have crucial controls on the interactions between the land surface and the atmosphere. Over the past decades, a number of remote sensing (RS) LAI products have been developed at both global and regional scales for various applications. These products are so far only validated using ground LAI data acquired mostly in the middle of the growing season. The accuracy of the seasonal LAI variation in these products remains unknown and there are few ground data available for this purpose. We performed regular LAI measurements over a whole year at five coniferous sites using two methods: (1) an optical method with LAI-2000 and TRAC; (2) a direct method through needle elongation monitoring and litterfall collection. We compared seasonal trajectory of LAI from remote sensing (RS LAI) with that from a direct method (direct LAI). RS LAI agrees very well with direct LAI from the onset of needle growth to the seasonal peak (R2 = 0.94, RMSE = 0.44), whereas RS LAI declines earlier and faster than direct LAI from the seasonal peak to the completion of needle fall. To investigate the possible reasons for the discrepancy, the MERIS Terrestrial Chlorophyll Index (MTCI) was compared with RS LAI. Meanwhile, phenological metrics, i.e. the start of growing season (SOS) and the end of growing season (EOS), were extracted from direct LAI, RS LAI and MTCI time series. SOS from RS LAI is later than that from direct LAI by 9.3 ± 4.0 days but earlier than that from MTCI by 2.6 ± 1.9 days. On the contrary, for EOS, RS LAI is later than MTCI by 3.3 ± 8.4 days and much earlier than direct LAI by 30.8 ± 7.2 days. Our results suggest that the seasonal trajectory of RS LAI well captures canopy structural information from the onset of needle growth to the seasonal peak, but is greatly influenced by the decrease in leaf chlorophyll content, as indicated by MTCI, from the seasonal peak to the completion of needle fall. These findings have significant implications for improving existing RS LAI products and terrestrial productivity modeling. Numéro de notice : A2017-514 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.05.017 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.05.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86475 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2017081	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2017083	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2017082	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Improving winter leaf area index estimation in coniferous forests and its significance in estimating the land surface albedo / Rong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 32 - 48 Titre : Improving winter leaf area index estimation in coniferous forests and its significance in estimating the land surface albedo Type de document : Article/Communication Auteurs : Rong Wang, Auteur ; Jing M. Chen, Auteur ; Goran Pavlic, Auteur ; Altaf Arain, Auteur Année de publication : 2016 Article en page(s) : pp 32 - 48 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] albedo [Termes IGN] hiver [Termes IGN] Leaf Area Index [Termes IGN] luninosité [Termes IGN] photo-interprétation [Termes IGN] Pinophyta Résumé : (Auteur) Winter leaf area index (LAI) of evergreen coniferous forests exerts strong control on the interception of snow, snowmelt and energy balance. Simulation of winter LAI and associated winter processes in land surface models is challenging. Retrieving winter LAI from remote sensing data is difficult due to cloud contamination, poor illumination, lower solar elevation and higher radiation reflection by snow background. Underestimated winter LAI in evergreen coniferous forests is one of the major issues limiting the application of current remote sensing LAI products. It has not been fully addressed in past studies in the literature. In this study, we used needle lifespan to correct winter LAI in a remote sensing product developed by the University of Toronto. For the validation purpose, the corrected winter LAI was then used to calculate land surface albedo at five FLUXNET coniferous forests in Canada. The RMSE and bias values for estimated albedo were 0.05 and 0.011, respectively, for all sites. The albedo map over coniferous forests across Canada produced with corrected winter LAI showed much better agreement with the GLASS (Global LAnd Surface Satellites) albedo product than the one produced with uncorrected winter LAI. The results revealed that the corrected winter LAI yielded much greater accuracy in simulating land surface albedo, making the new LAI product an improvement over the original one. Our study will help to increase the usability of remote sensing LAI products in land surface energy budget modeling. Numéro de notice : A2016-777 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.05.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.05.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82472 [article]

Evaluating leaf chlorophyll content prediction from multispectral remote sensing data within a physically-based modelling framework / H. Croft in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 85 - 95 Titre : Evaluating leaf chlorophyll content prediction from multispectral remote sensing data within a physically-based modelling framework Type de document : Article/Communication Auteurs : H. Croft, Auteur ; Jing M. Chen, Auteur ; Y. Zhang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 85 - 95 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Acer saccharum [Termes IGN] aiguille [Termes IGN] image Landsat-TM [Termes IGN] indice de stress [Termes IGN] Leaf Area Index [Termes IGN] modèle de transfert radiatif [Termes IGN] Picea mariana [Termes IGN] Pinus banksiana [Termes IGN] Populus tremuloides [Termes IGN] réflectance végétale [Termes IGN] surveillance forestière [Termes IGN] teneur en chlorophylle des feuilles Résumé : (auteur) Accurate modelling of leaf chlorophyll content over a range of spatial and temporal scales is central to monitoring vegetation stress and physiological condition, and vegetation response to different ecological, climatic and anthropogenic drivers. A process-based modelling approach can account for variation in other factors affecting canopy reflectance, providing a more accurate estimate of chlorophyll content across different vegetation species, time-frames, and broader spatial extents. However, physically-based modelling studies usually use hyperspectral data, neglecting a wealth of data from broadband and multispectral sources. In this study, we assessed the potential for using canopy (4-Scale) and leaf radiative transfer (PROSPECT4/5) models to estimate leaf chlorophyll content using canopy Landsat satellite data and simulated Landsat bands from leaf level hyperspectral reflectance data. Over 600 leaf samples were used to test the performance of PROSPECT for different vegetation species, including black spruce (Picea mariana), sugar maple (Acer saccharum), trembling aspen (Populus tremuloides) and jack pine (Pinus banksiana). At the leaf level, hyperspectral and simulated Landsat bands showed very similar results to laboratory measured chlorophyll (R2 = 0.77 and R2 = 0.75, respectively). Comparisons between PROSPECT4 modelled chlorophyll from simulated Landsat and hyperspectral spectra showed a very close correspondence (R2 = 0.97, root mean square error (RMSE) = 3.01 μg/cm2), as did simulated reflectance bands from other broadband and narrowband sensors (MODIS: R2 = 0.99, RMSE = 1.80 μg/cm2; MERIS: R2 = 0.97, RMSE = 2.50 μg/cm2 and SPOT5 HRG: R2 = 0.96, RMSE = 5.38 μg/cm2). Modelled leaf chlorophyll content from Landsat 5 TM canopy reflectance data, acquired from over 40 ground validation sites, demonstrated a strong relationship with measured leaf chlorophyll content (R2 = 0.78, RMSE = 8.73 μg/cm2, p Numéro de notice : A2015-691 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.01.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.01.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78326 [article]

Hybrid geometric optical–radiative transfer model suitable for forests on slopes / Weiliang Fan in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 52 n° 9 Tome 1 (September 2014) . - pp 5579 - 5586 Titre : Hybrid geometric optical–radiative transfer model suitable for forests on slopes Type de document : Article/Communication Auteurs : Weiliang Fan, Auteur ; Jing M. Chen, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 5579 - 5586 Note générale : Bibliographie Langues : Anglais (eng) Résumé : (Auteur) A new geometric optical (GO)-radiative transfer (RT) model with a multiple scattering scheme suitable for sloping forest canopies is developed in this study. It is based on a Geometrical-Optical model for Sloping Terrains and an RT method. This new model overcomes the difficulty to prescribe bidirectional reflectance factors (BRFs) of shaded components (shaded foliage and background) in GO modeling through simulating radiation multiple scattering within a sloping forest. A case study shows that multiply scattered radiation depends on topographic factors and leaf area index. The contributions of the shaded components to stand-level BRF are less than 3% in the red band and can reach up to 40% in the near-infrared (NIR) band. The “multiangle” Moderate Resolution Imaging Spectroradiometer (MODIS) data over sloping pixels are selected to validate the modeled forest BRF. Considering the multiple scattering schemes and topographic factors, the modeled BRF is closer to the MODIS surface reflectance (BRF product) (red band: R2 = 0.8614, rRMSE = 0.1339; NIR band: R2 = 0.7573, rRMSE = 0.0850) than the modeled BRF (red band: R2 = 0.7771, rRMSE=0.1839; NIR band: R2 =0.5176, rRMSE = 0.1155) without topographic consideration. It is also shown that the MODIS surface reflectance of sloping forests at multiple angles can be simulated well using the newly developed model. Numéro de notice : A2014-441 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2290590 En ligne : https://doi.org/10.1109/TGRS.2013.2290590 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73978 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2014091A	RAB	Revue	Centre de documentation	En réserve L003	Disponible

The potential of the greenness and radiation (GR) model to interpret 8-day gross primary production of vegetation / Chaoyang Wu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 88 (February 2014) . - pp 69 - 79 Titre : The potential of the greenness and radiation (GR) model to interpret 8-day gross primary production of vegetation Type de document : Article/Communication Auteurs : Chaoyang Wu, Auteur ; Alemu Gonsamo, Auteur ; Fangmin Zhang, Auteur ; Jing M. Chen, Auteur Année de publication : 2014 Article en page(s) : pp 69 - 79 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] arbre sempervirent [Termes IGN] bilan du carbone [Termes IGN] croissance des arbres [Termes IGN] écosystème forestier [Termes IGN] Enhanced vegetation index [Termes IGN] forêt de feuillus [Termes IGN] indice de végétation [Termes IGN] production primaire brute [Termes IGN] température au sol Résumé : (Auteur) Remote sensing of vegetation gross primary production (GPP) is an important step to analyze terrestrial carbon (C) cycles in response to changing climate. The availability of global networks of C flux measurements provides a valuable opportunity to develop remote sensing based GPP algorithms and test their performances across diverse regions and plant functional types (PFTs). Using 70 global C flux measurements including 24 non-forest (NF), 17 deciduous forest (DF) and 29 evergreen forest (EF), we present the evaluation of an upscaled remote sensing based greenness and radiation (GR) model for GPP estimation. This model is developed using enhanced vegetation index (EVI) and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and global course resolution radiation data from the National Center for Environmental Prediction (NCEP). Model calibration was achieved using statistical parameters of both EVI and LST fitted for different PFTs. Our results indicate that compared to the standard MODIS GPP product, the calibrated GR model improved the GPP accuracy by reducing the root mean square errors (RMSE) by 16%, 30% and 11% for the NF, DF and EF sites, respectively. The standard MODIS and GR model intercomparisons at individual sites for GPP estimation also showed that GR model performs better in terms of model accuracy and stability. This evaluation demonstrates the potential use of the GR model in capturing short-term GPP variations in areas lacking ground measurements for most of vegetated ecosystems globally. Numéro de notice : A2014-085 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32990 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2014021	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Spectral response function comparability among 21 satellite sensors for vegetation monitoring / Alemu Gonsamo in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 1 (March 2013)  

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Comparison and validation of MODIS and VEGETATION global LAI products over four BigFoot sites in North America / J. Pisek in Remote sensing of environment, vol 109 n° 1 (12 July 2007)  

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