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A 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)
[article]
Titre : A Bayesian network-based method to alleviate the ill-posed inverse problem: A case study on leaf area index and canopy water content retrieval Type de document : Article/Communication Auteurs : Xingwen Quan, Auteur ; Binbin He, Auteur ; Xing Li, Auteur Année de publication : 2015 Article en page(s) : pp 6507 - 6517 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] appariement d'images
[Termes IGN] image Landsat-8
[Termes IGN] Leaf Area Index
[Termes IGN] probabilité
[Termes IGN] problème inverse
[Termes IGN] réseau bayesien
[Termes IGN] teneur en eau de la végétationRésumé : (auteur) Retrieval of vegetation parameters from remotely sensed data using a radiative transfer model is generally hampered by the ill-posed inverse problem, which dramatically decreases the precision level of retrieved parameters. The purpose of this study was to use a Bayesian network-based method to allow the alleviation of the ill-posed inverse problem. This was achieved by introducing the correlations between the model free parameters into their prior joint probability distribution (PJPD), allowing the reduction of the probabilities of unrealistic combinations. Three sampling strategies intended to design three types of PJPDs that considered different correlations (represented by a correlation matrix) were presented. They were multivariate uniform distribution composed by independent free parameters, multivariate uniform distribution based on a simple correlation matrix, and multivariate Gaussian distribution based on a complicated correlation matrix, respectively. A case study of the presented method to retrieve leaf area index (LAI) and canopy water content (CWC) using the PROSAIL_5B (PROSPECT-5 + 4SAIL) model from Landsat 8 products was implemented. Results indicate that the presented method greatly improves the precision level of target parameters, with the coefficient of determination R2 of 0.69, 0.77, and 0.82 and root-mean-square error (RMSE) of 0.55, 0.51, and 0.44 m2 · m-2 for LAI and R2 = 0.68, 0.78, and 0.84 and RMSE = 230, 198, and 166 g · m-2 for CWC, respectively. Hence, the ill-posed inverse problem can be alleviated by the presented method, which can be widely applied for vegetation parameters retrieval. Numéro de notice : A2015-838 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2442999 Date de publication en ligne : 30/06/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2442999 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79172
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 12 (December 2015) . - pp 6507 - 6517[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2015121 SL Revue Centre de documentation Revues en salle Disponible Validation 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)
[article]
Titre : Validation of canopy height profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment Type de document : Article/Communication Auteurs : Karolina D. Fieber, Auteur ; Ian J. Davenport, Auteur ; Mihai A. Tanase, Auteur ; James M. Ferryman, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 144 - 157 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Australie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forme d'onde pleine
[Termes IGN] hauteur des arbres
[Termes IGN] Leaf Area Index
[Termes IGN] modèle numérique de surface de la canopéeRésumé : (auteur) A Canopy Height Profile (CHP) procedure presented in Harding et al. (2001) for large footprint LiDAR data was tested in a closed canopy environment as a way of extracting vertical foliage profiles from LiDAR raw-waveform. In this study, an adaptation of this method to small-footprint data has been shown, tested and validated in an Australian sparse canopy forest at plot- and site-level. Further, the methodology itself has been enhanced by implementing a dataset-adjusted reflectance ratio calculation according to Armston et al. (2013) in the processing chain, and tested against a fixed ratio of 0.5 estimated for the laser wavelength of 1550 nm. As a by-product of the methodology, effective leaf area index (LAIe) estimates were derived and compared to hemispherical photography values. To assess the influence of LiDAR aggregation area size on the estimates in a sparse canopy environment, LiDAR CHPs and LAIes were generated by aggregating waveforms to plot- and site-level footprints (plot/site-aggregated) as well as in 5 m grids (grid-processed). LiDAR profiles were then compared to field biomass profiles generated based on field tree measurements. The correlation between field and LiDAR profiles was very high, with a mean R2 of 0.75 at plot-level and 0.86 at site-level for 55 plots and the corresponding 11 sites. Gridding had almost no impact on the correlation between LiDAR and field profiles (only marginally improvement), nor did the dataset-adjusted reflectance ratio. However, gridding and the dataset-adjusted reflectance ratio were found to improve the correlation between raw-waveform LiDAR and hemispherical photography LAIe estimates, yielding the highest correlations of 0.61 at plot-level and of 0.83 at site-level. This proved the validity of the approach and superiority of dataset-adjusted reflectance ratio of Armston et al. (2013) over a fixed ratio of 0.5 for LAIe estimation, as well as showed the adequacy of small-footprint LiDAR data for LAIe estimation in discontinuous canopy forests. Numéro de notice : A2015-702 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.03.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.03.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78338
in ISPRS Journal of photogrammetry and remote sensing > vol 104 (June 2015) . - pp 144 - 157[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)
[article]
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 feuillesRésumé : (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
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 85 - 95[article]Estimating leaf chlorophyll of barley at different growth stages using spectral indices to reduce soil background and canopy structure effects / Kiyun Yu in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)
[article]
Titre : Estimating leaf chlorophyll of barley at different growth stages using spectral indices to reduce soil background and canopy structure effects Type de document : Article/Communication Auteurs : Kiyun Yu, Auteur ; Victoria Lenz-Wiedemann, Auteur ; X. Chen, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 58 – 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] agriculture de précision
[Termes IGN] croissance des arbres
[Termes IGN] exitance spectrale
[Termes IGN] indice de végétation
[Termes IGN] indice foliaire
[Termes IGN] orge (céréale)
[Termes IGN] réflectance spectrale
[Termes IGN] surveillance de la végétation
[Termes IGN] teneur en chlorophylle des feuillesRésumé : (Auteur) Monitoring in situ chlorophyll (Chl) content in agricultural crop leaves is of great importance for stress detection, nutritional state diagnosis, yield prediction and studying the mechanisms of plant and environment interaction. Numerous spectral indices have been developed for chlorophyll estimation from leaf- and canopy-level reflectance. However, in most cases, these indices are negatively affected by variations in canopy structure and soil background. The objective of this study was to develop spectral indices that can reduce the effects of varied canopy structure and growth stages for the estimation of leaf Chl. Hyperspectral reflectance data was obtained through simulation by a radiative transfer model, PROSAIL, and measurements from canopies of barley comprising different cultivars across growth stages using spectroradiometers. We applied a comprehensive band-optimization algorithm to explore five types of spectral indices: reflectance difference (RD), reflectance ratio (RR), normalized reflectance difference (NRD), difference of reflectance ratio (DRR) and ratio of reflectance difference (RRD). Indirectly using the multiple scatter correction (MSC) theory, we hypothesized that RRD can eliminate adverse effects of soil background, canopy structure and multiple scattering. Published indices and multivariate models such as optimum multiple band regression (OMBR), partial least squares regression (PLSR) and support vector machines for regression (SVR) were also employed. Results showed that the ratio of reflectance difference index (RRDI) optimized for simulated data significantly improved the correlation with Chl (R2 = 0.98, p Numéro de notice : A2014-524 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.08.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.08.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74136
in ISPRS Journal of photogrammetry and remote sensing > vol 97 (November 2014) . - pp 58 – 77[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2014111 RAB Revue Centre de documentation En réserve L003 Disponible Disturbances in European beech water relation during an extreme drought / Marianne Peiffer in Annals of Forest Science, vol 71 n° 7 (October 2014)
[article]
Titre : Disturbances in European beech water relation during an extreme drought Type de document : Article/Communication Auteurs : Marianne Peiffer, Auteur ; Nathalie Bréda, Auteur ; Vincent Badeau, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 821 - 829 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] comportement
[Termes IGN] evaporation
[Termes IGN] Fagus (genre)
[Termes IGN] forêt
[Termes IGN] humidité du sol
[Termes IGN] indice foliaire
[Termes IGN] Lorraine
[Termes IGN] sécheresseRésumé : (Auteur) Context
In the context of a probable increase in intensity and frequency of extreme summer drought events, a better understanding of the key processes involved in water relations is needed to improve the theoretical foundations of predictive process-based models.
Aims
This paper aims to analyse how temperate deciduous trees cope with water shortage.
Methods
The exceptional summer drought of 2003 in Europe provided an opportunity to monitor stomatal conductance and twig water potential in European beech (Fagus sylvatica L.) at predawn and midday and to analyse variations with respect to leaf height within the canopy. By comparing our field measurements of twig water potential to values found in the literature, we confirmed the strong impact of soil water shortage on crown water relations.
Results
This paper shows that (1) the vertical gradient of stomatal conductance within the crown disappeared under extreme soil water depletion; (2) at maximum drought intensity, predawn twig water potential (ψ pd) reached −2.3 MPa at a height of 14 m in the crown and −2.0 MPa at a height of 10 m. The significant differences in ψ pd between the two measurement heights in the canopy may be due to night transpiration; (3) there was a close relationship between predawn twig water potential and relative extractable soil water; (4) as drought conditions intensified, there was a close relationship between canopy radiation interception and predawn water potential, as estimated daily from relative extractable soil water.Numéro de notice : A2014-536 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-014-0383-3 Date de publication en ligne : 23/05/2014 En ligne : https://doi.org/10.1007/s13595-014-0383-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74149
in Annals of Forest Science > vol 71 n° 7 (October 2014) . - pp 821 - 829[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 016-2014071 SL Revue Centre de documentation Revues en salle Disponible Quantification of L-band InSAR coherence over volcanic areas using LiDAR and in situ measurements / Mélanie 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)Permalink