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Termes IGN > télédétection
télédétection
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Télédétection aérospatiale Télédétection par satellite Télédétection satellitaire Télédétection spatiale Appareils enregistreurs >> Agriculture de précision Capteurs (technologie) Photogrammétrie aérienne Photographie aérienne >>Terme(s) spécifique(s) : Télédétection en sciences de la Terre Cartographie radar Traitement d'images -- Techniques numériques Images de télédétection Radar à antenne synthétique Radar en sciences de la Terre Reconnaissance aérienne Satellites artificiels en télédétection Satellites de télédétection des ressources terrestres SPOT (satellites de télédétection) Surveillance électronique Télédétection hyperfréquence Télémesure spatiale Thermographie Equiv. LCSH : Remote sensing Domaine(s) : 500; 600 |
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Du nuage de points à la représentation 3D avec PostGIS / Tom Van Tilburg in Géomatique expert, n° 113 (novembre - décembre 2016)
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Titre : Du nuage de points à la représentation 3D avec PostGIS Type de document : Article/Communication Auteurs : Tom Van Tilburg, Auteur Année de publication : 2016 Article en page(s) : pp 21 - 22 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] données lidar
[Termes IGN] données multitemporelles
[Termes IGN] représentation cartographique 3D
[Termes IGN] semis de points
[Termes IGN] stockage de donnéesRésumé : (Auteur) [Introduction] Une fois que les nuages de points sont stockés dans la base de données, comment faire pour les exploiter et en tirer, par exemple, des modèles 3D ? La question est particulièrement importante pour un pays comme les Pays Bas où, tous les six/sept ans, le gouvernement fait réaliser un survol LIDAR complet du territoire et publie un nuage de points classifié d'une densité de huit points par mètre carré. [...] Numéro de notice : A2016-961 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83621
in Géomatique expert > n° 113 (novembre - décembre 2016) . - pp 21 - 22[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 265-2016061 RAB Revue Centre de documentation En réserve L003 Disponible IFN-001-P001918 PER Revue Nogent-sur-Vernisson Salle périodiques Exclu du prêt Quantifying early-seral forest composition with remote sensing / Rayma A Cooley in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 11 (November 2016)
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Titre : Quantifying early-seral forest composition with remote sensing Type de document : Article/Communication Auteurs : Rayma A Cooley, Auteur ; Peter T. Wolter, Auteur ; Brian R. Sturtevant, Auteur Année de publication : 2016 Article en page(s) : pp 853 - 863 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] données de terrain
[Termes IGN] incendie de forêt
[Termes IGN] Populus tremula
[Termes IGN] prédiction
[Termes IGN] surface terrière
[Termes IGN] télédétection
[Termes IGN] teneur en carbone
[Termes IGN] troncRésumé : (Auteur) Spatially explicit modeling of recovering forest structure within two years following wildfire disturbance has not been attempted, yet such knowledge is critical for determining successional pathways. We used remote sensing and field data, along with digital climate and terrain data, to model and map early-seral aspen structure and vegetation species richness following wildfire. Richness was the strongest model (rmse = 2.47 species, Adj. R2 = 0.60), followed by aspen stem diameter, basal area (ba), height, density, and percent cover (Adj. R2 range = 0.22 to 0.53). Effects of pre-fire aspen ba and fire severity on post-fire aspen structure and richness were analyzed. Post-fire recovery attributes were not significantly related to fire severity, while all but percent cover and richness were sensitive to pre-fire aspen ba (Adj. R2 range = 0.12 to 0.33, p Numéro de notice : A2016-945 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.11.853 En ligne : http://dx.doi.org/10.14358/PERS.82.11.853 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83437
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 11 (November 2016) . - pp 853 - 863[article]Influence of tree species complexity on discrimination performance of vegetation indices / Azadeh Ghiyamat in European journal of remote sensing, vol 49 n° 1 (2016)
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Titre : Influence of tree species complexity on discrimination performance of vegetation indices Type de document : Article/Communication Auteurs : Azadeh Ghiyamat, Auteur ; Helmi Zulhaidi Mohd Shafri, Auteur ; Abdul Rashid Mohamed Shariff, Auteur Année de publication : 2016 Article en page(s) : pp 15 - 37 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] analyse discriminante
[Termes IGN] espèce végétale
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] information complexe
[Termes IGN] Pinus nigra corsicana
[Termes IGN] Pinus sylvestris
[Termes IGN] test de performanceRésumé : (auteur) Performance of different vegetation indices (VIs) in combination with single- and multipleendmember (SEM and MEM) for discriminating Corsican and Scots pines with different ages and Broadleaves tree species is demonstrated by using an airborne hyperspectral data. The analysis is performed in three different complexity levels. The results show by increasing tree species complexity, overall accuracy significantly reduced. An overall accuracy up to 90% is obtained from the first category with the least complexity; however, it is reduced to 55% in the third category with the highest complexity. By employing MEM, performance of normalized difference vegetation index (NDVI) is increased by 10%. Numéro de notice : A2016-834 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.5721/EuJRS20164902 En ligne : http://dx.doi.org/10.5721/EuJRS20164902 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82723
in European journal of remote sensing > vol 49 n° 1 (2016) . - pp 15 - 37[article]Vegetation effects modeling in soil moisture retrieval using MSVI / Mina Moradizadeh in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 10 (October 2016)
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Titre : Vegetation effects modeling in soil moisture retrieval using MSVI Type de document : Article/Communication Auteurs : Mina Moradizadeh, Auteur ; Mohammad R. Saradjian, Auteur Année de publication : 2016 Article en page(s) : pp 803 - 810 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] humidité du sol
[Termes IGN] image multicapteur
[Termes IGN] indice de végétation
[Termes IGN] itération
[Termes IGN] température au sol
[Termes IGN] température de luminanceRésumé : (Auteur) Brightness temperature (BT) measured by passive microwave sensors is usually affected by soil moisture, vegetation cover, and soil roughness. Soil moisture estimates have been limited to regions that had either bare soil or low to moderate amounts of vegetation cover.
In this study, Simultaneous Land Parameters Retrieval Model (SLPRM) as an iterative least-squares minimization method has been used. This algorithm retrieves surface soil moisture, land surface temperature, and canopy temperature simultaneously using brightness temperature data in bare soil, low to moderate and higher amounts of vegetation cover.
Furthermore, a new index called MSVI (Multi Sensor Vegetation Index) has been introduced to approximate vegetation effects on properly observed brightness temperatures. The algorithm includes model construction, calibration, and validation using observations carried out for the SMEX03 (Soil Moisture Experiment 2003) region in the South and North of Oklahoma. The results indicated about 0.9 percent improvement on soil moisture estimation accuracy using the MSVI.Numéro de notice : A2016-935 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.10.803 En ligne : http://dx.doi.org/10.14358/PERS.82.10.803 Format de la ressource électronique : URL artilce Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83349
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 10 (October 2016) . - pp 803 - 810[article]Lidar detection of individual tree size in tropical forests / António Ferraz in Remote sensing of environment, vol 183 (15 September 2016)
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Titre : Lidar detection of individual tree size in tropical forests Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Sassan Saatchi, Auteur ; Clément Mallet
, Auteur ; Victoria Meyer, Auteur
Année de publication : 2016 Projets : 1-Pas de projet / Article en page(s) : pp 318 - 333 Note générale : Bibliographie
António Ferraz's research was supported by an appointment to the NASA Postdoctoral Program at the Jet Propulsion Laboratory, administrated by Oak Ridge Associated Universities under contract with NASA(grant number NNH15CO48B).Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] allométrie
[Termes IGN] arbre (flore)
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] Panama
[Termes IGN] semis de points
[Termes IGN] télédétection aérienneRésumé : (Auteur) Characterization of tropical forest trees has been limited to field-based techniques focused on measurement of diameter of the cylindrical part of the bole, with large uncertainty in measuring large trees with irregular shapes, and other size attributes such as total tree height and the crown size. Here, we introduce a methodology to decompose lidar point cloud data into 3D clusters corresponding to individual tree crowns (ITC) that enables the estimation of many biophysical variables of tropical forests such as tree height, crown area, crown volume, and tree number density. The ITC-based approach was tested using airborne high-resolution lidar data collected over the 50-ha Center for Tropical Forest Science (CTFS) plot in the Barro Colorado Island, Panama. The lack of tree height and crown size measurements in the field prohibits the direct validation of the ITC metrics. We assess the reliability of our method by comparing the aboveground biomass (AGB) estimated using ground and lidar individual tree measurements at multiple spatial scales, namely 1ha, 2.25 ha, 4ha, and 6.25 ha. We examined four different lidar-derived AGB models, with three based on individual tree height, crown volume, and crown area, and one with mean top canopy height (TCH) calculated at the plot level using the lidar canopy height model. Results show that the predictive power of all models based on ITC size and TCH increases with decreasing spatial resolution from16.9% at 1ha for the worst model to 5.0% at 6.25ha for the best model. The TCH-based model performed slightly better than ITC-based models except at higher spatial scales (~4 ha) and when errors due to edge effects associated with tree crowns were reduced. Unlike the TCH models that change regionally depending on forest type and structure allometry, the ITC-based models are derived as a function of individual tree allometry and can be extended globally to all tropical forests. The method for lidar detection of individual crown size overcome some limitations of ground-based inventories such as 1) it is able to access crowns of large trees and 2) it enables the assessment of directional changes in tree density, canopy architecture and forest dynamics over large and inaccessible areas to support robust tropical ecological studies. Numéro de notice : A2016--103 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2016.05.028 Date de publication en ligne : 21/06/2016 En ligne : http://doi.org/10.1016/j.rse.2016.05.028 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84669
in Remote sensing of environment > vol 183 (15 September 2016) . - pp 318 - 333[article]CHP toolkit : case study of LAIe sensitivity to discontinuity of canopy cover in fruit plantations / Karolina D. Fieber in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
PermalinkCorrection of ZY-3 image distortion caused by satellite jitter via virtual steady reimaging using attitude data / Mi Wang in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
PermalinkEstimating the solar transmittance of urban trees using airborne LiDAR and radiative transfer simulation / Haruki Oshio in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
PermalinkImproving winter leaf area index estimation in coniferous forests and its significance in estimating the land surface albedo / Rong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
PermalinkRetrieval of leaf area index in different plant species using thermal hyperspectral data / Elnaz Neinavaz in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
PermalinkA simulated annealing algorithm for zoning in planning using parallel computing / Inès Santé in Computers, Environment and Urban Systems, vol 59 (September 2016)
PermalinkTracking the seasonal dynamics of boreal forest photosynthesis using EO-1 hyperion reflectance : sensitivity to structural and illumination effects / Rocío Hernández-Clemente in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
PermalinkApport des images THRS pour la catégorisation des agro-systèmes complexes à Mayotte / Rafaël Molina in Géomatique expert, n° 111 (juillet- août 2016)
PermalinkA general variational framework considering cast shadows for the topographic correction of remote sensing imagery / Huifang Li in ISPRS Journal of photogrammetry and remote sensing, vol 117 (July 2016)
PermalinkA manifold alignment approach for hyperspectral image visualization with natural color / Danping Liao in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)
PermalinkRelationship between landform classification and vegetation (case study: southwest of Fars province, Iran) / Marzieh Mokarram in Open geosciences, vol 8 n° 1 (January - July 2016)
PermalinkScale effect in indirect measurement of leaf area index / Guangjian Yan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)
PermalinkA simple method for detecting phenological change from time series of vegetation index / Jin Chen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)
PermalinkThermal infrared reveals vegetation stress / Thomas A. Groen in GIM international, vol 30 n° 6 (June 2016)
PermalinkAn iterative haze optimized transformation for automatic cloud/haze detection of landsat imagery / Shuli Chen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 5 (May 2016)
PermalinkAssessing the planimetric accuracy of historical maps (sixteenth to nineteenth centuries): new methods and potential for coastal landscape reconstruction / Iason Jongepier in Cartographic journal (the), Vol 53 n° 2 (May 2016)
PermalinkDeveloping the information infrastructure based on LADM – the case of Poland / K. J. Góźdź in Survey review, vol 48 n° 348 (May 2016)
PermalinkGenerative models for road network reconstruction / Colin Kuntzsch in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)
PermalinkHigh-precision positioning of radar scatterers / Prabu Dheenathayalan in Journal of geodesy, vol 90 n° 5 (May 2016)
PermalinkInformation from imagery: ISPRS scientific vision and research agenda / Jun Chen in ISPRS Journal of photogrammetry and remote sensing, vol 115 (May 2016)
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