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Point-of-interest (POI) data validation methods: An urban case study / Lih Wei Yeow in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 11 (November 2021) . - n° 735 Titre : Point-of-interest (POI) data validation methods: An urban case study Type de document : Article/Communication Auteurs : Lih Wei Yeow, Auteur ; Raymond Low, Auteur ; Yu Xiang Tan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 735 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] analyse spatiale [Termes IGN] données cartographiques [Termes IGN] données issues des réseaux sociaux [Termes IGN] données localisées des bénévoles [Termes IGN] erreur de positionnement [Termes IGN] OpenStreetMap [Termes IGN] point d'intérêt [Termes IGN] qualité des données [Termes IGN] Singapour [Termes IGN] validation des données Résumé : (auteur) Point-of-interest (POI) data from map sources are increasingly used in a wide range of applications, including real estate, land use, and transport planning. However, uncertainties in data quality arise from the fact that some of this data are crowdsourced and proprietary validation workflows lack transparency. Comparing data quality between POI sources without standardized validation metrics is a challenge. This study reviews and implements the available POI validation methods, working towards identifying a set of metrics that is applicable across datasets. Twenty-three validation methods were found and categorized. Most methods evaluated positional accuracy, while logical consistency and usability were the least represented. A subset of nine methods was implemented to assess four real-world POI datasets extracted for a highly urbanized neighborhood in Singapore. The datasets were found to have poor completeness with errors of commission and omission, although spatial errors were reasonably low ( Numéro de notice : A2021-830 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10110735 Date de publication en ligne : 29/10/2021 En ligne : https://doi.org/10.3390/ijgi10110735 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98968 [article]

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 IGN] métadonnées géographiques [Termes IGN] qualité des metadonnées [Termes IGN] récepteur GNSS [Termes IGN] réseau permanent EUREF [Termes IGN] station GNSS [Termes 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 IGN] Italie [Termes IGN] jeu [Termes IGN] occupation du sol [Termes IGN] participation du public [Termes IGN] production participative [Termes IGN] QGIS [Termes IGN] science citoyenne [Termes 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 IGN] complexité [Termes IGN] image hyperspectrale [Termes IGN] méthode robuste [Termes IGN] modèle de simulation [Termes IGN] optimisation (mathématiques) [Termes IGN] précision [Termes IGN] régression [Termes 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 IGN] altitude moyenne [Termes IGN] code source libre [Termes IGN] contrôle qualité [Termes IGN] données GPS [Termes IGN] Global Multi-resolution Terrain Elevation Data 2010 [Termes IGN] MNS ASTER [Termes IGN] MNS SRTM [Termes IGN] modèle numérique de surface [Termes IGN] précision métrique [Termes IGN] Tunisie [Termes 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 DOI : 10.3166/rig.2017.00017 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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