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GNSS metadata and data validation in the EUREF Permanent Network / Carine Bruyninx in GPS solutions, vol 23 n° 4 (October 2019)  

Public [article]  inGPS solutions > vol 23 n° 4 (October 2019) Titre : GNSS metadata and data validation in the EUREF Permanent Network Type de document : Article/Communication Auteurs : Carine Bruyninx, Auteur ; Juliette Legrand, Auteur ; András Fabian, Auteur ; Eric Pottiaux, Auteur Année de publication : 2019 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux [Termes descripteurs IGN] métadonnées géographiques [Termes descripteurs IGN] qualité des metadonnées [Termes descripteurs IGN] récepteur GNSS [Termes descripteurs IGN] réseau permanent EUREF [Termes descripteurs IGN] station GNSS [Termes descripteurs IGN] validation des données Résumé : (Auteur) The EUREF Permanent Network (EPN) is a network of continuously operating GNSS stations installed throughout the European continent. The EPN Central Bureau (CB) performs the day-to-day EPN coordination, acts as liaison between station operators, data centers, and analysis centers, and maintains the EPN Information System. Over the last years, the EPN CB has accommodated the enhancements required by the new EU General Data Protection Regulation, new multi-GNSS signals, new RINEX formats, increased usage of real-time GNSS data, and the new GeodesyML metadata exchange format. We will discuss how the EPN CB validates and provides access to EPN station metadata and monitors EPN data sets in terms of availability, latency, and quality to ensure they meet the user requirements. The analysis of 23 years of EPN GNSS data quality checks demonstrates some of the most frequently encountered tracking problems affecting EPN stations, and specific GNSS receiver types, throughout the years. Numéro de notice : A2019-332 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-019-0880-9 date de publication en ligne : 02/08/2019 En ligne : https://doi.org/10.1007/s10291-019-0880-9 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93420 [article]

A crowdsourcing-based game for land cover validation / Maria Antonia Brovelli in Applied geomatics, vol 10 n° 1 (March 2018)  

Public [article]  inApplied geomatics > vol 10 n° 1 (March 2018) . - pp 1 - 11 Titre : A crowdsourcing-based game for land cover validation Type de document : Article/Communication Auteurs : Maria Antonia Brovelli, Auteur ; Irene Celino, Auteur ; Andrea Fiano, Auteur ; Monia Elisa Molinari, Auteur ; Vijaycharan Venkatachalam, Auteur Année de publication : 2018 Article en page(s) : pp 1 - 11 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] Côme [Termes descripteurs IGN] jeu [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] participation du public [Termes descripteurs IGN] production participative [Termes descripteurs IGN] QGIS [Termes descripteurs IGN] science citoyenne [Termes descripteurs IGN] validation des données Mots-clés libres : Game With A Purpose Résumé : (Auteur) Land cover datasets are critical environmental information which are becoming increasingly available nowadays as open data. Accuracy of these datasets is key for their use in manifold applications and can be obtained through validation processes, e.g., the intercomparison with other existing land cover data. The results of this procedure usually highlight disagreements between the compared products which should be further analyzed. The presented work has the aim to address this need by proposing an innovative crowdsourcing-based game that engages citizens in validating disagreements between land cover datasets. The game was played during the Free and Open Source Software for Geospatial (FOSS4G) Europe Conference 2015 by the conference participants and allowed to evaluate the disagreements between the GlobeLand30 and the DUSAF land cover datasets on the Como city area (Italy). The results show the feasibility of the proposed approach and the potentiality of gaming in user engagement for land cover validation campaigns. Numéro de notice : A2018-157 Affiliation des auteurs : non IGN Thématique : IMAGERIE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-017-0201-3 date de publication en ligne : 29/11/2017 En ligne : https://doi.org/10.1007/s12518-017-0201-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89776 [article]

The Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data / Alby D. Rocha in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 133 (November 2017) . - pp 61 - 74 Titre : The Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data Type de document : Article/Communication Auteurs : Alby D. Rocha, Auteur ; Thomas A. Groen, Auteur ; Andrew K. Skidmore, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 61 - 74 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] complexité [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] optimisation (mathématiques) [Termes descripteurs IGN] précision [Termes descripteurs IGN] régression [Termes descripteurs IGN] validation des données Résumé : (Auteur) The growing number of narrow spectral bands in hyperspectral remote sensing improves the capacity to describe and predict biological processes in ecosystems. But it also poses a challenge to fit empirical models based on such high dimensional data, which often contain correlated and noisy predictors. As sample sizes, to train and validate empirical models, seem not to be increasing at the same rate, overfitting has become a serious concern. Overly complex models lead to overfitting by capturing more than the underlying relationship, and also through fitting random noise in the data. Many regression techniques claim to overcome these problems by using different strategies to constrain complexity, such as limiting the number of terms in the model, by creating latent variables or by shrinking parameter coefficients. This paper is proposing a new method, named Naïve Overfitting Index Selection (NOIS), which makes use of artificially generated spectra, to quantify the relative model overfitting and to select an optimal model complexity supported by the data. The robustness of this new method is assessed by comparing it to a traditional model selection based on cross-validation. The optimal model complexity is determined for seven different regression techniques, such as partial least squares regression, support vector machine, artificial neural network and tree-based regressions using five hyperspectral datasets. The NOIS method selects less complex models, which present accuracies similar to the cross-validation method. The NOIS method reduces the chance of overfitting, thereby avoiding models that present accurate predictions that are only valid for the data used, and too complex to make inferences about the underlying process. Numéro de notice : A2017-722 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.09.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.09.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88407 [article]

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Control quality of open source Digital Elevation Models (DEMs) in Tunisia / Noamen Rebaï in Revue internationale de géomatique, vol 27 n° 2 (avril - juin 2017)  

Public [article]  inRevue internationale de géomatique > vol 27 n° 2 (avril - juin 2017) . - pp 269 - 291 Titre : Control quality of open source Digital Elevation Models (DEMs) in Tunisia Type de document : Article/Communication Auteurs : Noamen Rebaï, Auteur ; Hammadi Achour, Auteur Année de publication : 2017 Article en page(s) : pp 269 - 291 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] altitude moyenne [Termes descripteurs IGN] code source libre [Termes descripteurs IGN] contrôle qualité [Termes descripteurs IGN] données GPS [Termes descripteurs IGN] Global Multi-resolution Terrain Elevation Data 2010 [Termes descripteurs IGN] MNS ASTER [Termes descripteurs IGN] MNS SRTM [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] précision métrique [Termes descripteurs IGN] Tunisie [Termes descripteurs IGN] validation des données Résumé : (Auteur) Digital Elevation Models (DEMs) are an invaluable source of information in large area studies. Some of the DEMs such as Advanced Spaceborne Thermal Emission Radiometer-Global Digital Elevation Model (ASTER GDEM), shuttle radar topography mission (SRTM), and Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) are,freely available for the scientific community worldwide. Prior to any application, global datasets of DEMs should he evaluated using reference data of higher accuracy. Therefore, the main objective of this study is to assess the quality of the ASTER GDEM (version 2), SRTM (version 4) and systematic subsample GMTED2010 in Tunisia. The validation process, adopted here, is based on two main approaches: internai and external validations. The internai validation is achieved by petforming visual inspection of shaded relief images extracted from the three DEMs. At this level, results show that SRTM is essentially similar to ASTER GDEM2 in term of relief features representation. In the second alternative, the vertical accuracy of each DEM is evaluated using 60 Global Positioning System (GPS) validation points. The overall vertical accuracy shows RMSE error of 11.96 m, 8.65 m and 10.86 m for ASTER GDEM2, SRTM and GMTED2010 DEM respectively, in comparison with GPS elevation points. Numéro de notice : A2017-389 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article En ligne : http://dx.doi.org/10.3166/rig.2017.00017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85822 [article]

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Generalizing the prediction sum of squares statistic and formula, application to linear fractional image warp and surface fitting / Adrien Bartoli in International journal of computer vision, vol 122 n° 1 (March 2017)  

Public [article]  inInternational journal of computer vision > vol 122 n° 1 (March 2017) . - pp 61 – 83 Titre : Generalizing the prediction sum of squares statistic and formula, application to linear fractional image warp and surface fitting Type de document : Article/Communication Auteurs : Adrien Bartoli, Auteur Année de publication : 2017 Article en page(s) : pp 61 – 83 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse d'image numérique [Termes descripteurs IGN] carte de profondeur [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] reconstruction automatique [Termes descripteurs IGN] reconstruction d'image [Termes descripteurs IGN] reconstruction d'objet [Termes descripteurs IGN] régression [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] validation des données Résumé : (auteur) The prediction sum of squares statistic uses the principle of leave-one-out cross-validation in linear least squares regression. It is computationally attractive, as it can be computed non-iteratively. However, it has limitations: it does not handle coupled measurements, which should be held out simultaneously, and is specific to the principle of leave-one-out, which is known to overfit when used for selecting a model’s complexity. We propose multiple-exclusion PRESS (MEXPRESS), which generalizes PRESS to coupled measurements and other types of cross-validation, while retaining computational efficiency with the non-iterative MEXPRESS formula. Using MEXPRESS, various strategies to resolve overfitting can be efficiently implemented. The core principle is to exclude training data too ‘close’ or too ‘similar’ to the validation data. We show that this allows one to select the number of control points automatically in three cases: (i) the estimation of linear fractional warps for dense image registration from point correspondences, (ii) surface reconstruction from a dense depth-map obtained by a depth sensor and (iii) surface reconstruction from a sparse point cloud obtained by shape-from-template. Numéro de notice : A2017-277 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article En ligne : https://doi.org/10.1007/s11263-016-0954-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85922 [article]

Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping / L. Drăguț in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)  

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Accuracy Validation of Large-scale Block Adjustment without Control of ZY3 Images over China / Yang Bo in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, III-1 (July 2016)  

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Position validation in crowdsourced accessibility mapping / Rebecca M. Rice in Cartographica, vol 51 n° 2 (Summer 2016)  

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Faire des SIG avec et pour les citoyens / J. Ingensand in Géomatique suisse, vol 114 n° 3 (mars 2016)

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Validation of INSPIRE metadata, data and services / Dominique Laurent (2016) 

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Forest 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)  

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Estimation of multi-constellation GNSS observation stochastic properties using single receiver single satellite data validation method / A. El-Mowafy in Survey review, vol 47 n° 341 (March 2015)  

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Modélisation graphique et validation formelle de politiques RBAC en systèmes d’information. Plateforme B4MSecure / Akram Idani in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 19 n° 6 (novembre - décembre 2014)  

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Providing reliable user reports from the emergency scene for better situation awareness using EMdroid mobile application / Nikola Davidovic in Revue internationale de géomatique, vol 23 n° 3 - 4 (septembre 2013 - février 2014)

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Evaluation of SMOS soil moisture products over continental U.S. using the SCAN/SNOTEL network / A. Al Bitar in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 1 (May 2012)  

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