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Real-time GPS satellite orbit and clock estimation based on OpenMP / Kaifa Kuang in Advances in space research, vol 63 n° 8 (15 April 2019)
[article]
Titre : Real-time GPS satellite orbit and clock estimation based on OpenMP Type de document : Article/Communication Auteurs : Kaifa Kuang, Auteur ; Shoujian Zhang, Auteur ; Jiancheng Li, Auteur Année de publication : 2019 Article en page(s) : pp 2378 - 2386 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] estimation statistique
[Termes IGN] filtre de Kalman
[Termes IGN] horloge du satellite
[Termes IGN] modèle mathématique
[Termes IGN] Open Multi-Processing
[Termes IGN] orbite
[Termes IGN] temps réelRésumé : (Auteur) Real-time precise GNSS satellite orbit and clock products are the prerequisite of real-time GNSS-based applications. To obtain real-time GNSS satellite orbit and clock, three approaches exist currently, namely, the prediction-estimation approach, the prediction-correction approach and the estimation approach. Different from the former two approaches, which are based on the predicted orbit, the last approach estimates orbit and clock in an integrated way, thus it is the most rigorous one. However, the simultaneously estimation of both orbit and clock parameters makes it very time-consuming. In this contribution, the extended Kalman filter with parallel computation proposed for real-time GPS satellite clock estimation (Gao et al., 2017) is introduced to improve the computational efficiency. In the introduced method, the epoch observations are processed sequentially and the covariance update process is accelerated with the Open Multi-Processing. With observation data from about 70 globally distributed stations spanning days 001–003 of 2018, the real-time GPS orbit and clock are estimated for validation. The epoch average processing time of the introduced method achieves around 2.9 s on average with 16 CPU cores, while that of the traditional method without Open Multi-Processing is about 4.1 s. When compare the estimated orbit and clock to the IGS final products, the daily constellation-mean RMS of orbit achieve 2.7, 5.7, 4.9 cm for the radial, along-track and cross-track respectively, while the daily constellation-mean STD of the clock is about 0.10 ns. The numerical experiments indicate that the introduced method is able to provide real-time sub-decimeter GPS orbit and clock within 10.0 s considering the time for data collection and corrections broadcast. Numéro de notice : A2019-170 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.asr.2019.01.009 Date de publication en ligne : 19/01/2019 En ligne : https://doi.org/10.1016/j.asr.2019.01.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92619
in Advances in space research > vol 63 n° 8 (15 April 2019) . - pp 2378 - 2386[article]Vertical ionospheric delay estimation for single-receiver operation / Ahmed Elsayed in Journal of applied geodesy, vol 13 n° 2 (April 2019)
[article]
Titre : Vertical ionospheric delay estimation for single-receiver operation Type de document : Article/Communication Auteurs : Ahmed Elsayed, Auteur ; Ahmed Sedeek, Auteur ; Mohamed Doma, Auteur ; Mostafa Rabah, Auteur Année de publication : 2019 Article en page(s) : pp 81 - 92 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] estimation statistique
[Termes IGN] Matlab
[Termes IGN] mesurage de phase
[Termes IGN] méthode des moindres carrés
[Termes IGN] positionnement ponctuel précis
[Termes IGN] récepteur bifréquence
[Termes IGN] retard ionosphèrique
[Termes IGN] teneur verticale totale en électronsRésumé : (Auteur) An apparent delay is occurred in GPS signal due to both refraction and diffraction caused by the atmosphere. The second region of the atmosphere is the ionosphere. The ionosphere is significantly related to GPS and the refraction it causes in GPS signal is considered one of the main source of errors which must be eliminated to determine accurate positions. GPS receiver networks have been used for monitoring the ionosphere for a long time.
The ionospheric delay is the most predominant of all the error sources. This delay is a function of the total electron content (TEC). Because of the dispersive nature of the ionosphere, one can estimate the ionospheric delay using the dual frequency GPS.
In the current research our primary goal is applying Precise Point Positioning (PPP) observation for accurate ionosphere error modeling, by estimating Ionosphere delay using carrier phase observations from dual frequency GPS receiver. The proposed algorithm was written using MATLAB and was named VIDE program.
The proposed Algorithm depends on the geometry-free carrier-phase observations after detecting cycle slip to estimates the ionospheric delay using a spherical ionospheric shell model, in which the vertical delays are described by means of a zenith delay at the station position and latitudinal and longitudinal gradients.
Geometry-free carrier-phase observations were applied to avoid unwanted effects of pseudorange measurements, such as code multipath. The ionospheric estimation in this algorithm is performed by means of sequential least-squares adjustment.
Finally, an adaptable user interface MATLAB software are capable of estimating ionosphere delay, ambiguity term and ionosphere gradient accurately.Numéro de notice : A2019-143 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2018-0041 Date de publication en ligne : 04/01/2019 En ligne : https://doi.org/10.1515/jag-2018-0041 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92470
in Journal of applied geodesy > vol 13 n° 2 (April 2019) . - pp 81 - 92[article]Application de la loi de Benford au contrôle de qualité des modèles numériques de terrain / Laurent Polidori in XYZ, n° 158 (mars 2019)
[article]
Titre : Application de la loi de Benford au contrôle de qualité des modèles numériques de terrain Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur ; Mhamad El Hage, Auteur Année de publication : 2019 Article en page(s) : pp 13 - 16 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] altitude
[Termes IGN] contrôle qualité
[Termes IGN] distribution de Benford
[Termes IGN] distribution, loi de
[Termes IGN] logarithme
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] modèle numérique de terrain
[Termes IGN] pente
[Termes IGN] qualité des donnéesRésumé : (auteur) La loi de Benford fait le constat empirique d’une régularité dans la distribution statistique du premier chiffre dans de nombreuses séries de nombres (géographie, sport, économie, etc.). Elle a été utilisée pour détecter des fraudes comptables ou électorales. Dans le même esprit, nous avons cherché à l’utiliser comme critère de vraisemblance pour évaluer la qualité des modèles numériques de terrain. Les métriques considérées sont l’altitude, la pente et l’ordre de Strahler. Numéro de notice : A2019-081 Affiliation des auteurs : non IGN Thématique : IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92218
in XYZ > n° 158 (mars 2019) . - pp 13 - 16[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 112-2019011 RAB Revue Centre de documentation En réserve L003 Disponible Estimating net biomass production and loss from repeated measurements of trees in forests and woodlands: Formulae, biases and recommendations / Takashi S. Kohyama in Forest ecology and management, vol 433 (15 February 2019)
[article]
Titre : Estimating net biomass production and loss from repeated measurements of trees in forests and woodlands: Formulae, biases and recommendations Type de document : Article/Communication Auteurs : Takashi S. Kohyama, Auteur ; Tetsuo I. Kohyama, Auteur ; Douglas Sheil, Auteur Année de publication : 2019 Article en page(s) : pp 729 - 740 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre mort
[Termes IGN] biomasse forestière
[Termes IGN] déboisement
[Termes IGN] densité du bois
[Termes IGN] écosystème forestier
[Termes IGN] erreur systématique
[Termes IGN] estimation statistique
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] production primaire brute
[Termes IGN] teneur en carbone
[Vedettes matières IGN] SylvicultureRésumé : (auteur) There is widespread interest in ensuring that assessment and knowledge of changes in forest biomass, and associated carbon gains or losses, are accurate and unbiased. Repeated measurements of individually-marked trees in permanent plots permit the estimation of rates of biomass production by tree growth and recruitment and of loss from mortality. But there are challenges, for example, simple estimates of production rate (i.e., the sum of biomass gain by growth of surviving trees and new recruits divided by census duration) decline as the census interval increases due to unrecorded growth. Even if we allow for these unobserved changes, additional biases may arise due to the non-independence of growth and mortality and to the heterogeneity and compositional changes within the forest. Here we examine these issues and demonstrate how problems can be minimized. We provide and compare alternative approaches to estimate net biomass production and loss from tree growth and mortality. Under the assumption that specific rates of biomass production and loss, i.e., turnover, are constant over time, we derive estimates of absolute biomass turnover rates that are independent of census duration. We show census-interval dependence of simple turnover rates grows with increasing specific turnover rates. While the time-dependent bias in simple estimates has previously been suggested to increase in proportion to the square of production, we show this relationship is approximately linear. Correlations between stem growth and mortality do not influence our estimates. We account for biomass gain by recruited stems without discounting their initial biomass in production estimates. We can reduce additional biases by accounting for differences in turnover among subpopulations (such as species, sites) and changes in their abundances. We provide worked examples from four forests covering a range of conditions (in Indonesia and Japan) and show the effects of accounting for these biases. For example, over five years in an Indonesian rain forest, simple estimates and instantaneous estimates neglecting species heterogeneity underestimated production by 4.9% and 1.6%, respectively when compared to comprehensive (instantaneous species-structured) estimates. Numéro de notice : A2019-010 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.11.010 Date de publication en ligne : 08/12/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.11.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91604
in Forest ecology and management > vol 433 (15 February 2019) . - pp 729 - 740[article]Tree cover mapping using hybrid fuzzy C-means method and multispectral satellite images / Linda Gulbe in Baltic forestry, vol 25 n° 1 ([01/02/2019])
[article]
Titre : Tree cover mapping using hybrid fuzzy C-means method and multispectral satellite images Type de document : Article/Communication Auteurs : Linda Gulbe, Auteur ; Aleksandrs Kozlovs, Auteur ; Janis Donis, Auteur ; Agris Tradkovs, Auteur Année de publication : 2019 Article en page(s) : pp 113 - 123 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte de la végétation
[Termes IGN] classification barycentrique
[Termes IGN] classification floue
[Termes IGN] estimation statistique
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] LettonieRésumé : (auteur) Countrywide up-to-date tree cover maps provide valuable information for planning and management purposes to investigate location of the resources and to identify afforestation and deforestation patterns. Landsat programme offers freely available satellite data with time span more than three decades and it can serve as bases for tree cover map calculation using satellite image classification; however, practical use of classification methods is limited due to lack of user-friendly solutions and complex interpretation of the results. The objective of this study is to evaluate user-friendly hybrid classification scheme for tree cover mapping in Latvia and to explore the nature of the spectral classes and consistency of the results when methodology is applied to images of different dates. Tree cover in this context means the area covered by crown of the tree, which may or may not be considered as forest according to local provisions. Tree cover is estimated using unsupervised fuzzy c-means methods with the stability check to ensure the presence of the same spectral classes in independent tests. Spectral classes are classified into two categories: tree cover and other by employing k-nearest neighbours. Such approach does not require high quality sample data and does not include user defined internal parameters of the algorithms (however, they can be specified if needed). The best overall accuracy achieved for year 2014 was 94.2% with producer's accuracy 98.7% (tree cover), 90.5% (other land cover), user's accuracy 90.0% (tree cover), 98.8% (other land cover) and kappa 0.89. Consistency studies showed high impact (within 10% of overall accuracy) of unique conditions during the image acquisition. Some of the spectral classes represent borderline case between relatively dense tree cover and other land cover types like sparse young stands. Those cases are the main threat to the consistency between the results of different dates and seasons. Numéro de notice : A2019-375 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : sans En ligne : https://balticforestry.lammc.lt/bf/PDF_Articles/2019-25%5B1%5D/Baltic%20Forestry [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93417
in Baltic forestry > vol 25 n° 1 [01/02/2019] . - pp 113 - 123[article]Bayesian iterative reconstruction methods for 3D X-ray Computed Tomography / Camille Chapdelaine (2019)PermalinkCorrecting for nondetection in estimating forest characteristics from single-scan terrestrial laser measurements / Mikko Kuronen in Canadian Journal of Forest Research, vol 49 n° 1 (janvier 2019)PermalinkPermalinkExploitation de séries temporelles d'images multi-sources pour la cartographie des surfaces en eau / Filsa Bioresita (2019)PermalinkFostering the use of methods for geosimulation models sensitivity analysis and validation / Romain Reuillon (2019)PermalinkImproving the reliability of landslide susceptibility mapping through spatial uncertainty analysis: a case study of Al Hoceima, Northern Morocco / Hassane Rahali in Geocarto international, vol 34 n° 1 ([01/01/2019])PermalinkPermalinkProjection sur l’évolution de la distribution future de la population en utilisant du Machine Learning et de la géosimulation / Julie Grosmaire (2019)PermalinkSimultaneous characterization of objects temperature and radiative properties through multispectral infrared thermography / Thibaud Toullier (2019)PermalinkPermalinkDeveloping allometric equations for estimating shrub biomass in a Boreal Fen / Annie He in Forests, vol 9 n° 9 (September 2018)PermalinkEstimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data / P. Kumar in Geocarto international, vol 33 n° 9 (September 2018)PermalinkA two-stage estimation method with bootstrap inference for semi-parametric geographically weighted generalized linear models / Dengkui Li in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)PermalinkEPLA : efficient personal location anonymity / Dapeng Zhao in Geoinformatica, vol 22 n° 1 (January 2018)PermalinkBayesian statistics and Monte Carlo methods / Karl Rudolf Koch in Journal of geodetic science, vol 8 n° 1 (January 2018)PermalinkPermalinkPermalinkUn inventaire forestier multisource pour la gestion des territoires / Dinesh Babu Irulappa-Pillai-Vijayakumar (2018)PermalinkPermalinkA wavelet decomposition and polynomial fitting-based method for the estimation of time-varying residual motion error in airborne interferometric SAR / Hai Qiang Fu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)PermalinkAlgebraic method to speed up robust algorithms: example of laser-scanned point clouds / B. Palancz in Survey review, vol 49 n° 357 (December 2017)PermalinkEstimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery / Jose Alan A. Castillo in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)PermalinkTotal evaporation estimation for accurate water accounting purposes: an appraisal of various available estimation methods / Cletah Shoko in Geocarto international, vol 32 n° 12 (December 2017)PermalinkMapping the height and spatial cover of features beneath the forest canopy at small-scales using airborne scanning discrete return Lidar / Matthew Sumnall in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)PermalinkCharacterizing noise in daily GPS position time series with overlapping Hadamard variance and maximum likelihood estimation / Chang Xu in Survey review, vol 49 n° 355 (October 2017)PermalinkLocalisation 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)PermalinkMulti-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)PermalinkTree size thresholds produce biased estimates of forest biomass dynamics / Eric B. Searle in Forest ecology and management, vol 400 (15 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)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)PermalinkHybrid three-phase estimators for large-area forest inventory using ground plots, airborne lidar, and space lidar / Sören Holm in Remote sensing of environment, vol 197 (August 2017)PermalinkForest modelling: the gamma shape mixture model and simulation of tree diameter distributions / Rafał Podlaski in Annals of Forest Science, vol 74 n° 2 (June 2017)PermalinkGPS coordinate time series measurements in Ontario and Quebec, Canada / Hadis Samadi Alinia in Journal of geodesy, vol 91 n° 6 (June 2017)PermalinkExploring spatiotemporal clusters based on extended kernel estimation methods / Jay Lee in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)PermalinkForest classification and impact of BIOMASS resolution on forest area and aboveground biomass estimation / Michael Schlund in International journal of applied Earth observation and geoinformation, vol 56 (April 2017)PermalinkPerformance evaluation of GNSS-TEC estimation techniques at the grid point in middle and low latitudes during different geomagnetic conditions / O. E. Abe in Journal of geodesy, vol 91 n° 4 (April 2017)PermalinkEstimation and analysis of Galileo differential code biases / Min Li in Journal of geodesy, vol 91 n° 3 (March 2017)PermalinkImage-based target detection and radial velocity estimation methods for multichannel SAR-GMTI / Kei Suwa in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)PermalinkMapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory / Jonas Bohlin in Silva fennica, vol 51 n° 2 (2017)PermalinkSemi-parametric segmentation of multiple series using a DP-Lasso strategy / Karine Bertin in Journal of Statistical Computation and Simulation, vol 87 n° 6 (2017)PermalinkInconsistent estimates of forest cover change in China between 2000 and 2013 from multiple datasets: differences in parameters, spatial resolution, and definitions / Yan Li in Scientific reports, vol 7 (2017)PermalinkAmélioration de la vitesse et de la qualité d'image du rendu basé image / Rodrigo Ortiz Cayón (2017)PermalinkPermalinkFusion of multi-temporal Sentinel-2 image series and very-high spatial resolution images for detection of urban areas / Cyril Wendl (2017)PermalinkTélédétection pour l'observation des surfaces continentales, Volume 3. Observation des surfaces continentales par télédétection 1 / Nicolas Baghdadi (2017)PermalinkUtilisation d’un modèle numérique de hauteur en stratification des données de l’Inventaire Forestier National / Sophie Georges (2017)PermalinkVision stéréoscopique temps-réel pour la navigation autonome d'un robot en environnement dynamique / Maxime Derome (2017)PermalinkComparison of methods used in European National Forest Inventories for the estimation of volume increment: towards harmonisation / Thomas Gschwantner in Annals of Forest Science, vol 73 n° 4 (December 2016)PermalinkThe 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)PermalinkAn advanced GNSS code multipath detection and estimation algorithm / Negin Sokhandan in GPS solutions, vol 20 n° 4 (October 2016)PermalinkDisaster debris estimation using high-resolution polarimetric stereo-SAR / Christian N. Koyama in ISPRS Journal of photogrammetry and remote sensing, vol 120 (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)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)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)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)PermalinkAn average error-ellipsoid model for evaluating TLS point-cloud accuracy / Xijiang Chen in Photogrammetric record, vol 31 n° 153 (March - May 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)PermalinkCaractérisation 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)PermalinkEstimation of forest biomass using multivariate relevance vector regression / Alireza Sharifi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 1 (January 2016)PermalinkPermalinkPermalinkInvestigating efficacy of robust M-estimation of deformation from observation differences / Krzysztof Nowel in Survey review, vol 48 n° 346 (January 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)PermalinkThe ill wind that blew some good / Miroslav Holubec in GEO: Geoconnexion international, vol 15 n° 1 (January 2016)PermalinkVers la prise en compte de la dépendance spatio temporelle des séries de position GNSS dans leur analyse / Clément Benoist (2016)PermalinkCanopy density model: A new ALS-derived product to generate multilayer crown cover maps / António Ferraz in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)PermalinkPermalinkModeling and simulation of glacier avalanche: a case study of Gayari sector glaciers Hazards assessment / Muhammad Ashan Mahboob in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)PermalinkForest height estimation by means of Pol-InSAR data inversion : The role of the vertical wavenumber / Florian Kugler in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)PermalinkHigh-resolution forest canopy height estimation in an African blue carbon ecosystem / David Lagomasino in Remote sensing in ecology and conservation, vol 1 n° 1 (October 2015)PermalinkMapping and assessing coastal resilience in the Caribbean region / Nina S.N. Lam in Cartography and Geographic Information Science, Vol 42 n° 4 (September 2015)PermalinkRecommendations for the use of tree models to estimate national forest biomass and assess their uncertainty / Matieu Henry in Annals of Forest Science, vol 72 n° 6 (September 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)PermalinkEstimation de paramètres forestiers par données Lidar aéroporté et imagerie satellitaire RapidEye : étude de sensibilité / Jean-Matthieu Monnet in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)PermalinkNetwork-based estimation of time-dependent noise in GPS position time series / Ksenia Dimitrieva in Journal of geodesy, vol 89 n° 6 (June 2015)PermalinkObject detection in optical remote sensing images based on weakly supervised learning and high-level feature learning / Junwei Han in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)PermalinkOutlier Detection by means of Monte Carlo Estimation including resistant Scale Estimation / Christian Marx in Journal of applied geodesy, vol 9 n° 2 (June 2015)PermalinkReal-time GPS precise point positioning-based precipitable water vapor estimation for rainfall monitoring and forecasting / Junbo Shi in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)PermalinkThe guided bilateral filter: When the joint/cross bilateral filter becomes robust / Laurent Caraffa in IEEE Transactions on image processing, vol 24 n° 4 (April 2015)PermalinkForest inventory attribute estimation using airborne laser scanning, aerial stereo imagery, radargrammetry and interferometry–Finnish experiences of the 3D techniques / Markus Holopainen in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W4 (March 2015)PermalinkChamp de vitesse GPS du Nord-Est de la France : apport des stations permanentes pour une précision submillimétrique / Eric Henrion in XYZ, n° 142 (mars - mai 2015)PermalinkEvaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)PermalinkSequential estimation of surface water mass changes from daily satellite gravimetry data / Guillaume L. Ramilien in Journal of geodesy, vol 89 n° 3 (March 2015)PermalinkJoint segmentation of multiple GPS coordinate series / Julien Gazeaux in Journal de la Société Française de Statistique, vol 156 n° 4 ([01/02/2015])Permalink