Descripteur
Termes IGN > sciences naturelles > sciences de la vie > biologie > botanique > formation végétale > forêt
forêt
Commentaire :
Bois (forêts), Boisé, Espace boisé, Espace forestier, Essence forestière, Forêt et sylviculture, Groupement forestier (écologie), Massif forestier, Milieu forestier, Peuplement forestier, Région forestière Ressource forestière, Zone forestière. Campagne, Espace naturel. >> Arbre, Archéologie des forêts, Écologie des forêts, Foresterie, Paysage forestier, Politique forestière, Produit forestier, Sylviculture. Voir aussi aux noms des forêts, par ex. : Fontainebleau, Forêt de (Seine-et-Marne) ; Bayerischer Wald (Allemagne). >>Terme(s) spécifique(s) : Biomasse des forêts, Canopée, Forêt domaniale, Forêt privée, Plante des forêts, Réserve forestière, Sol forestier, Station forestière -- Typologie. Source(s) : Grand Larousse universel . - Terminologie forestière / A. Métro, 1975. Equiv. LCSH : Forests and forestry. Domaine(s) : 577, 580. Synonyme(s)paysage forestierVoir aussi |
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Toward satellite-based land cover classification through optimum-path forest / Rodrigo José Pisani in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)
[article]
Titre : Toward satellite-based land cover classification through optimum-path forest Type de document : Article/Communication Auteurs : Rodrigo José Pisani, Auteur ; Rodrigo Yuji Mizobe Nakamura, Auteur ; Paulina Setti Riedel, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 6075 - 6085 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] forêt
[Termes IGN] occupation du solRésumé : (Auteur) Land cover classification has been paramount in the last years. Since the amount of information acquired by satellite on-board imaging systems has increased, there is a need for automatic tools that can tackle such problem. Despite the fact that one can find several works in the literature, we propose a novel methodology for land cover classification by means of the optimum-path forest (OPF) framework, which has never been applied to this context up to date. Experiments were conducted in supervised and unsupervised situations against some state-of-the-art pattern recognition techniques, such as support vector machines, Bayesian classifier, k-means, and mean shift. We had shown that supervised OPF can outperform such approaches, being much faster than all. In regard to clustering techniques, all classifiers have achieved similar results. Numéro de notice : A2014-483 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2294762 En ligne : https://doi.org/10.1109/TGRS.2013.2294762 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74066
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 10 tome 1 (October 2014) . - pp 6075 - 6085[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014101A RAB Revue Centre de documentation En réserve L003 Disponible Forêt et transition énergétique : la forêt, un sentier pour la transition énergétique et écologique / Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (2011 - 2019; France) (19/09/2014)
Titre : Forêt et transition énergétique : la forêt, un sentier pour la transition énergétique et écologique Type de document : Monographie Auteurs : Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (2011 - 2019; France), Auteur Editeur : Antony [France] : Institut national de recherche en sciences et technologies pour l’environnement et l’agriculture IRSTEA (2012-2019) Année de publication : 19/09/2014 Langues : Français (fre) Descripteur : [Termes IGN] forêt
[Termes IGN] surveillance écologique
[Vedettes matières IGN] Végétation et changement climatiqueNuméro de notice : 14696 Affiliation des auteurs : non IGN Thématique : FORET Nature : Recueil / ouvrage collectif En ligne : http://www.irstea.fr/nos-editions/dossiers/foret-transition-ecologique-energetiq [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73679 SIG nouveauté : un outil aux mains des propriétaires / Anonyme in Forêts de France, n° 576 (septembre 2014)
[article]
Titre : SIG nouveauté : un outil aux mains des propriétaires Type de document : Article/Communication Auteurs : Anonyme, Auteur Année de publication : 2014 Article en page(s) : p20 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] forêt
[Termes IGN] propriété foncière
[Termes IGN] système d'information géographiqueNuméro de notice : A2014-807 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74429
in Forêts de France > n° 576 (septembre 2014) . - p20[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité IFN-001-P001609 PER Revue Nogent-sur-Vernisson Salle périodiques Disponible An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data / Wei Zhuang in ISPRS Journal of photogrammetry and remote sensing, vol 95 (September 2014)
[article]
Titre : An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data Type de document : Article/Communication Auteurs : Wei Zhuang, Auteur ; Giorgos Mountrakis, Auteur Année de publication : 2014 Article en page(s) : pp 81 – 92 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] empreinte
[Termes IGN] filtrage numérique d'image
[Termes IGN] forêt
[Termes IGN] forme d'onde
[Termes IGN] groupe
[Termes IGN] identification automatique
[Termes IGN] onde lidar
[Termes IGN] surface du sol
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] traitement de donnéesRésumé : (Auteur) Large footprint waveform LiDAR sensors have been widely used for numerous airborne studies. Ground peak identification in a large footprint waveform is a significant bottleneck in exploring full usage of the waveform datasets. In the current study, an accurate and computationally efficient algorithm was developed for ground peak identification, called Filtering and Clustering Algorithm (FICA). The method was evaluated on Land, Vegetation, and Ice Sensor (LVIS) waveform datasets acquired over Central NY. FICA incorporates a set of multi-scale second derivative filters and a k-means clustering algorithm in order to avoid detecting false ground peaks. FICA was tested in five different land cover types (deciduous trees, coniferous trees, shrub, grass and developed area) and showed more accurate results when compared to existing algorithms. More specifically, compared with Gaussian decomposition, the RMSE ground peak identification by FICA was 2.82 m (5.29 m for GD) in deciduous plots, 3.25 m (4.57 m for GD) in coniferous plots, 2.63 m (2.83 m for GD) in shrub plots, 0.82 m (0.93 m for GD) in grass plots, and 0.70 m (0.51 m for GD) in plots of developed areas. FICA performance was also relatively consistent under various slope and canopy coverage (CC) conditions. In addition, FICA showed better computational efficiency compared to existing methods. FICA’s major computational and accuracy advantage is a result of the adopted multi-scale signal processing procedures that concentrate on local portions of the signal as opposed to the Gaussian decomposition that uses a curve-fitting strategy applied in the entire signal. The FICA algorithm is a good candidate for large-scale implementation on future space-borne waveform LiDAR sensors. Numéro de notice : A2014-474 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74051
in ISPRS Journal of photogrammetry and remote sensing > vol 95 (September 2014) . - pp 81 – 92[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014091 RAB Revue Centre de documentation En réserve L003 Disponible Assessing 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)
[article]
Titre : Assessing the potential for leaf-off LiDAR data to model canopy closure in temperate deciduous forests Type de document : Article/Communication Auteurs : Jason R. Parent, Auteur ; John C. Volin, Auteur Année de publication : 2014 Article en page(s) : pp 134 – 145 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] feuillu
[Termes IGN] forêt
[Termes IGN] objectif grand angulaire
[Termes IGN] photographie aérienne
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) Estimates of canopy closure have many important uses in forest management and ecological research. Field measurements, however, are typically not practical to acquire over expansive areas or for large numbers of locations. This problem has been addressed, in recent years, through the use of airborne light detection and ranging (LiDAR) technology which has proven effective in modeling canopy closure remotely. The techniques developed to use LiDAR for this purpose have been designed and evaluated for datasets acquired during leaf-on conditions. However, a large number of LiDAR datasets are acquired during leaf-off conditions since their primary purpose is to generate bare-earth Digital Elevation Models. In this paper, we develop and evaluate techniques for leveraging small-footprint leaf-off LiDAR data to model leaf-on canopy closure in temperate deciduous forests.
We evaluate three techniques for modeling canopy closure: (1) the canopy-to-total-return-ratio (CTRR), (2) the canopy-to-total-pixel-ratio (CTPR), and (3) the hemispherical-viewshed (HV). The first technique has been used widely, in various forms, and has been shown to be effective with leaf-on LiDAR datasets. The CTRR technique that we tested uses the first-return LiDAR data only. The latter two techniques are new contributions that we develop and present in this paper. These techniques use Canopy Height Models (CHM) to detect significant gaps in the forest canopy which are of primary importance in estimating closure.
The techniques we tested each showed good promise for predicting canopy closure using leaf-off LiDAR data with the CTPR and HV models having particularly high correlations with closure estimates from hemispherical photographs. The CTRR model had performance on par with results from previous studies that used leaf-on LiDAR, although, with leaf-off data the model tended to be negatively biased with respect to species having simple and compound leaf types and positively biased for coniferous species. The CTPR and HV models also showed some slight negative biases for compound-leaf species. The biases for the CTPR and HV models were mitigated when the CHM data were smoothed to fill in small gaps. The CHM-based models were robust to changes in the CHM model resolution which suggests that these methods may be applicable to a variety of small-footprint LiDAR datasets. In this research, the new CTPR and HV methods showed a strong ability to predict canopy closure using leaf-off data, however, future work will be needed to test the applicability of the models to variations in LiDAR datasets, forest types, and topography.Numéro de notice : A2014-477 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.009 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74054
in ISPRS Journal of photogrammetry and remote sensing > vol 95 (September 2014) . - pp 134 – 145[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014091 RAB Revue Centre de documentation En réserve L003 Disponible Comparison of airborne laser scanning methods for estimating forest structure indicators based on Lorenz curves / Rubén Valbuena in ISPRS Journal of photogrammetry and remote sensing, vol 95 (September 2014)PermalinkCross-correlation of diameter measures for the co-registration of forest inventory plots with airborne laser scanning data / Jean-Matthieu Monnet in Forests, vol 5 n° 9 (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)PermalinkVolet forestier de la loi d'avenir pour l'agriculture, l'alimentation et la forêt (loi n° 2014-1170 du 13 octobre 2014) / Jean-Luc Guitton in Revue forestière française, vol 66 n° 5 (septembre - octobre 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)PermalinkLe climat change, vite, trop vite ... comment aider les arbres à le suivre ? / Hervé Le Bouler in Forêt entreprise, n° 217 (juillet-août 2014)PermalinkLa forêt privée en 2060 : quelques éléments de prospective / Thomas Formery in Forêt entreprise, n° 217 (juillet-août 2014)PermalinkAn inventory of the above ground biomass in the Mau Forest Ecosystem, Kenya / Mwangi James Kinyanjui in Open journal of forestry, vol 4 n° 10 (July 2014)PermalinkApproche de détermination de signature de texture : application à la classification de couverts forestiers d’image satellitaire à haute résolution / Wala Zaaboub in Revue Française de Photogrammétrie et de Télédétection, n° 207 (Juillet 2014)PermalinkChampagne-Ardenne : valorisation d'une filière feuillue d'excellence / Anonyme in Forêts de France, n° 575 (jullet-août 2014)PermalinkGML-based data management and semantic world modelling for a 4D forest simulation and information system / Jürgen Roβmann in International journal of 3-D information modeling, vol 3 n° 3 (July- September 2014)PermalinkLe massif forestier des Landes de Gascogne, un patrimoine naturel ? Le regard des gestionnaires / Aude Pottier in Annales de géographie, n° 698 (juillet - août 2014)Permalinkn° 33 - Juin 2014 - Forêt et changements climatiques : apports des données d'inventaire IGN (Bulletin de L'if) / Stéphanie WurpillotPermalinkManaging coppice forests for rockfall protection: lessons from modeling / Anna Radkte in Annals of Forest Science, vol 71 n° 4 (June 2014)PermalinkSignificance analysis of different types of ancillary geodata utilized in a multisource classification process for forest identification in Germany / Michael Förster in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)PermalinkThinning has a positive effect on growth dynamics and growth-climate relationships in Aleppo pine (Pinus halepensis) tree of different crown classes / Jorge Olivar in Annals of Forest Science, vol 71 n° 3 (April - May 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)PermalinkVolume et structure des peuplements en forêt privée / Gilles Brouillet in Forêt entreprise, n° 215 (mars - avril 2014)PermalinkClimate change impacts in European forests: the expert views of local observers / Peter Spathelf in Annals of Forest Science, vol 71 n° 2 (March 2014)PermalinkLe positionnement par satellite : les nouveaux récepteurs améliorent-ils les performances sous couvert forestier ? / Alain Munoz in Rendez-vous techniques, n° 43 (Mars 2014)PermalinkUS strategy for forest management adaptation to climate change: building a framework for decision making / V. Alaric Sample in Annals of Forest Science, vol 71 n° 2 (March 2014)PermalinkUn vaste champ d'applications / Françoise de Blomac in DécryptaGéo le mag, n° 155 (01/03/2014)PermalinkDetecting subcanopy invasive plant species in tropical rainforest by integrating optical and microwave (InSAR/PolInSAR) remote sensing data, and a decision tree algorithm / Abduwasit Ghulam in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkThe potential of the greenness and radiation (GR) model to interpret 8-day gross primary production of vegetation / Chaoyang Wu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkBasal area and biomass estimates of loblolly pine stands using L-band UAVSAR / William L. 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