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Termes IGN > sciences naturelles > sciences de la vie > biologie > botanique > formation végétale > forêt > canopée
canopée
Commentaire :
interface forêt-atmosphère. forêt, association végétale. >> écologie de la canopée. Source(s) : Glossaire d'écologie fondamentale / M. Duquet, 1993. Equiv. LCSH : Forest canopies. Domaine(s) : 580. Synonyme(s)Voûte forestièreVoir aussi |
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Estimating over- and understorey canopy density of temperate mixed stands by airborne LiDAR data / Hooman Latifi in Forestry, an international journal of forest research, vol 89 n° 1 (January 2016)
[article]
Titre : Estimating over- and understorey canopy density of temperate mixed stands by airborne LiDAR data Type de document : Article/Communication Auteurs : Hooman Latifi, Auteur ; Marco Heurich, Auteur ; Florian Hartig, Auteur ; Jorg Müller, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 61 - 81 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Abies alba
[Termes IGN] Acer pseudoplatanus
[Termes IGN] Betula pendula
[Termes IGN] betula pubescens
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Fagus sylvatica
[Termes IGN] habitat forestier
[Termes IGN] Picea abies
[Termes IGN] régression
[Termes IGN] sorbus aucuparia
[Termes IGN] sous-boisRésumé : (auteur) Estimating forest structural attributes is one of the essential forestry-related remote sensing applications. The methods applied so far typically concentrate on the structure of the overstorey. For various conservation and management applications, however, information on lower layers is also of great interest. Detecting understorey cover by remote sensing is challenging, as passive sensors do not penetrate to the forest ground layer. An alternative to these is 3D metrics from active light detection and ranging (LiDAR). Here, we evaluate this technique for describing the vegetation density of multiple stand layers within the temperate stands of a large protected area in south-eastern Germany. We combined LiDAR metrics and information on forest habitat types with regression models to investigate LiDAR metrics that are significantly correlated with vegetation density. The top canopy and the herbal layer showed strong correlations with the applied LiDAR metrics, whereas the predictive power was lower for the intermediate stand layers. Moreover, our results suggest that the relationship between LiDAR predictors and vegetation density depends on the forest type. A comparison of the regression models with random forest predictions showed no major improvement in predictive error. In conclusion, this study highlights the value of the LiDAR metrics for characterizing the structural properties of lower forest layers, which has implications for wildlife and forest management applications, especially in protected areas. Numéro de notice : A2016--102 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1093/forestry/cpv032 En ligne : https://doi.org/10.1093/forestry/cpv032 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84668
in Forestry, an international journal of forest research > vol 89 n° 1 (January 2016) . - pp 61 - 81[article]Canopy density model: A new ALS-derived product to generate multilayer crown cover maps / António Ferraz in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)
[article]
Titre : Canopy density model: A new ALS-derived product to generate multilayer crown cover maps Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Clément Mallet , Auteur ; Stéphane Jacquemoud, Auteur ; Gil Rito-Gonçalves , Auteur ; Margarida Tomé, Auteur ; Paola Soares, Auteur ; Luisa M. Gomes Pereira, Auteur ; Frédéric Bretar, Auteur Année de publication : 2015 Article en page(s) : pp 6776 - 6790 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] canopée
[Termes IGN] carte de la végétation
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] estimation par noyau
[Termes IGN] Portugal
[Termes IGN] sous-étage
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] traitement d'imageRésumé : (auteur) The canopy density model (CDM), a new product interpolated from airborne laser scanner (ALS) data and dedicated to forest structure characterization is presented. It exploits both the multiecho capability of the ALS and a nonparametric density estimation technique called kernel density estimators (KDEs). The CDM is used to delineate the outmost perimeter of vegetation features and to compute forest crown cover (CrCO). Contrary to other works that focus on single-layer forest canopies, CrCo is derived here for each layer, namely, the overstory, the understory, and ground vegetation. The root-mean-square error of prediction determined by using field data acquired over 44 forest stands in a forest in Portugal allows the testing of the reliability of the method: It ranges from 6.21% (overstory) to 13.76% (ground vegetation). In addition, we investigate the ability of the CDM to map the CrCo for individual trees. Finally, two existing methods have been applied to our study site in order to assess improvements, advantages, and drawbacks of our approach. Numéro de notice : A2015-840 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2448056 Date de publication en ligne : 10/08/2015 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2448056 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79180
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 12 (December 2015) . - pp 6776 - 6790[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015121 SL Revue Centre de documentation Revues en salle Disponible Tropical forest canopy cover estimation using satellite imagery and airborne lidar reference data / Lauri Korhonen in Silva fennica, vol 49 n° 5 ([01/10/2015])
[article]
Titre : Tropical forest canopy cover estimation using satellite imagery and airborne lidar reference data Type de document : Article/Communication Auteurs : Lauri Korhonen, Auteur ; Daniela Ali-Sisto, Auteur ; Timo Tokola, Auteur Année de publication : 2015 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] canopée
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] image ALOS-AVNIR2
[Termes IGN] image optique
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Laos
[Termes IGN] placette d'échantillonnage
[Termes IGN] régression logistique
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) The fusion of optical satellite imagery, strips of lidar data and field plots is a promising approach for the inventory of tropical forests. Airborne lidars also enable an accurate direct estimation of the forest canopy cover (CC), and thus a sample of lidar strips can be used as reference data for creating CC maps which are based on satellite images. In this study, our objective was to validate CC maps obtained from an ALOS AVNIR-2 satellite image wall-to-wall, against a lidar-based CC map of a tropical forest area located in Laos. The reference CC values which were needed for model training were obtained from a sample of four lidar strips. Zero-and-one inflated beta regression (ZOINBR) models were applied to link the spectral vegetation indices derived from the ALOS image with the lidar-based CC estimates. In addition, we compared ZOINBR and logistic regression models in the forest area estimation by using >20% CC as a forest definition. Using a total of 409 217 30 × 30 m population units as validation, our model showed a strong correlation between lidar-based CC and spectral satellite features (root mean square error = 12.8%, R2 = 0.82). In the forest area estimation, a direct classification using logistic regression provided better accuracy than the estimation of CC values as an intermediate step (kappa = 0.61 vs. 0.53). It is important to obtain sufficient training data from both ends of the CC range. The forest area estimation should be done before the CC estimation, rather than vice versa. Numéro de notice : A2015-673 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14214/sf.1405 En ligne : http://www.silvafennica.fi/article/1405 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78293
in Silva fennica > vol 49 n° 5 [01/10/2015][article]Aboveground-biomass estimation of a complex tropical forest in India using Lidar / Cédric Vega in Remote sensing, vol 7 n° 8 (August 2015)
[article]
Titre : Aboveground-biomass estimation of a complex tropical forest in India using Lidar Type de document : Article/Communication Auteurs : Cédric Vega , Auteur ; Udayalakshmi Vepakomma, Auteur ; Jules Morel, Auteur ; Jean-Luc Bader, Auteur ; Gopalakrishnan Rajashekar, Auteur ; Chandra Shekhar Jha, Auteur ; Jérôme Ferêt, Auteur ; Christophe Proisy, Auteur ; Raphaël Pélissier, Auteur ; Vinay Kumar Dadhwal, Auteur Année de publication : 2015 Projets : 3-projet - voir note / Article en page(s) : pp 10607 - 10625 Note générale : bibliographie
The research has been supported by IFPCAR (Indo-French Promotion Center for Advanced Research) through the joint project number 4509-1 “Controlling for Uncertainty in Assessment of Forest Aboveground Biomass in the Western Ghats of India”between UMR AMAP, Montpellier and the National Remote Sensing Centre, Hyderabad. The authors also greatly acknowledge the French Institute of Pondicherry (IFP) for its financial support to Udayalakshmi Vepakomma for visiting IFPand for providing field control data from its long term monitoring plot in Uppangala.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse aérienne
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] Ghats occidentaux
[Termes IGN] Inde
[Termes IGN] pente
[Termes IGN] profil en travers
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] volume en boisRésumé : (auteur) Light Detection and Ranging (Lidar) is a state of the art technology to assess forest aboveground biomass (AGB). To date, methods developed to relate Lidar metrics with forest parameters were built upon the vertical component of the data. In multi-layered tropical forests, signal penetration might be restricted, limiting the efficiency of these methods. A potential way for improving AGB models in such forests would be to combine traditional approaches by descriptors of the horizontal canopy structure. We assessed the capability and complementarity of three recently proposed methods for assessing AGB at the plot level using point distributional approach (DM), canopy volume profile approach (CVP), 2D canopy grain approach (FOTO), and further evaluated the potential of a topographical complexity index (TCI) to explain part of the variability of AGB with slope. This research has been conducted in a mountainous wet evergreen tropical forest of Western Ghats in India. AGB biomass models were developed using a best subset regression approach, and model performance was assessed through cross-validation. Results demonstrated that the variability in AGB could be efficiently captured when variables describing both the vertical (DM or CVP) and horizontal (FOTO) structure were combined. Integrating FOTO metrics with those of either DM or CVP decreased the root mean squared error of the models by 4.42% and 6.01%, respectively. These results are of high interest for AGB mapping in the tropics and could significantly contribute to the REDD+ program. Model quality could be further enhanced by improving the robustness of field-based biomass models and influence of topography on area-based Lidar descriptors of the forest structure. Numéro de notice : A2015--081 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs70810607 Date de publication en ligne : 18/08/2015 En ligne : https://doi.org/10.3390/rs70810607 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84559
in Remote sensing > vol 7 n° 8 (August 2015) . - pp 10607 - 10625[article]Documents numériques
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Aboveground-biomass estimation ... - pdf éditeurAdobe Acrobat PDF Savannah woody structure modelling and mapping using multi-frequency (X-, C- and L-band) Synthetic Aperture Radar data / Laven Naidoo in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)
[article]
Titre : Savannah woody structure modelling and mapping using multi-frequency (X-, C- and L-band) Synthetic Aperture Radar data Type de document : Article/Communication Auteurs : Laven Naidoo, Auteur ; Renaud Mathieu, Auteur ; Russell Main, Auteur ; Waldo Kleynhans, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 234 - 250 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Afrique du sud (état)
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] bande X
[Termes IGN] biomasse
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] image TerraSAR-X
[Termes IGN] savaneRésumé : (auteur) Structural parameters of the woody component in African savannahs provide estimates of carbon stocks that are vital to the understanding of fuelwood reserves, which is the primary source of energy for 90% of households in South Africa (80% in Sub-Saharan Africa) and are at risk of over utilisation. The woody component can be characterised by various quantifiable woody structural parameters, such as tree cover, tree height, above ground biomass (AGB) or canopy volume, each been useful for different purposes. In contrast to the limited spatial coverage of ground-based approaches, remote sensing has the ability to sense the high spatio-temporal variability of e.g. woody canopy height, cover and biomass, as well as species diversity and phenological status – a defining but challenging set of characteristics typical of African savannahs. Active remote sensing systems (e.g. Light Detection and Ranging – LiDAR; Synthetic Aperture Radar – SAR), on the other hand, may be more effective in quantifying the savannah woody component because of their ability to sense within-canopy properties of the vegetation and its insensitivity to atmosphere and clouds and shadows. Additionally, the various components of a particular target’s structure can be sensed differently with SAR depending on the frequency or wavelength of the sensor being utilised. This study sought to test and compare the accuracy of modelling, in a Random Forest machine learning environment, woody above ground biomass (AGB), canopy cover (CC) and total canopy volume (TCV) in South African savannahs using a combination of X-band (TerraSAR-X), C-band (RADARSAT-2) and L-band (ALOS PALSAR) radar datasets. Training and validation data were derived from airborne LiDAR data to evaluate the SAR modelling accuracies. It was concluded that the L-band SAR frequency was more effective in the modelling of the CC (coefficient of determination or R2 of 0.77), TCV (R2 of 0.79) and AGB (R2 of 0.78) metrics in Southern African savannahs than the shorter wavelengths (X- and C-band) both as individual and combined (X + C-band) datasets. The addition of the shortest wavelengths also did not assist in the overall reduction of prediction error across different vegetation conditions (e.g. dense forested conditions, the dense shrubby layer and sparsely vegetated conditions). Although the integration of all three frequencies (X + C + L-band) yielded the best overall results for all three metrics (R2 = 0.83 for CC and AGB and R2 = 0.85 for TCV), the improvements were noticeable but marginal in comparison to the L-band alone. The results, thus, do not warrant the acquisition of all three SAR frequency datasets for tree structure monitoring in this environment. Numéro de notice : A2015-713 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.04.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.04.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78353
in ISPRS Journal of photogrammetry and remote sensing > vol 105 (July 2015) . - pp 234 - 250[article]Determination of the spatial structure of vegetation on the repository of the mine “Fryderyk” in Tarnowskie Góry, based on airborne laser scanning from the ISOK project and digital orthophotomaps / Marta Szostak in Geodesy and cartography, vol 64 n° 1 (June 2015)PermalinkComparing individual-tree approaches for predicting height growth of underplanted seedlings / John M. Lhotka in Annals of Forest Science, vol 72 n° 4 (June 2015)PermalinkCharacterizing stand-level forest canopy cover and height using Landsat time series, samples of airborne LiDAR, and the Random Forest algorithm / Oumer S. Ahmed in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)PermalinkVegetation Burn Severity Mapping Using Landsat-8 and WorldView-2 / Zhuoting Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 2 (February 2015)PermalinkPinastéréo, estimation de la hauteur dominante et de la biomasse forestière dans le massif des Landes de Gascogne à partir d'images stéréoscopiques Pléiades / Thierry Bélouard in Revue Française de Photogrammétrie et de Télédétection, n° 209 (Janvier 2015)PermalinkPrédire la structure des forêts tropicales humides calédoniennes : analyse texturale de la canopée sur des images Pléiades / Elodie Blanchard in Revue Française de Photogrammétrie et de Télédétection, n° 209 (Janvier 2015)PermalinkRetrieving surface variables by integrating ground measurements and earth observation data in forest canopies : a case study in Speuldersbos forest / Kitsiri Weligepolage (2015)PermalinkEvaluating tree detection and segmentation routines on very high resolution UAV LiDAR data / Luke Wallace in IEEE Transactions on geoscience and remote sensing, vol 52 n° 12 (December 2014)PermalinkDeriving airborne laser scanning based computational canopy volume for forest biomass and allometry studies / Jari Vauhkonen in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)PermalinkIntegration of Lidar and Landsat to estimate forest canopy cover in coastal British Columbia / Oumer S. Ahmed in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 10 (October 2014)PermalinkAssessing the potential for leaf-off LiDAR data to model canopy closure in temperate deciduous forests / Jason R. Parent in ISPRS Journal of photogrammetry and remote sensing, vol 95 (September 2014)PermalinkGenerating pit-free canopy height models from airborne lidar / Anahita Khosravipour in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 9 (September 2014)PermalinkA novel rapid SAR simulator based on equivalent scatterers for three-dimensional forest canopies / Tao Zeng in IEEE Transactions on geoscience and remote sensing, vol 52 n° 9 Tome 1 (September 2014)PermalinkDeriving Predictive relationships of carotenoid content at the canopy level in a conifer forest using hyperspectral imagery and model simulation / Rocío Hernández-Clemente in IEEE Transactions on geoscience and remote sensing, vol 52 n° 8 Tome 2 (August 2014)PermalinkModélisation de la canopée forestière par photogrammétrie depuis des images acquises par drone / Jonathan Lisein in Revue Française de Photogrammétrie et de Télédétection, n° 206 (Avril 2014)PermalinkCoastal wetland mapping combining multi-date SAR and LiDAR / Thomas Richard Allen in Geocarto international, vol 28 n° 7-8 (November - December 2013)PermalinkBackscattering of individual LiDAR pulses from forest canopies explained by photogrammetrically derived vegetation structure / Ilkka Korpela in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)PermalinkForest canopy height estimation using ICESat/GLAS data and error factor analysis in Hokkaido, Japan / Masato Hayashi in ISPRS Journal of photogrammetry and remote sensing, vol 81 (July 2013)PermalinkAssessing the impact of hydrocarbon leakages on vegetation using reflectance spectroscopy / I.D. Sanches in ISPRS Journal of photogrammetry and remote sensing, vol 78 (April 2013)PermalinkComparison of forest attributes derived from two terrestrial lidar systems / Mark J. Ducey in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 3 (March 2013)PermalinkSingle strata canopy cover estimation using airborne laser scanning data / António Ferraz (juillet 2013)PermalinkDetection of large-scale forest canopy change in pan-tropical humid forests 2000–2009 with the seawinds Ku-band scatterometer / S. Frolking in IEEE Transactions on geoscience and remote sensing, vol 50 n° 7 Tome 1 (July 2012)PermalinkFull waveform-based analysis for forest type information derivation from large footprint spaceborne lidar data / Junjie Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 3 (March 2011)PermalinkLa canopée forestière vue par un Lidar ultra-violet aéroporté de nouvelle génération / J. Cuesta in Revue Française de Photogrammétrie et de Télédétection, n° 191 (Mai 2010)PermalinkDétection des variations de structure de peuplements en forêt dense tropicale humide par Lidar aéroporté / G. Vincent in Revue Française de Photogrammétrie et de Télédétection, n° 191 (Mai 2010)PermalinkAn application-oriented automated approach for co-registration of forest inventory and airborne laser scanning data / W. Dorigo in International Journal of Remote Sensing IJRS, vol 31 n° 5 (March 2010)PermalinkLidar mapping of canopy gaps in continuous cover forests : a comparison of canopy height model and point cloud based techniques / Rachel Gaulton in International Journal of Remote Sensing IJRS, vol 31 n° 5 (March 2010)PermalinkUncertainty within satellite LiDAR estimations of vegetation and topography / J. Rosette in International Journal of Remote Sensing IJRS, vol 31 n° 5 (March 2010)PermalinkInfluence de l'intensité d'exploitation et du degré d'ouverture de la canopée en forêt tropicale humide sur le maintien et la dynamique de la biodiversité / Christopher Baraloto (2010)PermalinkAdvanced full-waveform lidar data echo detection: assessing quality of derived terrain and tree height models in an alpine coniferous forest / Adrien Chauve in International Journal of Remote Sensing IJRS, vol 30 n° 19 (October 2009)PermalinkComparative analysis of SRTM-NED vegetation canopy height to LIDAR-derived vegetation canopy metrics / L. Kenyi in International Journal of Remote Sensing IJRS, vol 30 n°11-12 (June 2009)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)PermalinkImproved topographic correction of forest image data using a 3D canopy reflectance model in multiple forward mode / S.A. Soenen in International Journal of Remote Sensing IJRS, vol 29 n°3-4 (February 2008)PermalinkPermalinkCartographier la structure de la végétation forestière avec un système lidar aéroporté en terrain montagnard / L. Dorren in Revue Française de Photogrammétrie et de Télédétection, n° 186 (Juin 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)PermalinkQuality assessment of SRTM C- and X-band interferometric data: Implications for the retrieval of vegetation canopy height / W.S. Walker in Remote sensing of environment, vol 106 n° 4 (28/02/2007)PermalinkRadiometric correction of hemispherical images / A. Kuusk in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 6 (February 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 / Cédric Bacour in Remote sensing of environment, vol 105 n° 4 (30/12/2006)PermalinkExamining the influence of changing laser pulse repetition frequencies on conifer forest canopy returns / Laura Chasmer in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 12 (December 2006)PermalinkError assessment in two lidar-derived TIN datasets / M.H. Peng in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 8 (August 2006)PermalinkAssessment of forest structure with airborne LiDAR and the effects of platform altitude / N.R. Goodwin in Remote sensing of environment, vol 103 n° 2 (30/07/2006)PermalinkMapping the effects of water stress on sphagnum: preliminary observations using airborne remote sensing / A. Harris in Remote sensing of environment, vol 100 n° 3 (15 february 2006)PermalinkRelating SAR image texture to the biomass of regenerating tropical forests / T.M. Kuplich in International Journal of Remote Sensing IJRS, vol 26 n° 21 (November 2005)Permalink