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Systematic effects in laser scanning and visualization by confidence regions / Karl Rudolf Koch in Journal of applied geodesy, vol 10 n° 4 (December 2016)
[article]
Titre : Systematic effects in laser scanning and visualization by confidence regions Type de document : Article/Communication Auteurs : Karl Rudolf Koch, Auteur ; Jan Martin Brockmann, Auteur Année de publication : 2016 Article en page(s) : pp 247 – 257 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] carte de confiance
[Termes IGN] covariance
[Termes IGN] densité de probabilité
[Termes IGN] distribution de Gauss
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] ellipsoïde (géodésie)
[Termes IGN] itération
[Termes IGN] matrice de covariance
[Termes IGN] mesure géométrique
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] série temporelle
[Termes IGN] visualisationRésumé : (auteur) A new method for dealing with systematic effects in laser scanning and visualizing them by confidence regions is derived. The standard deviations of the systematic effects are obtained by repeatedly measuring three-dimensional coordinates by the laser scanner. In addition, autocovariance and cross-covariance functions are computed by the repeated measurements and give the correlations of the systematic effects. The normal distribution for the measurements and the multivariate uniform distribution for the systematic effects are applied to generate random variates for the measurements and random variates for the measurements plus systematic effects. Monte Carlo estimates of the expectations and the covariance matrix of the measurements with systematic effects are computed. The densities for the confidence ellipsoid for the measurements and the confidence region for the measurements with systematic effects are obtained by relative frequencies. They only depend on the size of the rectangular volume elements for which the densities are determined. The problem of sorting the densities is solved by sorting distances together with the densities. This allows a visualization of the confidence ellipsoid for the measurements and the confidence region for the measurements with systematic effects. Numéro de notice : A2016-975 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1515/jag-2016-0012 En ligne : https://doi.org/10.1515/jag-2016-0012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83682
in Journal of applied geodesy > vol 10 n° 4 (December 2016) . - pp 247 – 257[article]The effects of temporal differences between map and ground data on map-assisted estimates of forest area and biomass / Ronald E. McRoberts in Annals of Forest Science, vol 73 n° 4 (December 2016)
[article]
Titre : The effects of temporal differences between map and ground data on map-assisted estimates of forest area and biomass Type de document : Article/Communication Auteurs : Ronald E. McRoberts, Auteur ; Erik Naesset, Auteur ; Terje Gobakken, Auteur Année de publication : 2016 Article en page(s) : pp 839 - 847 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] biomasse
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] estimation statistique
[Termes IGN] forêt
[Termes IGN] image Landsat
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Minnesota (Etats-Unis)
[Termes IGN] Norvège
[Termes IGN] régression
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Key message : When areas of interest experience little change, remote sensing-based maps whose dates deviate from ground data can still substantially enhance precision. However, when change is substantial, deviations in dates reduce the utility of such maps for this purpose.
Context : Remote sensing-based maps are well-established as means of increasing the precision of estimates of forest inventory parameters. The general practice is to use maps whose dates correspond closely to the dates of ground data. However, as national forest inventories move to continuous inventories, deviations between map and ground data dates increase.
Aims : The aim was to assess the degree to which remote sensing-based maps can be used to increase the precision of estimates despite differences between map and ground data dates.
Methods : For study areas in the USA and Norway, maps were constructed for each of two dates, and model-assisted regression estimators were used to estimate inventory parameters using ground data whose dates differed by as much as 11 years from the map dates.
Results : For the Minnesota study area that had little change, 7-year differences in dates had little effect on the precision of estimates of proportion forest area. For the Norwegian study area that experienced considerable change, 11-year differences in dates had a detrimental effect on the precision of estimates of mean biomass per unit area.
Conclusions : The effects of differences in map and ground data dates were less important than temporal change in the study area.Numéro de notice : A2016--168 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-015-0485-6 Date de publication en ligne : 12/05/2015 En ligne : https://doi.org/10.1007/s13595-015-0485-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87210
in Annals of Forest Science > vol 73 n° 4 (December 2016) . - pp 839 - 847[article]An advanced GNSS code multipath detection and estimation algorithm / Negin Sokhandan in GPS solutions, vol 20 n° 4 (October 2016)
[article]
Titre : An advanced GNSS code multipath detection and estimation algorithm Type de document : Article/Communication Auteurs : Negin Sokhandan, Auteur ; James T. Curran, Auteur ; Ali Broumandan, Auteur ; Gérard Lachapelle, Auteur Année de publication : 2016 Article en page(s) : pp 627 - 640 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] code GNSS
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] milieu urbain
[Termes IGN] modèle de simulation
[Termes IGN] positionnement par GNSS
[Termes IGN] système de navigation
[Termes IGN] trajet multipleRésumé : (Auteur) A novel maximum likelihood-based range estimation algorithm is designed to provide robustness to multipath, which is recognized as a dominant error source in DS-CDMA-based navigation systems. The detection–estimation problem is jointly solved to sequentially estimate the parameters of each individual multipath component and predict the existence of a next possible component. A comparison between contemporary maximum likelihood-based multipath estimation techniques and this new technique is provided. A selection of realistic channel simulation models is used to assess relative performance under different operating situations. A set of real GPS L1/CA data processing results are also presented to further assess the applicability of the proposed algorithm for urban navigation. Numéro de notice : A2016--025 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-015-0475-z En ligne : http://dx.doi.org/10.1007/s10291-015-0475-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83926
in GPS solutions > vol 20 n° 4 (October 2016) . - pp 627 - 640[article]Disaster debris estimation using high-resolution polarimetric stereo-SAR / Christian N. Koyama in ISPRS Journal of photogrammetry and remote sensing, vol 120 (october 2016)
[article]
Titre : Disaster debris estimation using high-resolution polarimetric stereo-SAR Type de document : Article/Communication Auteurs : Christian N. Koyama, Auteur ; Hideomi Gokon, Auteur ; Masaru Jimbo, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 84 - 98 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] catastrophe naturelle
[Termes IGN] déchet
[Termes IGN] estimation statistique
[Termes IGN] hauteur (coordonnée)
[Termes IGN] image radar moirée
[Termes IGN] Japon
[Termes IGN] modèle stéréoscopique
[Termes IGN] séisme
[Termes IGN] volume (grandeur)Résumé : (Auteur) This paper addresses the problem of debris estimation which is one of the most important initial challenges in the wake of a disaster like the Great East Japan Earthquake and Tsunami. Reasonable estimates of the debris have to be made available to decision makers as quickly as possible. Current approaches to obtain this information are far from being optimal as they usually rely on manual interpretation of optical imagery. We have developed a novel approach for the estimation of tsunami debris pile heights and volumes for improved emergency response. The method is based on a stereo-synthetic aperture radar (stereo-SAR) approach for very high-resolution polarimetric SAR. An advanced gradient-based optical-flow estimation technique is applied for optimal image coregistration of the low-coherence non-interferometric data resulting from the illumination from opposite directions and in different polarizations. By applying model based decomposition of the coherency matrix, only the odd bounce scattering contributions are used to optimize echo time computation. The method exclusively considers the relative height differences from the top of the piles to their base to achieve a very fine resolution in height estimation. To define the base, a reference point on non-debris-covered ground surface is located adjacent to the debris pile targets by exploiting the polarimetric scattering information. The proposed technique is validated using in situ data of real tsunami debris taken on a temporary debris management site in the tsunami affected area near Sendai city, Japan. The estimated height error is smaller than 0.6 m RMSE. The good quality of derived pile heights allows for a voxel-based estimation of debris volumes with a RMSE of 1099 m3. Advantages of the proposed method are fast computation time, and robust height and volume estimation of debris piles without the need for pre-event data or auxiliary information like DEM, topographic maps or GCPs. Numéro de notice : A2016-796 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.08.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.08.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82530
in ISPRS Journal of photogrammetry and remote sensing > vol 120 (october 2016) . - pp 84 - 98[article]Modeling the effects of horizontal positional error on classification accuracy statistics / Henry B. Glick in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 10 (October 2016)
[article]
Titre : Modeling the effects of horizontal positional error on classification accuracy statistics Type de document : Article/Communication Auteurs : Henry B. Glick, Auteur ; Devin Routh, Auteur ; Charlie Bettigole, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 789 - 802 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification
[Termes IGN] erreur de positionnement
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] simulationRésumé : (Auteur) Using a concept proposed by Stehman and Czaplewski (1997), we implemented spatially-explicit Monte Carlo simulations to test the effects of manually introduced horizontal positional error on standard inter-rater statistics derived from twelve classified high-resolution images. Through simulations we found that both overall and kappa accuracies decrease markedly with increasing error distance, varying greatly across distances relevant to practical application. The use of ground reference sites falling solely in homogeneous patches significantly improves inter-rater statistics and calls into question the use of kernel-smoothed data in one-time accuracy assessments. Our simulations offer insight into the scale of both structural and cover type heterogeneity across our landscapes, and support a new method for minimizing the effects of positional error on map accuracy. We recommend that analysts use caution when applying traditional accuracy assessment strategies to categorical maps, particularly when working with high-resolution imagery. Numéro de notice : A2016-934 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.10.789 En ligne : http://dx.doi.org/10.14358/PERS.82.10.789 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83348
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 10 (October 2016) . - pp 789 - 802[article]Outlier detection by using fault detection and isolation techniques in geodetic networks / U.M. Durdag in Survey review, vol 48 n° 351 (October 2016)PermalinkA probabilistic approach to detect mixed periodic patterns from moving object data / Jun Li in Geoinformatica, vol 20 n° 4 (October - December 2016)PermalinkRelative importance analysis of Landsat, waveform LIDAR and PALSAR inputs for deciduous biomass estimation / Alyssa Endres in European journal of remote sensing, vol 49 n° 1 (2016)PermalinkTaking correlations in GPS least squares adjustments into account with a diagonal covariance matrix / Gaël Kermarrec in Journal of geodesy, vol 90 n° 9 (September 2016)PermalinkAn adaptive stochastic model for GPS observations and its performance in precise point positioning / J. Z. Zheng in Survey review, vol 48 n° 349 (July 2016)PermalinkSpace-time multiple regression model for grid-based population estimation in urban areas / Ko Ko Lwin in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)PermalinkStochastic modeling of triple-frequency BeiDou signals: estimation, assessment and impact analysis / Bofeng Li in Journal of geodesy, vol 90 n° 7 (July 2016)PermalinkComparison of robust estimators for leveling networks in Monte Carlo simulations / Maria Pokarowska in Reports on geodesy and geoinformatics, vol 101 (June 2016)PermalinkInventory-based estimation of forest biomass in Shitai County, China: A comparison of five methods / X. Tang in Annals of forest research, vol 59 n° 2 (July - December 2016)PermalinkThe variants of an LOD of a 3D building model and their influence on spatial analyses / Filip Biljecki in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 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)PermalinkReconstruction of itineraries from annotated text with an informed spanning tree algorithm / Ludovic Moncla in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)PermalinkA correctly weighted least squares adjustment - Part 3 Estimating standard errors in angular observations / Charles D. Ghilani in xyHt, vol 2016 n° 4 (April 2016)PermalinkJoint analysis of GOCE gravity gradients data of gravitational potential and of gravity with seismological and geodynamic observations to infer mantle properties / Marianne Greff-Lefftz in Geophysical journal international, vol 205 n° 1 (April 2016)PermalinkAn average error-ellipsoid model for evaluating TLS point-cloud accuracy / Xijiang Chen in Photogrammetric record, vol 31 n° 153 (March - May 2016)PermalinkApproximating prediction uncertainty for random forest regression models / John W. Coulston in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 3 (March 2016)PermalinkMarkov random field-based method for super-resolution mapping of forest encroachment from remotely sensed ASTER image / L. K. Tiwari in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)PermalinkMIDAS robust trend estimator for accurate GPS station velocities without step detection / Geoffrey Blewitt in Journal of geophysical research : Solid Earth, vol 121 n° 3 (March 2016)PermalinkRobust spatial approximation of laser scanner point clouds by means of Free-form Curve approaches in deformation analysis / Johannes Bureick in Journal of applied geodesy, vol 10 n° 1 (March 2016)PermalinkA correctly weighted least squares adjustment - Part 2 Estimating uncertainties / Charles D. Ghilani in xyHt, vol 2016 n° 2 (February 2016)PermalinkLa géostatistique : une vision novatrice au service des géosciences / Bernard Bourgine in Géosciences, n°20 (février 2016)PermalinkSpace–time adaptive processing and motion parameter estimation in multistatic passive radar using sparse Bayesian learning / Qisong Wu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)PermalinkUse of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation / Göran Stahl in Forest ecosystems, vol 3 (2016)PermalinkApplication of topo-edaphic factors and remotely sensed vegetation indices to enhance biomass estimation in a heterogeneous landscape in the Eastern Arc mountains of Tanzania / Mercy Ojoyi in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)PermalinkPermalinkCaractérisation des signaux et des bruits des séries temporelles du géocentre et des paramètres de rotation de la Terre (EOP) / Bachir Gourine in Bulletin des sciences géographiques, n° 30 (2015 - 2016)PermalinkConvex programming approach to robust estimation of a multivariate Gaussian model / Samuel Balmand (2016)PermalinkPermalinkEstimation of forest biomass using multivariate relevance vector regression / Alireza Sharifi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 1 (January 2016)PermalinkPermalinkPermalinkPermalinkInvestigating efficacy of robust M-estimation of deformation from observation differences / Krzysztof Nowel in Survey review, vol 48 n° 346 (January 2016)PermalinkLandmark based localization: LBA refinement using MCMC-optimized projections of RJMCMC-extracted road marks / Bahman Soheilian (2016)PermalinkLocalisation à base d’amers visuels : Cartographie et mise en correspondance de marquages au sol et intégration dans LBA / Bahman Soheilian (2016)PermalinkModelling forest canopy trends with on-demand spatial simulation / Gordon M. Green in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)PermalinkMultifractal analysis for multivariate data with application to remote sensing / Sébastien Combrexelle (2016)PermalinkOn estimation of the diagonal elements of a sparse precision matrix / Samuel Balmand in Electronic Journal of Statistics, vol 10 n° 1 (January 2016)PermalinkPassive microwave remote sensing of soil moisture based on dynamic vegetation scattering properties for AMSR-E / Jinyang Du in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)PermalinkPhotogrammetric computer vision / Wolfgang Förstner (2016)PermalinkA probabilistic approach for InSAR time-series postprocessing / Ling Chang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)PermalinkPermalinkQualité des données géographiques : à propos de la propagation des incertitudes / Gilles Troispoux in Signature, n° 59 (janvier 2016)PermalinkPermalinkPermalink