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Computation of GPS P1–P2 differential code biases with JASON-2 / Gilles Wautelet in GPS solutions, vol 21 n° 4 (October 2017)
[article]
Titre : Computation of GPS P1–P2 differential code biases with JASON-2 Type de document : Article/Communication Auteurs : Gilles Wautelet, Auteur ; Sylvain Loyer, Auteur ; Flavien Mercier, Auteur ; Félix Perosanz, Auteur Année de publication : 2017 Article en page(s) : pp 1619 - 1631 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] code GPS
[Termes IGN] corrélation
[Termes IGN] données Jason
[Termes IGN] erreur systématique
[Termes IGN] GPS en mode différentiel
[Termes IGN] orbitographie
[Termes IGN] plasmasphère
[Termes IGN] teneur verticale totale en électronsRésumé : (Auteur) GPS Differential Code Biases (DCBs) computation is usually based on ground networks of permanent stations. The drawback of the classical methods is the need for the ionospheric delay so that any error in this quantity will map into the solution. Nowadays, many low-orbiting satellites are equipped with GPS receivers which are initially used for precise orbitography. Considering spacecrafts at an altitude above the ionosphere, the ionized contribution comes from the plasmasphere, which is less variable in time and space. Based on GPS data collected onboard JASON-2 spacecraft, we present a methodology which computes in the same adjustment the satellite and receiver DCBs in addition to the plasmaspheric vertical total electron content (VTEC) above the satellite, the average satellite bias being set to zero. Results show that GPS satellite DCB solutions are very close to those of the IGS analysis centers using ground measurements. However, the receiver DCB and VTEC are closely correlated, and their value remains sensitive to the choice of the plasmaspheric parametrization. Numéro de notice : A2017-617 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-017-0638-1 Date de publication en ligne : 19/05/2017 En ligne : https://doi.org/10.1007/s10291-017-0638-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86927
in GPS solutions > vol 21 n° 4 (October 2017) . - pp 1619 - 1631[article]Efficient structure from motion for oblique UAV images based on maximal spanning tree expansion / San Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)
[article]
Titre : Efficient structure from motion for oblique UAV images based on maximal spanning tree expansion Type de document : Article/Communication Auteurs : San Jiang, Auteur ; Wanshou Jiang, Auteur Année de publication : 2017 Article en page(s) : pp 140 - 161 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme STA
[Termes IGN] compensation par faisceaux
[Termes IGN] drone
[Termes IGN] image aérienne oblique
[Termes IGN] reconstruction 3D
[Termes IGN] structure-from-motionRésumé : (Auteur) The primary contribution of this paper is an efficient Structure from Motion (SfM) solution for oblique unmanned aerial vehicle (UAV) images. First, an algorithm, considering spatial relationship constraints between image footprints, is designed for match pair selection with the assistance of UAV flight control data and oblique camera mounting angles. Second, a topological connection network (TCN), represented by an undirected weighted graph, is constructed from initial match pairs, which encodes the overlap areas and intersection angles into edge weights. Then, an algorithm, termed MST-Expansion, is proposed to extract the match graph from the TCN, where the TCN is first simplified by a maximum spanning tree (MST). By further analysis of the local structure in the MST, expansion operations are performed on the vertices of the MST for match graph enhancement, which is achieved by introducing critical connections in the expansion directions. Finally, guided by the match graph, an efficient SfM is proposed. Under extensive analysis and comparison, its performance is verified by using three oblique UAV datasets captured with different multi-camera systems. Experimental results demonstrate that the efficiency of image matching is improved, with speedup ratios ranging from 19 to 35, and competitive orientation accuracy is achieved from both relative bundle adjustment (BA) without GCPs (Ground Control Points) and absolute BA with GCPs. At the same time, images in the three datasets are successfully oriented. For the orientation of oblique UAV images, the proposed method can be a more efficient solution. Numéro de notice : A2017-642 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.09.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.09.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86999
in ISPRS Journal of photogrammetry and remote sensing > vol 132 (October 2017) . - pp 140 - 161[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017101 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017102 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017103 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Localisation des caméras ANPR sur le réseau routier pour le profilage géographique / Marie Trotta in Revue internationale de géomatique, vol 27 n° 4 (octobre - décembre 2017)
[article]
Titre : Localisation des caméras ANPR sur le réseau routier pour le profilage géographique Type de document : Article/Communication Auteurs : Marie Trotta, Auteur ; Jean-Paul Donnay, Auteur Année de publication : 2017 Article en page(s) : pp 503 - 521 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse multicritère
[Termes IGN] estimation par noyau
[Termes IGN] infraction
[Termes IGN] Liège
[Termes IGN] réseau routier
[Termes IGN] trafic routierRésumé : (auteur) Malgré un recours croissant à la technologie des caméras ANPR, en particulier dans les investigations criminelles, la littérature et l’expérience des forces de police avec lesquelles nous avons travaillé, semblent montrer qu’il n’existe pas de méthode systématique afin de localiser le plus adéquatement possible ces installations coûteuses. Partant d’un ensemble de délits localisés, relevant de quatre catégories de vols perpétrés sur une année au sein de la province de Liège (Belgique), nous proposons une méthodologie exploitant, dans une analyse multicritère, la densité de délits, la densité de voirie et la distance entre les sites des caméras. L’approche multicritère permet d’ajuster la pondération des facteurs selon les types de délits. En outre, la méthodologie est itérative, dans la mesure où les sites des caméras sont localisés par phases successives. Un critère de validation des résultats est fourni sous la forme d’un taux de couverture du territoire considéré, qui est fonction du nombre de sites de caméras retenus et du temps de parcours depuis chacun de ces sites. De plus, les conséquences des tentatives d’évitement des sites installés en matière de profilage géographique sont rapidement évoquées. Numéro de notice : A2017-833 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3166/rig.2017.00047 En ligne : https://doi.org/10.3166/rig.2017.00047 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89372
in Revue internationale de géomatique > vol 27 n° 4 (octobre - décembre 2017) . - pp 503 - 521[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 047-2017041 SL Revue Centre de documentation Revues en salle Disponible Multi-model estimation of understorey shrub, herb and moss cover in temperate forest stands by laser scanner data / Hooman Latifi in Forestry, an international journal of forest research, vol 90 n° 4 (October 2017)
[article]
Titre : Multi-model estimation of understorey shrub, herb and moss cover in temperate forest stands by laser scanner data Type de document : Article/Communication Auteurs : Hooman Latifi, Auteur ; Steven Hill, Auteur ; Bastian Schumann, Auteur ; Marco Heurich, Auteur ; Stefan Dech, Auteur Année de publication : 2017 Article en page(s) : pp 496 - 514 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] estimation statistique
[Termes IGN] forêt tempérée
[Termes IGN] habitat forestier
[Termes IGN] sous-boisRésumé : (Auteur) In temperate forests, the highest plant richness is regularly found in the understorey, i.e. shrub, tree regeneration, herbal and moss covers, which provides important food and shelter for other plant and animal species. Here, Light Detection And Ranging (LiDAR) remote sensing was investigated as a surrogate to laborious field surveys to improve understanding of the causal and predictive attributes of understorey. We designed a study in which we used a high-density LiDAR point cloud and applied a thinning algorithm to simulate two lower density point clouds including first and last returns and half of the remaining points (half-thinned data) and only first and last returns (F/L-thinned data). From each dataset, several over- and understorey-related statistical metrics were derived. Each of the three sets of LiDAR metrics was then combined with the forest habitat information to estimate the recorded proportions of shrub, herb and moss coverages. We used three different model procedures including zero-and-one-inflated beta regression (ZOINBR), ordinary least squares with logit-transformed response variables (logistic model) and a machine learning random forest (RF) method. The logistic and ZOINBR model results showed highly significant relationships between LiDAR metrics and habitat types in explaining understorey coverage. The highest coefficients of determination included r2 = 0.80 for shrub cover (estimated by F/L-thinned data and ZOINBR model), r2 = 0.53 for herb cover (estimated by half-thinned data and logistic model) and r2 = 0.48 for moss cover (estimated by half-thinned data and logistic model). RF models returned the best predictive performances (i.e. the lowest root mean square errors). Despite slight differences, no substantial difference was observed amongst the performances achieved by the original, half-thinned and F/L-thinned point clouds. Moreover, the ZOINBR models did not improve predictive performances compared with the logistic model, which suggests that the latter should be preferred due to its greater simplicity and parsimony. Despite the differences between our simulated data and the real-world LiDAR point clouds of different point densities, the results of this study are thought to mostly reflect how LiDAR and forest habitat data can be combined for deriving ecologically relevant information on temperate forest understorey vegetation layers. This, in turn, increases the applicability of prediction results for overarching aims such as forest and wildlife management. Numéro de notice : A2017-906 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.1093/forestry/cpw066 Date de publication en ligne : 27/01/2017 En ligne : https://doi.org/10.1093/forestry/cpw066 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93195
in Forestry, an international journal of forest research > vol 90 n° 4 (October 2017) . - pp 496 - 514[article]Registration of images to Lidar and GIS data without establishing explicit correspondences / Gabor Barsai in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 10 (October 2017)
[article]
Titre : Registration of images to Lidar and GIS data without establishing explicit correspondences Type de document : Article/Communication Auteurs : Gabor Barsai, Auteur ; Alper Yilmaz, Auteur ; Sudhagar Nagarajan, Auteur ; Panu Srestasathiern, Auteur Année de publication : 2017 Article en page(s) : pp 705 - 716 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] contour
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] fusion d'images
[Termes IGN] image aérienne oblique
[Termes IGN] méthode de réduction d'énergie
[Termes IGN] superposition d'images
[Termes IGN] variable aléatoireRésumé : (auteur) Recovering the camera orientation is a fundamental problem in photogrammetry for precision 3D recovery, orthophoto generation, and image registration. In this paper, we achieve this goal by fusing the image information with information extracted from different modalities, including lidar and GIS. In contrast to other approaches, which require feature correspondences, our approach exploits edges across the modalities without the necessity to explicitly establish correspondences. In the proposed approach, extracted edges from different modalities are not required to have analytical forms. This flexibility is achieved by minimizing a new cost function using a Bayesian approach, which takes the Euclidean distances between the projected edges extracted from the other data source and the edges extracted from the reference image as its random variable. The proposed formulation minimizes the overall distances between the sets of edges iteratively, such that the end product results in the correct camera parameters for the reference image as well as matching features across the modalities. The initial solution can be obtained from GPS/IMU data. The formulation is shown to successfully handle noise and missing observations in edges. Point matching methods may fail for oblique images, especially high oblique images. We eliminate the requirement for exact point-to-point matching. The feasibility of the method is experimented with nadir and oblique images. Numéro de notice : A2017-691 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.83.10.705 En ligne : https://doi.org/10.14358/PERS.83.10.705 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87858
in Photogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 10 (October 2017) . - pp 705 - 716[article]The relation between degree-2160 spectral models of Earth’s gravitational and topographic potential : a guide on global correlation measures and their dependency on approximation effects / Christian Hirt in Journal of geodesy, vol 91 n° 10 (October 2017)PermalinkTree size thresholds produce biased estimates of forest biomass dynamics / Eric B. Searle in Forest ecology and management, vol 400 (15 September 2017)PermalinkAssessing the performance of multi-GNSS precise point positioning in Asia-Pacific region / X. Zhao in Survey review, vol 49 n° 354 (September 2017)PermalinkA GPU-accelerated adaptive kernel density estimation approach for efficient point pattern analysis on spatial big data / Guiming Zhang in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)PermalinkImpact of spatial correlations on the surface estimation based on terrestrial laser scanning / Tobias Jurek in Journal of applied geodesy, vol 11 n° 3 (September 2017)PermalinkA Markov chain model for simulating wood supply from any-aged forest management based on national forest inventory (NFI) data / Jari Vauhkonen in Forests, vol 8 n° 9 (September 2017)PermalinkRéduction de l'erreur systématique de mesure géométrique par enrichissement altimétrique des données géographiques / Jean-François Girres in Cartes & Géomatique, n° 233 (septembre - novembre 2017)PermalinkA Stepwise-Then-Orthogonal Regression (STOR) with quality control for optimizing the RFM of high-resolution satellite imagery / Chang Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 9 (September 2017)Permalink3D local feature BKD to extract road information from mobile laser scanning point clouds / Yang Bisheng in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)PermalinkAn evaluation of sampling and full enumeration strategies for Fisher Jenks classification in big data settings / Sergio J. Rey in Transactions in GIS, vol 21 n° 4 (August 2017)Permalink