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Real-time atmospheric correction of AVIRIS-NG imagery / Brian D. Bue in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)
[article]
Titre : Real-time atmospheric correction of AVIRIS-NG imagery Type de document : Article/Communication Auteurs : Brian D. Bue, Auteur ; David R. Thompson, Auteur ; Michael Eastwood, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 6419 - 6428 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] correction atmosphérique
[Termes IGN] image aérienne
[Termes IGN] image AVIRIS
[Termes IGN] image proche infrarouge
[Termes IGN] modèle stéréoscopique
[Termes IGN] temps réelRésumé : (auteur) We demonstrate real-time model-based atmospheric correction onboard the Next Generation Airborne Visible/Infrared Imaging Spectrometer. We achieve a reduction in processing time from hours or days to seconds by modifying a standard physics-based atmospheric correction algorithm to support real-time execution. We achieved this reduction by modifying the physics-based ATmospheric REMoval algorithm to leverage a large lookup table of precomputed scattering and transmission coefficients, indexed by parameters specifying the aircraft operating conditions at capture time. Interpolation among the precomputed coefficients allows surface reflectance retrieval at the sensor acquisition rate of 500 Mb/s. Our system produced science-quality reflectance products during over 30 test flights and, to our knowledge, is the first reported demonstration of real-time model-driven visible shortwave infrared atmospheric correction onboard an aircraft. Numéro de notice : A2015-841 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2439215 Date de publication en ligne : 23/06/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2439215 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79185
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 12 (December 2015) . - pp 6419 - 6428[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2015121 SL Revue Centre de documentation Revues en salle Disponible Road vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation / Fateme Ameri in Photogrammetric record, vol 30 n° 152 (December 2015 - February 2016)
[article]
Titre : Road vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation Type de document : Article/Communication Auteurs : Fateme Ameri, Auteur ; Mohammad Javad Valadan Zoej, Auteur Année de publication : 2015 Article en page(s) : pp 363 - 386 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification automatique d'objets
[Termes IGN] extraction automatique
[Termes IGN] extraction du réseau routier
[Termes IGN] image aérienne
[Termes IGN] image Ikonos
[Termes IGN] image Quickbird
[Termes IGN] optimisation par essaim de particules
[Termes IGN] réseau routier
[Termes IGN] vectorisationRésumé : (auteur) This paper introduces an innovative automatic road-vectorisation algorithm based on dynamic pixel clustering using particle swarm optimisation. A new cost function is designed to optimise the number and position of road keypoints and is capable of deriving road centrelines without considering geometric, spectral or topological characteristics in the road model. The algorithm is applied to different high-resolution images (IKONOS, QuickBird and aerial photographs) and is evaluated with respect to RMSE, correctness and completeness. Moreover, a new quality parameter is defined to evaluate a “kinking” effect in roads. Extraction of different road shapes with an acceptable precision in both urban and rural environments proves the efficiency of the algorithm in yielding complete road networks. Numéro de notice : A2015-827 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12123 Date de publication en ligne : 15/12/2015 En ligne : https://doi.org/10.1111/phor.12123 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79123
in Photogrammetric record > vol 30 n° 152 (December 2015 - February 2016) . - pp 363 - 386[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 106-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Discrimination of deciduous tree species from time series of unmanned aerial system imagery / Jonathan Lisein in Plos one, vol 10 n° 11 (November 2015)
[article]
Titre : Discrimination of deciduous tree species from time series of unmanned aerial system imagery Type de document : Article/Communication Auteurs : Jonathan Lisein , Auteur ; Adrien Michez, Auteur ; Hugues Claessens, Auteur ; Philippe Lejeune, Auteur Année de publication : 2015 Article en page(s) : n° 0141006 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse discriminante
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] drone
[Termes IGN] houppier
[Termes IGN] image aérienne
[Termes IGN] orthoimage
[Termes IGN] orthophotoplan numérique
[Termes IGN] phénologie
[Termes IGN] variation saisonnièreRésumé : (auteur) Technology advances can revolutionize Precision Forestry by providing accurate and fine forest information at tree level. This paper addresses the question of how and particularly when Unmanned Aerial System (UAS) should be used in order to efficiently discriminate deciduous tree species. The goal of this research is to determine when is the best time window to achieve an optimal species discrimination. A time series of high resolution UAS imagery was collected to cover the growing season from leaf flush to leaf fall. Full benefit was taken of the temporal resolution of UAS acquisition, one of the most promising features of small drones. The disparity in forest tree phenology is at the maximum during early spring and late autumn. But the phenology state that optimized the classification result is the one that minimizes the spectral variation within tree species groups and, at the same time, maximizes the phenologic differences between species. Sunlit tree crowns (5 deciduous species groups) were classified using a Random Forest approach for monotemporal, two-date and three-date combinations. The end of leaf flushing was the most efficient single-date time window. Multitemporal datasets definitely improve the overall classification accuracy. But single-date high resolution orthophotomosaics, acquired on optimal time-windows, result in a very good classification accuracy (overall out of bag error of 16%). Numéro de notice : A2015--031 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1371/journal.pone.0141006 En ligne : http://dx.doi.org/10.1371/journal.pone.0141006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81106
in Plos one > vol 10 n° 11 (November 2015) . - n° 0141006[article]Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing / Jerome O’Connell in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)
[article]
Titre : Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing Type de document : Article/Communication Auteurs : Jerome O’Connell, Auteur ; Ute Bradter, Auteur ; Tim G. Benton, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 165 - 177 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] algorithme d'apprentissage
[Termes IGN] analyse d'image orientée objet
[Termes IGN] Angleterre
[Termes IGN] Aves
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] habitat d'espèce
[Termes IGN] image aérienne
[Termes IGN] image infrarouge couleurRésumé : (auteur) Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer (Emberiza citronella), which requires hedgerows associated with grassy margins. We found that ∼22% of hedgerows were within 200 m of margins with an area >183.31 m2. The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability. Numéro de notice : A2015-862 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.09.007 Date de publication en ligne : 09/10/2015 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.09.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79243
in ISPRS Journal of photogrammetry and remote sensing > vol 109 (November 2015) . - pp 165 - 177[article]Revealing a buried historic fort : archeology meets UAS technology / Andrea Sangster in Geoinformatics, vol 18 n° 7 (October - November 2015)
[article]
Titre : Revealing a buried historic fort : archeology meets UAS technology Type de document : Article/Communication Auteurs : Andrea Sangster, Auteur Année de publication : 2015 Article en page(s) : pp 18 - 19 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] Canada
[Termes IGN] drone
[Termes IGN] fortification
[Termes IGN] image à ultra haute résolution
[Termes IGN] précision centimétriqueNuméro de notice : A2015-781 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78879
in Geoinformatics > vol 18 n° 7 (October - November 2015) . - pp 18 - 19[article]3D model construction in an urban environment from sparse LiDAR points and aerial photos : a statistical approach / Xuebin Wei in Geomatica, vol 69 n° 3 (september 2015)PermalinkAnalysis of different methods for 3D reconstruction of natural surfaces from parallel-axes UAV images / Annette Eltner in Photogrammetric record, vol 30 n° 151 (September - November 2015)PermalinkLe contrôle de la végétation dans les emprises ferroviaires : une approche multi-scalaire / Flavien Viguier in XYZ, n° 144 (septembre - novembre 2015)PermalinkNote technique : Apport de la photogrammétrie au suivi topographique de la flèche littorale de Joal (Sénégal) / Mamadou Sadio in Photo interprétation, European journal of applied remote sensing, vol 51 n° 3 (septembre 2015)PermalinkPlanificateur de missions photogrammétriques pour drones ultra-légers (Micro Aerial Vehicle MAV) / F. Gandor in Géomatique suisse, vol 113 n° 9 (septembre 2015)PermalinkRegistration of aerial imagery and lidar data in desert areas using sand ridges / Na Li in Photogrammetric record, vol 30 n° 151 (September - November 2015)PermalinkAutomatic registration of optical aerial imagery to a LiDAR point cloud for generation of city models / Bernard O. Abayowa in ISPRS Journal of photogrammetry and remote sensing, vol 106 (August 2015)PermalinkSequential spectral change vector analysis for iteratively discovering and detecting multiple changes in hyperspectral images / Sicong Liu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)PermalinkApport de modèles numériques de hauteur à l'amélioration de la précision d'inventaires statistiques forestiers / Jean-Pierre Renaud in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)PermalinkApplication of archival aerial photogrammetry to quantify climate forcing of alpine landscapes / Natan Micheletti in Photogrammetric record, vol 30 n° 150 (June - August 2015)Permalink