Descripteur
Termes IGN > sciences naturelles > sciences de la vie > biologie > botanique > phytogéographie
phytogéographie
Commentaire :
écologie végétale. >> inventaire de la végétation, distribution géographique, acclimatation (botanique), phytogéographie, introduction (botanique), migration (botanique), plante endémique, réintroduction (botanique), plante allochtone. >>Terme(s) spécifique(s) : limite de la végétation. Equiv. LCSH : Phytogeography. Domaine(s) : 570; 580. |
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Semi-supervised SVM for individual tree crown species classification / Michele Dalponte in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)
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Titre : Semi-supervised SVM for individual tree crown species classification Type de document : Article/Communication Auteurs : Michele Dalponte, Auteur ; Levi Theodor Ene, Auteur ; Mattia Marconcini, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 77 – 87 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données laser
[Termes IGN] forêt boréale
[Termes IGN] image hyperspectrale
[Termes IGN] inventaire forestier localRésumé : (auteur) In this paper a novel semi-supervised SVM classifier is presented, specifically developed for tree species classification at individual tree crown (ITC) level. In ITC tree species classification, all the pixels belonging to an ITC should have the same label. This assumption is used in the learning of the proposed semi-supervised SVM classifier (ITC-S3VM). This method exploits the information contained in the unlabeled ITC samples in order to improve the classification accuracy of a standard SVM. The ITC-S3VM method can be easily implemented using freely available software libraries. The datasets used in this study include hyperspectral imagery and laser scanning data acquired over two boreal forest areas characterized by the presence of three information classes (Pine, Spruce, and Broadleaves). The experimental results quantify the effectiveness of the proposed approach, which provides classification accuracies significantly higher (from 2% to above 27%) than those obtained by the standard supervised SVM and by a state-of-the-art semi-supervised SVM (S3VM). Particularly, by reducing the number of training samples (i.e. from 100% to 25%, and from 100% to 5% for the two datasets, respectively) the proposed method still exhibits results comparable to the ones of a supervised SVM trained with the full available training set. This property of the method makes it particularly suitable for practical forest inventory applications in which collection of in situ information can be very expensive both in terms of cost and time. Numéro de notice : A2015-894 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.10.010 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.10.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79445
in ISPRS Journal of photogrammetry and remote sensing > vol 110 (December 2015) . - pp 77 – 87[article]Evaluating the impact of leaf-on and leaf-off airborne laser scanning data on the estimation of forest inventory attributes with the area-based approach / Joanne C. White in Canadian Journal of Forest Research, vol 45 n° 11 (November 2015)
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Titre : Evaluating the impact of leaf-on and leaf-off airborne laser scanning data on the estimation of forest inventory attributes with the area-based approach Type de document : Article/Communication Auteurs : Joanne C. White, Auteur ; John T.T.R. Arnett, Auteur ; Michael A. Wulder, Auteur ; Piotr Tompalski, Auteur ; Nicholas C. Coops, Auteur Année de publication : 2015 Article en page(s) : pp 1498 - 1513 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Alberta (Canada)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] feuille (végétation)
[Termes IGN] feuillu
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle numérique de surface
[Termes IGN] Pinophyta
[Termes IGN] Pinus contorta
[Termes IGN] placette d'échantillonnageRésumé : (auteur) Dans cette étude, nous explorons les conséquences de l’utilisation des données de balayage laser aéroporté (BLA), acquises avec ou sans feuilles, sur les résultats d’un modèle par surface dans une forêt dominée par le pin tordu latifolié (Pinus contorta var. latifolia Engelm.) dans les contreforts des montagnes Rocheuses en Alberta, au Canada. Nous avons examiné huit caractéristiques de la forêt : la hauteur dominante, la hauteur moyenne, la hauteur moyenne de Lorey, la surface terrière, le diamètre moyen quadratique, le volume marchand, le volume total et la biomasse aérienne totale. Nous avons utilisé 787 placettes au sol pour l’élaboration du modèle, stratifiées par les conditions d’acquisition du BLA (avec ou sans feuilles) et le type forestier dominant (conifères ou feuillus). Nous avons également généré des modèles regroupés qui combinaient les données de BLA avec feuilles aux données sans feuilles, et des modèles génériques qui combinent les données des placettes de tous les types forestiers. Nous avons évalué les différences dans les mesures de BLA et les résultats des modèles avec ou sans feuilles, ainsi que les impacts du regroupement des données de BLA avec et sans feuilles, de la création de modèles génériques et de l’application des modèles étalonnés avec feuilles aux données sans feuilles (et vice versa). En général, les mesures de BLA avec et sans feuilles n’étaient pas significativement différentes (p Numéro de notice : A2015-671 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1139/cjfr-2015-0192 En ligne : http://www.nrcresearchpress.com/doi/full/10.1139/cjfr-2015-0192 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78287
in Canadian Journal of Forest Research > vol 45 n° 11 (November 2015) . - pp 1498 - 1513[article]Forest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI / Yuanwei Qin in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)
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Titre : Forest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI Type de document : Article/Communication Auteurs : Yuanwei Qin, Auteur ; Xiangming Xiao, Auteur ; Jinwei Dong, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1 - 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] base de données d'occupation du sol
[Termes IGN] carte de la végétation
[Termes IGN] carte thématique
[Termes IGN] Chine
[Termes IGN] classification par arbre de décision
[Termes IGN] forêt
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Terra-MODIS
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] superposition d'images
[Termes IGN] teneur en carboneRésumé : (auteur) Forests and their changes are important to the regional and global carbon cycle, biodiversity and ecosystem services. Some uncertainty about forest cover area in China calls for an accurate and updated forest cover map. In this study, we combined ALOS PALSAR orthorectified 50-m mosaic images (FBD mode with HH and HV polarization) and MODIS time series data in 2010 to map forests in China. We used MODIS-based NDVI dataset (MOD13Q1, 250-m spatial resolution) to generate a map of annual maximum NDVI and used it to mask out built-up lands, barren lands, and sparsely vegetated lands. We developed a decision tree classification algorithm to identify forest and non-forest land cover, based on the signature analysis of PALSAR backscatter coefficient data. The PALSAR-based algorithm was then applied to produce a forest cover map in China in 2010. The resulting forest/non-forest classification map has an overall accuracy of 96.2% and a Kappa Coefficient of 0.91. The resultant 50-m PALSAR-based forest cover map was compared to five forest cover databases. The total forest area (2.02 × 106 km2) in China from the PALSAR-based forest map is close to the forest area estimates from China National Forestry Inventory (1.95 × 106 km2), JAXA (2.00 × 106 km2), and FAO FRA (2.07 × 106 km2). There are good linear relationships between the PALSAR-based forest map and the forest maps from the JAXA, MCD12Q1, and NLCD-China datasets at the province and county scales. All the forest maps have similar spatial distributions of forest/non-forest at pixel scale. Our PALSAR-based forest map recognizes well the agro-forests in China. The results of this study demonstrate the potential of integrating PALSAR and MODIS images to map forests in large areas. The resultant map of forest cover in China in 2010 can be used for many studies such as forest carbon cycle and ecological restoration. Numéro de notice : A2015-854 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.08.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.08.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79234
in ISPRS Journal of photogrammetry and remote sensing > vol 109 (November 2015) . - pp 1 - 16[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)
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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 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])
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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]Effet de l’exposition sur la richesse et la composition floristique des lisières forestières dans le Gâtinais oriental (Loiret) / Richard Chevalier in Revue forestière française, vol 67 n° 5 (septembre 2015)
PermalinkHow much do we know about the endangered Atlantic Forest? Reviewing nearly 70 years of information on tree community surveys / Renato A.F. de Lima in Biodiversity & Conservation, vol 24 n° 9 (September 2015)
PermalinkRecommendations for the use of tree models to estimate national forest biomass and assess their uncertainty / Matieu Henry in Annals of Forest Science, vol 72 n° 6 (September 2015)
PermalinkDetection of fallen trees in ALS point clouds using a Normalized Cut approach trained by simulation / Przemyslaw Polewski in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)
PermalinkSite suitability for tree species: Is there a positive relation between a tree species’ occurrence and its growth? / Klara Dolos in European Journal of Forest Research, vol 134 n° 4 (July 2015)
PermalinkDetermination 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)
PermalinkAn improved species distribution model for Scots pine and downy oak under future climate change in the NW Italian Alps / Giorgio Vacchiano in Annals of Forest Science, vol 72 n° 3 (May 2015)
PermalinkDo competition-density rule and self-thinning rule agree? / Sonja Vospernik in Annals of Forest Science, vol 72 n° 3 (May 2015)
PermalinkLes données de l'inventaire forestier : état des lieux et évolution / Anonyme in Forêt entreprise, n° 222 (mai-juin 2015)
PermalinkPermalinkResponse of Swiss forests to management and climate change in the last 60 years / Meinrad Küchler in Annals of Forest Science, vol 72 n° 3 (May 2015)
PermalinkComparison of tree microhabitat abundance and diversity in the edges and interior of small temperate woodlands / Annie Ouin in Forest ecology and management, vol 340 (March 2015)
PermalinkForest inventory attribute estimation using airborne laser scanning, aerial stereo imagery, radargrammetry and interferometry–Finnish experiences of the 3D techniques / Markus Holopainen in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W4 (March 2015)
PermalinkBiomass estimation with high resolution satellite images: A case study of Quercus rotundifolia / Adelia M.O. Sousa in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)
PermalinkHabitat directive forest type western taiga (*9010) in Estonia : the first description of stand structure according to mapping and monitoring data / Anneli Palo in Baltic forestry, vol 21 n° 1 ([01/02/2015])
PermalinkActes des secondes rencontres végétales du massif central : flore, végétation et habitats du massif central / Conservatoire botanique national du Massif central (2015)
PermalinkAssessing forest inventory information obtained from different inventory approaches and remote sensing data sources / Even Bergseng in Annals of Forest Science, vol 72 n° 1 (January 2015)
PermalinkPermalinkComparison of methods toward multi-scale forest carbon mapping and spatial uncertainty analysis: combining national forest inventory plot data and landsat TM images / Andrew L. Fleming in European Journal of Forest Research, vol 134 n° 1 (January 2015)
PermalinkEnvironmental, spatial and temporal drivers of plant community composition in British forest habitat / Adam Robert Kimberley (2015)
PermalinkUne gestion mieux adaptée sur la piste d’un inventaire forestier multi-sources / Jean-Marc Frémont in Forêts de France, n° 580 (janvier/février 2015)
PermalinkModalités de représentation en 3D de données issues du SIG2D, pour la conception et la simulation / Olivier Jest (2015)
PermalinkPast, present, and future of forest accounting: an overview of the French experience / Alexandra Niedzwiedz in Annals of Forest Science, vol 72 n° 1 (January 2015)
PermalinkPermalinkUse of remotely sensed auxiliary data for improving sample-based forest inventories / Svetlana Saarela (2015)
PermalinkPTrees: A point-based approach to forest tree extraction from lidar data / Cédric Vega in International journal of applied Earth observation and geoinformation, vol 33 (December 2014)
PermalinkTracking seasonal changes of leaf and canopy light use efficiency in a Phlomis fruticosa Mediterranean ecosystem using field measurements and multi-angular satellite hyperspectral imagery / S. Stagakis in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)
PermalinkDistribution, données floristiques et architecture des boisements du delta du Rhône (sud-est de la France) / Annik Schnitzler in Ecologia mediterranea, vol 40 n° 2 (2014)
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PermalinkAn improved dark object method to retrieve 500 m-resolution AOT (Aerosol Optical Thickness) image from MODIS data: A case study in the Pearl River Delta area, China / Lili Li in ISPRS Journal of photogrammetry and remote sensing, vol 89 (March 2014)
PermalinkAssessing changes in species distribution from sequential large-scale forest inventories / Laura Hernandez in Annals of Forest Science, vol 71 n° 2 (March 2014)
PermalinkSpatial patterns of historical growth changes in Norway spruce across western European mountains and the key effect of climate warming / Marie Charru in Trees, vol 28 n° 1 (February 2014)
PermalinkEtude des habitats naturels du Parc National du Mercantour (Alpes-Maritimes et Alpes de Haute-Provence), Partie 1. Rapport technique / Jérémie Van Es (2014)
PermalinkEtude des habitats naturels du Parc National du Mercantour (Alpes-Maritimes et Alpes de Haute-Provence), Partie 2. Clé de détermination des habitats / Jérémie Van Es (2014)
PermalinkEtude des habitats naturels du Parc National du Mercantour (Alpes-Maritimes et Alpes de Haute-Provence), Partie 3. Fiches «habitat» / Jérémie Van Es (2014)
PermalinkLa forêt en chiffres et en cartes / Institut national de l'information géographique et forestière (2012 -) (2014)
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PermalinkLa forêt luxembourgeoise en chiffres : Résultats de l'Inventaire Forestier National au Grand-Duché de Luxembourg 2009 - 2011 / Jacques Rondeux (2014)
PermalinkMarkov land cover change modeling using pairs of time-series satellite images / Priyakant Sinha in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 11 (November 2013)
PermalinkAssessing the effect of snow/water obstructions on the measurement of tree seedlings in a large-scale temperate forest inventory / C. W. Woodall in Forestry, an international journal of forest research, vol 86 n° 4 (October 2013)
PermalinkGround-based array for tomographic imaging of the tropical forest in P-band / Ho Tong Minh Dinh in IEEE Transactions on geoscience and remote sensing, vol 51 n° 8 (August 2013)
PermalinkEffects of national forest inventory plot location error on forest carbon stock estimation using k-nearest neighbor algorithm / Jaehoon Jung in ISPRS Journal of photogrammetry and remote sensing, vol 81 (July 2013)
PermalinkLe projet EMERGE pour des tarifs cohérents de volumes et biomasses des essences forestières françaises métropolitaines / Christine Deleuze in Rendez-vous techniques, n° 39-40 (Hiver-printemps 2013)
PermalinkSeeing the wood for the trees: Opentreemap is helping individuals, organisations and governments to collaborate in mapping, tending and preserving 'urban forest' / Deborah Boyer in GEO: Geoconnexion international, vol 12 n° 4 (april 2013)
PermalinkSoil water balance performs better than climatic water variables in tree species distribution modelling / Christian Piedallu in Global ecology and biogeography, vol 22 n° 4 (April 2013)
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PermalinkAnalysis of desertification in the Upper East Region (UER) of Ghana using remote sensing, field study, and local knowledge / Alex B. Owusu in Cartographica, vol 48 n° 1 (March 2013)
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