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Forest height estimation by means of Pol-InSAR data inversion : The role of the vertical wavenumber / Florian Kugler in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)
[article]
Titre : Forest height estimation by means of Pol-InSAR data inversion : The role of the vertical wavenumber Type de document : Article/Communication Auteurs : Florian Kugler, Auteur ; Seung-Kuk Lee, Auteur ; Irena Hajnsek, Auteur ; Konstantinos P. Papathanassiou, Auteur Année de publication : 2015 Article en page(s) : pp 5294 - 5311 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] données polarimétriques
[Termes IGN] estimation statistique
[Termes IGN] forêt
[Termes IGN] hauteur des arbres
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] inversion
[Termes IGN] Pol-INSAR
[Termes IGN] polarimétrie radar
[Termes IGN] validation des donnéesRésumé : (Auteur) This paper examines the multifaceted effect of the effective spatial baseline, as expressed through the vertical (interferometric) wavenumber, on the inversion of forest height from polarimetric interferometric synthetic aperture radar (Pol-InSAR) data. First, the role of the vertical wavenumber in relating forest height to the interferometric (volume) coherence is introduced. Through the review of the forest height inversion from Pol-InSAR data, the effect of the vertical wavenumber on the inversion performance is evaluated. The selection of optimum with respect to forest height inversion performance, vertical wavenumbers is discussed. The impact of the acquisition geometry and terrain slopes on the vertical wavenumber and their consideration in the inversion methodology is addressed. The individual effects discussed are demonstrated by means of airborne repeat pass Pol-InSAR acquisitions in L- and P-band acquired over different forest conditions, including a boreal, a temperate, and a tropical forest test site. The achieved forest height inversion performance is validated against reference height data derived from airborne LIDAR acquisitions. Numéro de notice : A2015-747 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2420996 Date de publication en ligne : 04/05/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2420996 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78755
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 10 (October 2015) . - pp 5294 - 5311[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015101 SL Revue Centre de documentation Revues en salle Disponible A geometric method for wood-leaf separation using terrestrial and simulated Lidar data / Shengli Tao in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 10 (October 2015)
[article]
Titre : A geometric method for wood-leaf separation using terrestrial and simulated Lidar data Type de document : Article/Communication Auteurs : Shengli Tao, Auteur ; Qinghua Guo, Auteur ; Shiwu Xu, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 767 - 776 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection de contours
[Termes IGN] données lidar
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] feuille (végétation)
[Termes IGN] géométrie
[Termes IGN] semis de points
[Termes IGN] système de coordonnées
[Termes IGN] traitement de données localisées
[Termes IGN] troncRésumé : (auteur) Terrestrial light detection and ranging (lidar) can be used to record the three-dimensional structures of trees. Wood-leaf separation, which aims to classify lidar points into wood and leaf components, is an essential prerequisite for deriving individual tree characteristics. Previous research has tended to use intensity (including a multi-wavelength approach) and waveform information for wood-leaf separation, but use of the most fundamental information from a lidar point cloud, i.e., the x-, y-, and z- coordinates of each point, for this purpose has been poorly explored. In this study, we introduce a geometric method for wood-leaf separation using the x-, y-, and zcoordinates of each point. The separation results indicate that first-, second-, and third-order branches can be extracted from the raw point cloud by this new method, suggesting that it might provide a promising solution for wood-leaf separation. Numéro de notice : A2015-987 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.81.10.767 En ligne : https://doi.org/10.14358/PERS.81.10.767 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80268
in Photogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 10 (October 2015) . - pp 767 - 776[article]High-resolution forest canopy height estimation in an African blue carbon ecosystem / David Lagomasino in Remote sensing in ecology and conservation, vol 1 n° 1 (October 2015)
[article]
Titre : High-resolution forest canopy height estimation in an African blue carbon ecosystem Type de document : Article/Communication Auteurs : David Lagomasino, Auteur ; Temilola Fatoyinbo, Auteur ; Seung-Kuk Lee, Auteur ; Marc Simard, Auteur Année de publication : 2015 Article en page(s) : pp 51 - 60 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] biomasse
[Termes IGN] données localisées 3D
[Termes IGN] estimation statistique
[Termes IGN] hauteur des arbres
[Termes IGN] mangrove
[Termes IGN] MNS SRTM
[Termes IGN] MozambiqueRésumé : (auteur) Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereo-photogrammetric techniques on high-resolution spaceborne imagery (HRSI) for southern Mozambique. A mean-weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18-1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three-dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications. Numéro de notice : A2015--101 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1002/rse2.3 En ligne : http://doi.org/10.1002/rse2.3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87170
in Remote sensing in ecology and conservation > vol 1 n° 1 (October 2015) . - pp 51 - 60[article]Documents numériques
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High-resolution forest canopy height estimation - pdf éditeurAdobe Acrobat PDF Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)
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Titre : Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas Type de document : Article/Communication Auteurs : Timothy Dube, Auteur ; Onisimo Mutanga, Auteur Année de publication : 2015 Article en page(s) : pp 12 – 32 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] Afrique du sud (état)
[Termes IGN] biodiversité
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] classification
[Termes IGN] classification dirigée
[Termes IGN] espèce végétale
[Termes IGN] Eucalyptus dunii
[Termes IGN] Eucalyptus grandis
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-OLI
[Termes IGN] Pinus taeda
[Termes IGN] régression
[Termes IGN] sous-étage
[Termes IGN] sylviculture
[Termes IGN] texture d'imageRésumé : (auteur) The successful launch of the 30-m Landsat-8 Operational Land Imager (OLI) pushbroom sensor offers a new primary data source necessary for aboveground biomass (AGB) estimation, especially in resource-limited environments. In this work, the strength and performance of Landsat-8 OLI image derived texture metrics (i.e. texture measures and texture ratios) in estimating plantation forest species AGB was investigated. It was hypothesized that the sensor’s pushbroom design, coupled with the presence of refined spectral properties, enhanced radiometric resolution (i.e. from 8 bits to 12 bits) and improved signal-to-noise ratio have the potential to provide detailed spectral information necessary for significantly strengthening AGB estimation in medium-density forest canopies. The relationship between image texture metrics and measurements of forest attributes can be used to help characterize complex forests, and enhance fine vegetation biophysical properties, a difficult challenge when using spectral vegetation indices especially in closed canopies. This study examines the prospects of using Landsat-8 OLI sensor derived texture metrics for estimating AGB for three medium-density plantation forest species in KwaZulu Natal, South Africa. In order to achieve this objective, three unique data pre-processing techniques were tested (analysis I: Landsat-8 OLI raw spectral-bands vs. raw texture bands; analysis II: Landsat-8 OLI raw spectral-band ratios vs. texture band ratios and analysis III: Landsat-8 OLI derived vegetation indices vs. texture band ratios). The landsat-8 OLI derived texture parameters were examined for robustness in estimating AGB using linear regression, stepwise-multiple linear regression and stochastic gradient boosting regression models. The results of this study demonstrated that all texture parameters particularly band texture ratios calculated using a 3 × 3 window size, could enhance AGB estimation when compared to simple spectral reflectance, simple band ratios and the most popular spectral vegetation indices. For instance, the use of combined texture ratios yielded the highest R2 values of 0.76 (RMSE = 9.55 t ha−1 (18.07%) and CV-RMSE of 0.18); 0.74 (RMSE = 12.81 t ha−1 (17.72%) and CV-RMSE of 0.08); 0.74 (RMSE = 12.67 t ha−1 (06.15%) and CV-RMSE of 0.06) and 0.53 (RMSE = 20.15 t ha−1 (14.40%) and CV-RMSE of 0.15) overall for Eucalyptus dunii, Eucalyptus grandis, Pinus taeda individually and all species, respectively. Overall, the findings of this study provide the necessary insight and motivation to the remote sensing community, particularly in resource constrained regions, to shift towards embracing various texture metrics obtained from the readily-available and cheap multispectral Landsat-8 OLI sensor. Numéro de notice : A2015-849 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.002 Date de publication en ligne : 25/06/2015 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.06.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79219
in ISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 12 – 32[article]Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data / Virpi Junttila in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)
[article]
Titre : Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data Type de document : Article/Communication Auteurs : Virpi Junttila, Auteur ; Tuomo Kauranne, Auteur ; Andrew O. Finley, Auteur ; John B. Bradford, Auteur Année de publication : 2015 Article en page(s) : pp 5600 - 5612 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] appariement d'images
[Termes IGN] décomposition d'image
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle linéaire
[Termes IGN] placette d'échantillonnage
[Termes IGN] précision des données
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%-15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model's lack of fit. Numéro de notice : A2015-748 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2425916 Date de publication en ligne : 14/05/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2425916 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78757
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 10 (October 2015) . - pp 5600 - 5612[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015101 SL Revue Centre de documentation Revues en salle Disponible Modeling the above and belowground biomass of planted and coppiced Eucalytpus globulus stands in NW Spain / Daniel J. Vega-Nieva in Annals of Forest Science, vol 72 n° 7 (October 2015)PermalinkMonitoring ectomycorrhizal fungi at large scales for science, forest management, fungal conservation and environmental policy / Laura M. Suz in Annals of Forest Science, vol 72 n° 7 (October 2015)Permalinkvol 72 n° 7 - October 2015 - Monitoring European forests: results for science, policy, and society (Bulletin de Annals of Forest Science) / Pasi RautioPermalinkMonitoring European forests: results for science, policy, and society / Pasi Rautio in Annals of Forest Science, vol 72 n° 7 (October 2015)PermalinkPhosphorus nutrition of beech (Fagus sylvatica L.) is decreasing in Europe / Ulrike Talkne in Annals of Forest Science, vol 72 n° 7 (October 2015)PermalinkA semiautomated probabilistic framework for tree-cover delineation from 1-m NAIP imagery using a high-performance computing architecture / S. Basu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)PermalinkStand density, tree social status and water stress influence allocation in height and diameter growth of Quercus petraea (Liebl.) / Raphaël Trouvé in Tree Physiology, vol 35 n° 10 (October 2015)PermalinkTracking bats movements / Vivian Raiborde in GIM international [en ligne], vol 29 n° 10 (October 2015)PermalinkTropical forest canopy cover estimation using satellite imagery and airborne lidar reference data / Lauri Korhonen in Silva fennica, vol 49 n° 5 ([01/10/2015])PermalinkVariables related to nitrogen deposition improve defoliation models for European forests / Marco Ferretti in Annals of Forest Science, vol 72 n° 7 (October 2015)Permalink