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Optimization of multi-ecosystem model ensembles to simulate vegetation growth at the global scale / Linling Tang in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)
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[article]
Titre : Optimization of multi-ecosystem model ensembles to simulate vegetation growth at the global scale Type de document : Article/Communication Auteurs : Linling Tang, Auteur ; Qian Lei, Auteur ; Weizhe Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 962 - 978 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] croissance végétale
[Termes descripteurs IGN] écosystème
[Termes descripteurs IGN] estimation bayesienne
[Termes descripteurs IGN] Leaf Area Index
[Termes descripteurs IGN] modèle de simulation
[Termes descripteurs IGN] optimisation (mathématiques)
[Termes descripteurs IGN] optimisation par essaim de particulesRésumé : (auteur) Process-based ecosystem models are increasingly used to simulate the effects of a changing environment on vegetation growth in the past, present, and future. To improve the simulation, the multimodel ensemble mean (MME) and ensemble Bayesian model averaging (EBMA) methods are often used in optimizing the integration of ecosystem model ensemble. These two methods were compared with four other optimization techniques, including genetic algorithm (GA), particle swarm optimization (PSO), cuckoo search (CS), and interior-point method (IPM), to evaluate their efficiency in this article. Here, we focused on eight commonly used ecosystem models to simulate vegetation growth, represented by the growing season leaf area index (LAIgs), collected globally from 2000 to 2014. The performances of the multimodel ensembles and individual models were compared using the satellite-observed LAI products as the reference. Generally, ensemble simulations provide more accurate estimates than individual models. There were significant performance differences among the six tested methods. The IPM ensemble model simulated LAIgs more accurately than the other tested models, as the reduction in the root-mean-square error was 84.99% higher than the MME results and 61.50% higher than the EBMA results. Thus, IPM optimization can reproduce LAIgs trends accurately for 91.62% of the global vegetated area, which is double the area of the results from MME. Furthermore, the contributions and uncertainties of the individual models in the final simulated IPM LAIgs changes indicated that the best individual model (CABLE) showed the greatest area fraction for the maximum IPM weight (32.49%), especially in the low-lalitude to midlatitude areas. Numéro de notice : A2021-111 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.12.014 date de publication en ligne : 03/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.12.014 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96913
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 2 (February 2021) . - pp 962 - 978[article]Polarization of light reflected by grass: modeling using visible-sunlit areas / Bin Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 12 (December 2020)
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Titre : Polarization of light reflected by grass: modeling using visible-sunlit areas Type de document : Article/Communication Auteurs : Bin Yang, Auteur ; Lei Yan, Auteur ; Siyuan Liu, Auteur Année de publication : 2020 Article en page(s) : pp 745 - 752 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes descripteurs IGN] aérosol
[Termes descripteurs IGN] canopée
[Termes descripteurs IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes descripteurs IGN] ensoleillement
[Termes descripteurs IGN] image POLDER
[Termes descripteurs IGN] image Terra-MODIS
[Termes descripteurs IGN] Leaf Area Index
[Termes descripteurs IGN] polarisation
[Termes descripteurs IGN] réflectance de surface
[Termes descripteurs IGN] réflectance végétaleRésumé : (Auteur) The Bidirectional polarization distribution function (BPDF) of land surfaces is important for studies of land surfaces and aerosol. With the availability of a huge number of polarization measurements, several semi-empirical BPDF models have been proposed. However, these models do not pay much attention to canopy structure, which is fundamental for generation of polarization. In this article, we propose a new BPDF model using canopy structure information, which is parameterized by visible-sunlit areas. It is evaluated over grassland using POLDER BPDF and MODIS leaf area index data sets. Experiments suggest that compared to Nadal–Bréon and Litvinov models, the new BPDF model reduces root-mean-square error by 7% and 10%, respectively. The new BPDF model also provides better performance when it is fitted using observations clustered by sun zenith angle. The new BPDF model thus provides an effective tool for the study of land surface polarization. Numéro de notice : A2020-763 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.12.745 date de publication en ligne : 01/12/2020 En ligne : https://doi.org/10.14358/PERS.86.12.745 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96552
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 12 (December 2020) . - pp 745 - 752[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2020121 SL Revue Centre de documentation Revues en salle Disponible Quantification of cotton water consumption by remote sensing / Jefferson Vieira José in Geocarto international, vol 35 n° 16 ([01/12/2020])
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Titre : Quantification of cotton water consumption by remote sensing Type de document : Article/Communication Auteurs : Jefferson Vieira José, Auteur ; Niclene Ponce Rodrigues de Oliveira, Auteur ; Tonny José de Araújo da Silva, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1800 - 1813 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes descripteurs IGN] biome
[Termes descripteurs IGN] cultures irriguées
[Termes descripteurs IGN] évapotranspiration
[Termes descripteurs IGN] gestion de l'eau
[Termes descripteurs IGN] Gossypium (genre)
[Termes descripteurs IGN] image thermique
[Termes descripteurs IGN] irrigation
[Termes descripteurs IGN] Leaf Area Index
[Termes descripteurs IGN] Mato Grosso
[Termes descripteurs IGN] SEBAL (algorithme)Résumé : (auteur) Quantifying crop water consumption is essential for water resource management. The objective was to estimate the current evapotranspiration (ETa) of the cotton crop (Gossypium hirsutum L.) in the rainfed system, as well as the components of the radiation and energy balance in the Cerrado biome conditions using orbital images and the SEBAL algorithm and validate the estimates of evapotranspiration (ET) using FAO guidelines for crop coefficient (K c) of the cotton crop. Research was carried out in the State of Mato Grosso, Brazil, in areas with three cotton cultivars. Images of the Operational Land Imager and Thermal Infrared Sensor sensors were used and ET estimation was made based on the SEBAL algorithm. Mean ETa in the cotton cycle was 3.5 mm dia−1 and the K c values ranged from 0.22 and 1.12, on average, in the smaller and larger leaf area, respectively. Numéro de notice : A2020-726 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1583777 date de publication en ligne : 18/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1583777 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96329
in Geocarto international > vol 35 n° 16 [01/12/2020] . - pp 1800 - 1813[article]Bistatic specular scattering measurements for the estimation of rice crop growth variables using fuzzy inference system at X-, C-, and L-bands / Ajeet Kumar Vishwakarma in Geocarto international, vol 35 n° 13 ([01/10/2020])
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Titre : Bistatic specular scattering measurements for the estimation of rice crop growth variables using fuzzy inference system at X-, C-, and L-bands Type de document : Article/Communication Auteurs : Ajeet Kumar Vishwakarma, Auteur ; Rajendra Prasad, Auteur Année de publication : 2020 Article en page(s) : pp 1433 - 1449 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] bande C
[Termes descripteurs IGN] bande L
[Termes descripteurs IGN] bande X
[Termes descripteurs IGN] biomasse
[Termes descripteurs IGN] indice foliaire
[Termes descripteurs IGN] Inférence floue
[Termes descripteurs IGN] Leaf Area Index
[Termes descripteurs IGN] Oryza (genre)
[Termes descripteurs IGN] polarisation
[Termes descripteurs IGN] radar bistatique
[Termes descripteurs IGN] teneur en eau de la végétationRésumé : (auteur) Bistatic scatterometer measurements were performed on the rice crop-bed in the angular range of 20° to 60° for specular direction (ϕ=0) at X-, C- and L-bands for HH-, VV-, and HV-polarizations. The dominant scattering contribution to bistatic specular scattering coefficients (σ0) was analysed with the crop growth stages at various angle of incidence. The regression analysis showed high correlation between σ0 and crop growth variables at 40° angle of incidence for HH-polarization at X-band and for VV-polarization at C- and L-bands. The estimation of rice crop growth variables using subtractive clustering based fuzzy inference system (S-FIS) was done at 40° angle of incidence. The lower values of computed root mean square error (RMSE) between the observed and estimated values showed high potential of developed S-FIS model for the estimation of leaf area index for HH-polarisation at X-band, vegetation water content and fresh biomass for VV-polarization at C- and L-bands, respectively. Numéro de notice : A2020-608 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1576777 date de publication en ligne : 18/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1576777 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95969
in Geocarto international > vol 35 n° 13 [01/10/2020] . - pp 1433 - 1449[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2020101 SL Revue Centre de documentation Revues en salle Disponible Comparative analysis of index and chemometric techniques-based assessment of leaf area index (LAI) in wheat through field spectroradiometer, Landsat-8, Sentinel-2 and Hyperion bands / Bappa Das in Geocarto international, vol 35 n° 13 ([01/10/2020])
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Titre : Comparative analysis of index and chemometric techniques-based assessment of leaf area index (LAI) in wheat through field spectroradiometer, Landsat-8, Sentinel-2 and Hyperion bands Type de document : Article/Communication Auteurs : Bappa Das, Auteur ; Rabi N. Sahoo, Auteur ; Sourabh Pargal, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1415 - 1432 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] analyse comparative
[Termes descripteurs IGN] blé (céréale)
[Termes descripteurs IGN] canopée
[Termes descripteurs IGN] image EO1-Hyperion
[Termes descripteurs IGN] image hyperspectrale
[Termes descripteurs IGN] image Landsat-8
[Termes descripteurs IGN] image Sentinel-MSI
[Termes descripteurs IGN] indice de végétation
[Termes descripteurs IGN] Leaf Area Index
[Termes descripteurs IGN] modèle de régression
[Termes descripteurs IGN] réflectance spectrale
[Termes descripteurs IGN] régression des moindres carrés partiels
[Termes descripteurs IGN] séparateur à vaste marge
[Termes descripteurs IGN] spectroradiomètreRésumé : (auteur) Successful retrieval of leaf area index (LAI) from hyperspectral remote sensing relies on the proper selection of indices or multivariate models. The objectives of the research work were to identify best vegetation index and multivariate model based on canopy reflectance and LAI measured at different growth stages of wheat. Comparison of existing indices revealed optimized soil-adjusted vegetation index (OSAVI) as the best index based on R2 of calibration, validation and root mean square error of validation. Proposed ratio index (RI; R670, R845) and normalized difference index (NDI; R670, R845) provided comparable performance with the existing vegetation indices (R2 = 0.65 and 0.62 for RI and NDI, respectively, during validation). Among the multivariate models, partial least squares regression (PLSR) model with Hyperion band configuration performed the best during validation (R2 = 0.80 and RMSE = 0.58 m2 m−2). Our results manifested the opportunities for developing biophysical products based on satellite sensors. Numéro de notice : A2020-607 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1581271 date de publication en ligne : 28/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1581271 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95967
in Geocarto international > vol 35 n° 13 [01/10/2020] . - pp 1415 - 1432[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2020101 SL Revue Centre de documentation Revues en salle Disponible Ground-based remote sensing of forests exploiting GNSS signals / Leila Guerriero in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)
PermalinkTowards a semi-automated mapping of Australia native invasive alien Acacia trees using Sentinel-2 and radiative transfer models in South Africa / Cecilia Masemola in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)
PermalinkPath length correction for improving leaf area index measurements over sloping terrains: A deep analysis through computer simulation / Gaofei Yin in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)
PermalinkUnsupervised semantic and instance segmentation of forest point clouds / Di Wang in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)
PermalinkWheat leaf area index retrieval using RISAT-1 hybrid polarized SAR data / Thota Sivasankar in Geocarto international, Vol 35 n° 8 ([01/06/2020])
PermalinkYear-to-year crown condition poorly contributes to ring width variations of beech trees in French ICP level I network / Clara Tallieu in Forest ecology and management, Vol 465 (1st June 2020)
PermalinkModeling strawberry biomass and leaf area using object-based analysis of high-resolution images / Zhen Guan in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)
PermalinkTemporal Validation of Four LAI Products over Grasslands in the Northeastern Tibetan Plateau / Gaofei Yin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 4 (April 2020)
PermalinkRed-edge band vegetation indices for leaf area index estimation from Sentinel-2/MSI imagery / Yuanheng Sun in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)
PermalinkThe effects of different combinations of simulated climate change-related stressors on juveniles of seven forest tree species grown as mono-species and mixed cultures / Alfas Pliüra in Baltic forestry, vol 26 n° 1 (2020)
PermalinkCombination of linear regression lines to understand the response of Sentinel-1 dual polarization SAR data with crop phenology - case study in Miyazaki, Japan / Emal Wali in Remote sensing, vol 12 n° 1 (January 2020)
PermalinkAccurate modelling of canopy traits from seasonal Sentinel-2 imagery based on the vertical distribution of leaf traits / Tawanda W. Gara in ISPRS Journal of photogrammetry and remote sensing, vol 157 (November 2019)
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PermalinkMonitoring the structure of forest restoration plantations with a drone-lidar system / D.R.A. Almeida in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)
PermalinkUsing LiDAR-modified topographic wetness index, terrain attributes with leaf area index to improve a single-tree growth model in south-eastern Finland / Cheikh Mohamedou in Forestry, an international journal of forest research, vol 92 n° 3 (July 2019)
PermalinkThe process-based forest growth model 3-PG for use in forest management : A review / Rajit Gupta in Ecological modelling, vol 397 (1 April 2019)
PermalinkFeasibility study of vegetation indices derived from Sentinel-2 and PlanetScope satellite images for validating the LAI biophysical parameter to monitoring development stages of winter wheat / Radoslaw Gurdak in Geoinformation issues, Vol 10 n°1 (2018)
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Permalink3D radiative transfer modeling over complex vegetation canopies and forest reconstruction from LIDAR measurements / Jianbo Qi (2019)
PermalinkAssessment of different vegetation parameters for parameterizing the coupled water cloud model and advanced integral equation model for soil moisture retrieval using time series Sentinel-1A data / Long Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)
PermalinkEstimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data / P. Kumar in Geocarto international, vol 33 n° 9 (September 2018)
PermalinkICARE-VEG: A 3D physics-based atmospheric correction method for tree shadows in urban areas / Karine R.M. Adeline in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)
PermalinkExtracting leaf area index using viewing geometry effects : A new perspective on high-resolution unmanned aerial system photography / Lukas Roth in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)
PermalinkRemote estimation of canopy leaf area index and chlorophyll content in Moso bamboo (Phyllostachys edulis (Carrière) J. Houz.) forest using MODIS reflectance data / Xiaojun Xu in Annals of Forest Science [en ligne], vol 75 n° 1 (March 2018)
PermalinkEstimation cohérente de l'indice de surface foliaire en utilisant des données terrestres et aéroportées / Ronghai Hu (2018)
PermalinkA hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning / Rasmus M. Houborg in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)
PermalinkPermalinkPermalinkHyperspectral dimensionality reduction for biophysical variable statistical retrieval / Juan Pablo Rivera-Caicedo in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)
PermalinkImproving the prediction of African savanna vegetation variables using time series of MODIS products / Miriam Tsalyuk in ISPRS Journal of photogrammetry and remote sensing, vol 131 (September 2017)
PermalinkSpatiotemporal analyses of urban vegetation structural attributes using multitemporal Landsat TM data and field measurements / Zhibin Ren in Annals of Forest Science [en ligne], vol 74 n° 3 (September 2017)
PermalinkEvaluation 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)
PermalinkSimultaneous estimation of leaf area index, fraction of absorbed photosynthetically active radiation, and surface albedo from multiple-satellite data / Han Ma in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)
PermalinkApplication of 3D triangulations of airborne laser scanning data to estimate boreal forest leaf area index / Titta Majasalmi in International journal of applied Earth observation and geoinformation, vol 59 (July 2017)
PermalinkTélédétection pour l'observation des surfaces continentales, Volume 3. Observation des surfaces continentales par télédétection 1 / Nicolas Baghdadi (2017)
PermalinkCHP toolkit : case study of LAIe sensitivity to discontinuity of canopy cover in fruit plantations / Karolina D. Fieber in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
PermalinkEstimating the solar transmittance of urban trees using airborne LiDAR and radiative transfer simulation / Haruki Oshio in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
PermalinkImproving 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)
PermalinkRetrieval of leaf area index in different plant species using thermal hyperspectral data / Elnaz Neinavaz in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
PermalinkTracking the seasonal dynamics of boreal forest photosynthesis using EO-1 hyperion reflectance : sensitivity to structural and illumination effects / Rocío Hernández-Clemente in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
PermalinkScale effect in indirect measurement of leaf area index / Guangjian Yan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)
PermalinkForest above ground biomass inversion by fusing GLAS with optical remote sensing data / Xiaohuan Xi in ISPRS International journal of geo-information, vol 5 n° 4 (April 2016)
PermalinkAssessing the contribution of woody materials to forest angular gap fraction and effective leaf area index using terrestrial laser scanning data / Guang Zheng in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)
PermalinkImproved salient feature-based approach for automatically separating photosynthetic and nonphotosynthetic components within terrestrial Lidar point cloud data of forest canopies / Lixia Ma in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)
PermalinkMangrove forest characterization in Southeast Côte d’Ivoire / Isimemen Osemwegie in Open journal of forestry, vol 6 n° 3 (February 2016)
PermalinkEffects of water and heat on growth of winter wheat in the North China Plain / Hongyan Wang in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)
PermalinkA Bayesian network-based method to alleviate the ill-posed inverse problem: A case study on leaf area index and canopy water content retrieval / Xingwen Quan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)
PermalinkValidation of canopy height profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment / Karolina D. Fieber in ISPRS Journal of photogrammetry and remote sensing, vol 104 (June 2015)
PermalinkEvaluating 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)
PermalinkEstimating leaf chlorophyll of barley at different growth stages using spectral indices to reduce soil background and canopy structure effects / K. Yu in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)
PermalinkDisturbances in European beech water relation during an extreme drought / Marianne Peiffer in Annals of Forest Science, vol 71 n° 7 (October 2014)
PermalinkQuantification of L-band InSAR coherence over volcanic areas using LiDAR and in situ measurements / M. Arab-Sedze in Remote sensing of environment, vol 152 (September 2014)
PermalinkLaboratory measurements of plant drying: Implications to estimate moisture content from radiative transfer models in two temperate species / Sara Jurdao in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 5 (May 2014)
PermalinkDeriving leaf mass per area (LMA) from foliar reflectance across a variety of plant species using continuous wavelet analysis / Tao Cheng in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
PermalinkGaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval / Jochem Verrlest in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)
PermalinkImprovement and application of the conifer forest multiangular hybrid GORT model MGeoSAIL / Qiang Wang in IEEE Transactions on geoscience and remote sensing, vol 51 n° 10 (October 2013)
PermalinkLeaf area index estimation of boreal and subarctic forests using VV/HH ENVISAT/ASAR data of various swaths / Terhikki Manninen in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 1 (July 2013)
PermalinkUtility of the wavelet transform for LAI estimation using hyperspectral data / Asim Banskota in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 7 (July 2013)
PermalinkUsing thermal time and pixel purity for enhancing biophysical variable time series: An interproduct comparison / Grégory Duveiller in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 1 (April 2013)
PermalinkRetrieval of effective leaf area index in heterogeneous forests with terrestrial laser scanning / G. Zheng in IEEE Transactions on geoscience and remote sensing, vol 51 n° 2 (February 2013)
PermalinkEstimating urban leaf area index (LAI) of individual trees with hyperspectral data / R. Jensen in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 5 (May 2012)
PermalinkEtude des couverts forestiers par inversion de formes d'onde Lidar à l'aide du modèle de transfert radiatif DART développé par le CESBIO / A. Ueberschlag in XYZ, n° 126 (mars - mai 2011)
PermalinkExtending sapwood – Leaf area relationships from stems to roots in Coast Douglas-fir / Peter J. Gould ; Constance A. Harrington in Annals of Forest Science, Vol 65 n° 8 (December 2008)
PermalinkManipulating nutrient and water availability in a maritime pine plantation: effects on growth, production, and biomass allocation at canopy closure / Pierre Trichet ; Denis Loustau ; Catherine Lambrot ; Sune Linder in Annals of Forest Science, Vol 65 n° 8 (December 2008)
PermalinkAssessment of the influence of flying altitude and scan angle on biophysical vegetation products derived from airborne laser scanning / F. Morsdorf in International Journal of Remote Sensing IJRS, vol 29 n° 5 (March 2008)
PermalinkSpatially and temporally continuous LAI data sets based on an integrated filtering method: examples from North America / H. Fang in Remote sensing of environment, vol 112 n° 1 (15/01/2008)
PermalinkComparison 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)
PermalinkEstimating spatial patterns of rainfall interception from remotely sensed vegetation indices and spectral mixture analysis / S.M. de Jong in International journal of geographical information science IJGIS, vol 21 n° 5 (may 2007)
PermalinkSupport vector machines regression for retrieval of leaf area index from multiangle imaging spectroradiometer / S. Durbha in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)
PermalinkFusion of imaging spectrometer and LIDAR data over combined radiative transfer models for forest canopy characterization / B. Koetz in Remote sensing of environment, vol 106 n° 4 (28/02/2007)
PermalinkReflectance seasonality and its relation to the canopy leaf area index in an eastern Siberian larch forest: Multi-satellite data and radiative transfer analyses / H. Kobayashi in Remote sensing of environment, vol 106 n° 2 (30/01/2007)
PermalinkNeural network estimation of LAI, fAPAR, fCover and LAI*Cab, from top of canopy MERIS reflectance data: principles and validation / C. Bacour in Remote sensing of environment, vol 105 n° 4 (30/12/2006)
PermalinkIntegration of MODIS data into a simple model for the spatial distributed simulation of soil water content and evapotranspiration / Y. Zhang in Remote sensing of environment, vol 104 n° 4 (30/10/2006)
PermalinkLAI retrieval from multiangular image classification and inversion of a ray tracing model / R. Casa in Remote sensing of environment, vol 98 n° 4 (30/10/2005)
PermalinkRegional simulation of ecosystem CO2 and water vapor exchange for agricultural land using NOAA AVHRR and Terra MODIS satellite data: Application to Zealand, Denmark / Rasmus M. Houborg in Remote sensing of environment, vol 93 n° 1 (30/10/2004)
PermalinkEstimating live fuel moisture content from remotely sensed reflectance / F. Mark Danson in Remote sensing of environment, vol 92 n° 3 (30 August 2004)
PermalinkLeaf Area Index measurements in a tropical moist forest: a case study from Costa Rica / M. Kalacska in Remote sensing of environment, vol 91 n° 2 (30/05/2004)
PermalinkWavelet transform applied to EO-1 hyperspectral data for forest LAI and crown closure mapping / R. Pu in Remote sensing of environment, vol 91 n° 2 (30/05/2004)
PermalinkEvaluation of the MODIS LAI at coniferous forest site in Finland / Y. Wang in Remote sensing of environment, vol 91 n° 1 (15/05/2004)
PermalinkUsing Lidar and effective LAI data to evaluate Ikonos and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest / X. Chen in Remote sensing of environment, vol 91 n° 1 (15/05/2004)
PermalinkHyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modelling and validation in the context of precision agriculture / D. Haboudane in Remote sensing of environment, vol 90 n° 3 (15/04/2004)
PermalinkAirborne measurement of hot spot reflectance signatures / F. Camacho-De Coca in Remote sensing of environment, vol 90 n° 1 (15/03/2004)
PermalinkComparisons of land cover and LAI estimates derived from ETM+ and MODIS for four sites in North America: a quality assessment of 2000/2001 provisional MODIS / W.B. Cohen in Remote sensing of environment, vol 88 n° 3 (15/12/2003)
PermalinkTraining a neural network with a canopy reflectance model to estimate crop leaf area index / F. Mark Danson in International Journal of Remote Sensing IJRS, vol 24 n° 23 (December 2003)
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