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végétation
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plante non vasculaire, plante vasculaire, règne végétal, trachéophyte, végétation, végétaux. >> botanique. >>Terme(s) spécifique(s) : cormophyte, thallophyte. Source(s) : Chadefaud, 1960. Equiv. LCSH : Plants. Domaine(s) : 580. |
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Error assessment in two lidar-derived TIN datasets / M.H. Peng in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 8 (August 2006)
[article]
Titre : Error assessment in two lidar-derived TIN datasets Type de document : Article/Communication Auteurs : M.H. Peng, Auteur ; T.Y. Shih, Auteur Année de publication : 2006 Article en page(s) : pp 933 - 947 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] canopée
[Termes IGN] classification dirigée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] erreur de mesure
[Termes IGN] estimation statistique
[Termes IGN] modèle numérique de surface
[Termes IGN] occupation du sol
[Termes IGN] pente
[Termes IGN] point de vérification
[Termes IGN] précision des données
[Termes IGN] rugosité
[Termes IGN] rugosité du sol
[Termes IGN] semis de points
[Termes IGN] Triangulated Irregular Network
[Termes IGN] variabilité
[Termes IGN] végétationRésumé : (Auteur) An accuracy assessment of two lidar-derived elevation datasets was conducted in areas of rugged terrain (average slope 26.6°). Data from 906 ground checkpoints in various land-cover types were collected in situ as reference points. Analysis of the accuracy of lidar-derived elevation as a function of several factors including terrain slope, terrain aspect, and land-cover types was conducted. This paper attempts to characterize vegetation information derived from lidar data based on variables such as canopy volume, local roughness of point clouds, point spacing of lidar ground returns, and vegetation angle. This information was used to evaluate the accuracy of elevation as a function of vegetation type. The experimental results revealed that the accuracy of elevation was considerably correlated with five factors: terrain slope, vegetation angle, canopy volume, local roughness of point clouds, and point spacing of lidar ground returns. The results show a linear relationship between the elevation accuracy and the combination of vegetation angle and the point spacing of ground returns (r2 > 0.9). The combination of vegetation angle and point spacing of ground returns explains a significant amount of the variability in elevation accuracy. Elevation accuracy varied with different vegetation types. The elevation accuracy was also linearly correlated with the product of the point spacing of ground returns and the tangent of the slope (r2 = 0.9). A greater product value implies a greater elevation error. In addition, with regard to terrain aspect, one dense dataset with extra cross-flight data revealed a lesser impact of aspect on elevation accuracy. Copyright ASPRS Numéro de notice : A2006-312 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.72.8.933 En ligne : https://doi.org/10.14358/PERS.72.8.933 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28036
in Photogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 8 (August 2006) . - pp 933 - 947[article]Subpixel analysis of Landsat ETM/sup +/ using self-organizing map (SOM) neural networks for urban land cover characterization / S. Lee in IEEE Transactions on geoscience and remote sensing, vol 44 n° 6 (June 2006)
[article]
Titre : Subpixel analysis of Landsat ETM/sup +/ using self-organizing map (SOM) neural networks for urban land cover characterization Type de document : Article/Communication Auteurs : S. Lee, Auteur ; R.G. Lathrop, Auteur Année de publication : 2006 Article en page(s) : pp 1642 - 1654 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse infrapixellaire
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] apprentissage automatique
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte de Kohonen
[Termes IGN] image Ikonos
[Termes IGN] image Landsat-ETM+
[Termes IGN] surface imperméable
[Termes IGN] végétation
[Termes IGN] zone urbaineRésumé : (Auteur) This paper examines the subpixel analysis of Landsat ETM+ data to estimate the percent cover of impervious surface, lawn, and woody tree cover in typical urban/suburban land-scapes. By combining Self-Organizing Map (SOM), Learning Vector Quantization (LVQ), and Gaussian Mixture Model (GMM) methods, the posterior probability of the various land cover components were estimated for each pixel as a means of sub-pixel analysis. The estimation of impervious surface and the differentiation of urban vegetation grass versus woody tree coverage the main objectives of this paper. Overall, the output estimates compared favorably with those obtained using higher spatial resolution aerial photograph and IKONOS satellite image and traditional hard classification techniques as independent reference. The SOM-LVQ-GMM mode! showed a moderate degree of similarity in the estimates of impervious surface [root mean-square errors (RMSEs) of Numéro de notice : A2006-261 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.869984 En ligne : https://doi.org/10.1109/TGRS.2006.869984 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27988
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 6 (June 2006) . - pp 1642 - 1654[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-06061 RAB Revue Centre de documentation En réserve L003 Disponible Detecting vegetation changes in a wetland area in Northern Germany using earth observation and geodata / Konstanze Kleinod in Journal for nature conservation, vol 13 n° 2-3 (July 2005)
[article]
Titre : Detecting vegetation changes in a wetland area in Northern Germany using earth observation and geodata Type de document : Article/Communication Auteurs : Konstanze Kleinod, Auteur ; Michael Wissen, Auteur ; Michaël Bock, Auteur Année de publication : 2005 Article en page(s) : pp 115 - 125 Note générale : biblographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Allemagne
[Termes IGN] carte de la végétation
[Termes IGN] détection de changement
[Termes IGN] image aérienne
[Termes IGN] image Landsat-TM
[Termes IGN] restauration du milieu naturel
[Termes IGN] végétation
[Termes IGN] zone humideRésumé : (auteur) Monitoring land use and landscape dynamics in conservation areas is important to understand and influence nature and restoration processes. Earth observation data can help to detect changes automatically in extensive areas. In a wetland area in Northern Germany different change detection methods have been tested to detect wetland restoration processes, especially succession of wetland and moorland vegetation over 11 years. Therefore a change detection method based on a selective principal component analysis followed by a fuzzy membership function introduced by Weiers et al. (2001). was tested with dual date Landsat TM/ETM+ images. As comparison vegetation maps and Colour-infrared (CIR)-aerial photographs were analysed. The main objectives were to find out (1) if changes, especially vegetation changes, can be detected on the study area by the method as described by Weiers et al. (2001), (2) which changes can be detected and (3) which is the best method on the study area, respectively: the Landsat change detection method, the analysis of vegetation maps or the interpretation of CIR-aerial photographs. For detecting vegetation changes the most detailed information were achieved by interpreting CIR-aerial photographs, while the Landsat change detection method turned out to be more suitable for detecting changes of wetness. Numéro de notice : A2005-009 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jnc.2005.01.004 Date de publication en ligne : 23/01/2005 En ligne : http://dx.doi.org/10.1016/j.jnc.2005.01.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81062
in Journal for nature conservation > vol 13 n° 2-3 (July 2005) . - pp 115 - 125[article]Estimation and monitoring of bare soil/vegetation ratio with SPOT vegetation and HRVIR / Grégoire Mercier in IEEE Transactions on geoscience and remote sensing, vol 43 n° 2 (February 2005)
[article]
Titre : Estimation and monitoring of bare soil/vegetation ratio with SPOT vegetation and HRVIR Type de document : Article/Communication Auteurs : Grégoire Mercier, Auteur ; Fernand Verger, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 348 - 354 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] agriculture
[Termes IGN] analyse multiéchelle
[Termes IGN] carte de Kohonen
[Termes IGN] classification par réseau neuronal
[Termes IGN] estimation statistique
[Termes IGN] image à haute résolution
[Termes IGN] image SPOT-HRVIR
[Termes IGN] image SPOT-Végétation
[Termes IGN] occupation du sol
[Termes IGN] pollution des eaux
[Termes IGN] réalité de terrain
[Termes IGN] sol nu
[Termes IGN] surface cultivée
[Termes IGN] surveillance agricole
[Termes IGN] végétationRésumé : (Auteur) Covering soils with vegetation during the fallow and planting seasons is one of the main ways to reduce water pollution, by restricting pollutant fluxes to aquatic systems. The bare soil/vegetation ratio monitoring can be carried out daily with a coarse spatial resolution using SPOT VEGETATION (1 km). Nevertheless, land-cover changes detected at a regional scale with this ratio may be due to winter vegetation cover changes as well as the influence of climatic events. Therefore, observed changes have to be validated from a local-scale analysis with higher spatial resolution data. The aim of this study is to develop a technique that allows high or low variations detected at a regional scale to be assessed from SPOT VEGETATION images with data acquired at a higher scale, SPOT High Resolution Visible and Infrared images in our case. In this study, the link between the images from the two sensors is achieved from the design of an artificial neural network method based on a Kohonen self-organizing map. The originality of this method lies in the use of external knowledge from ground observations and the use of temporal behavior to solve such a change of scale. Results of testing this method by using a potential change map based on the last few years' land-cover observations have shown a good correspondence between the observed and predicted bare soil/vegetation balance with regards to the spatial resolution difference between the two sensors. Numéro de notice : A2005-102 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/IGARSS.2003.1294745 En ligne : https://doi.org/10.1109/IGARSS.2003.1294745 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27240
in IEEE Transactions on geoscience and remote sensing > vol 43 n° 2 (February 2005) . - pp 348 - 354[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-05022 RAB Revue Centre de documentation En réserve L003 Disponible 065-05021 RAB Revue Centre de documentation En réserve L003 Disponible Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery / C. Wu in Remote sensing of environment, vol 93 n° 4 (15/12/2004)
[article]
Titre : Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery Type de document : Article/Communication Auteurs : C. Wu, Auteur Année de publication : 2004 Article en page(s) : pp 480 - 492 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] Colombus (Ohio)
[Termes IGN] contrôle par télédétection
[Termes IGN] image Landsat-ETM+
[Termes IGN] impact sur l'environnement
[Termes IGN] milieu urbain
[Termes IGN] surface imperméable
[Termes IGN] utilisation du sol
[Termes IGN] variable biophysique (végétation)
[Termes IGN] végétationRésumé : (Auteur) With rapid urban growth in recent years, understanding urban biophysical composition and dynamics becomes an important research topic. Remote sensing technologies introduce a potentially scientific basis for examining urban composition and monitoring its changes over time. The vegetation-impervious surface-soil (V-I-S) model, in particular, provides a foundation for describing urban/suburban environments and a basis for further urban analyses including urban growth modeling, environmental impact analysis, and socioeconomic factor estimation. This paper develops a normalized spectral mixture analysis (NSMA) method to examine urban composition in Columbus (Ohio) using Landsat ETM+ data. In particular, a brightness normalization method is applied to reduce brightness variation. Through this normalization, brightness variability within each V-I-S component is reduced or eliminated, thus allowing a single endmember representing each component. Further, with the normalized image, three endmembers, vegetation, impervious surface, and soil, are chosen to model heterogeneous urban composition using a constrained spectral mixture analysis (SMA) model. The accuracy of impervious surface estimation is assessed and compared with two other existing models. Results indicate that the proposed model is a better alternative to existing models, with a root mean square error (RMSE) of 10.1% for impervious surface estimation in the study area. Numéro de notice : A2004-461 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.08.003 En ligne : https://doi.org/10.1016/j.rse.2004.08.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26981
in Remote sensing of environment > vol 93 n° 4 (15/12/2004) . - pp 480 - 492[article]Linking spatial patterns of bird and butterfly species richness with Landsat TM derived NDVI / K.C. Seto in International Journal of Remote Sensing IJRS, vol 25 n° 20 (October 2004)PermalinkUse of hyperspectral derivative ratios in the red-edge region to identify plant stress responses to gas leaks / K.L. Smith in Remote sensing of environment, vol 92 n° 2 (15/08/2004)PermalinkDTM generation from Ikonos in-track stereo images using a 3D physical model / Thierry Toutin in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 6 (June 2004)PermalinkTree model based eco-climatic vegetation classification and fuzzy mapping in diverse tropical deciduous ecosystems using multi-season NDVI / J. Krishnaswamy in International Journal of Remote Sensing IJRS, vol 25 n° 6 (March 2004)PermalinkReducing the dimensionality of plant spectral databases / I.E. Bell in IEEE Transactions on geoscience and remote sensing, vol 42 n° 3 (March 2004)PermalinkAnalysis of hyperspectral data for estimation of temperate forest canopy nitrogen concentration: Comparison between an Airborne (AVIRIS) and a spaceborne (Hyperion) sensor / M.L. Smith in IEEE Transactions on geoscience and remote sensing, vol 41 n° 6 (June 2003)PermalinkCreation of digital terrain models using an adaptative Lidar vegetation point removal process / G.T. Raber in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 12 (December 2002)PermalinkRelationship between plant spectral reflectances and their image tonal responses on aerial photographs / D.E. Escobar in Geocarto international, vol 17 n° 2 (June - August 2002)PermalinkAnalyse d'images aériennes haute résolution pour la reconstruction de scènes urbaines / Matthieu Cord in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 166 (Janvier 2002)PermalinkDiscrimination of arid vegetation with airborne multispectral scanner hyperspectral imagery / M. Lewis in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)Permalink