Centre dedocumentation
scientifique

Geo-environment risk assessment in Zhengzhou City, China / Chuanming Ma in Geomatics, Natural Hazards and Risk, vol 11 n° 1 (2020)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 11 n° 1 (2020) . - pp 40 - 70 Titre : Geo-environment risk assessment in Zhengzhou City, China Type de document : Article/Communication Auteurs : Chuanming Ma, Auteur ; Wu Yan, Auteur ; Xinjie Hu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 40 - 70 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] cartographie des risques [Termes IGN] Chine [Termes IGN] effondrement de terrain [Termes IGN] évaluation des données [Termes IGN] gestion des risques [Termes IGN] pollution des eaux [Termes IGN] processus d'analyse hiérarchique [Termes IGN] risque environnemental [Termes IGN] séisme [Termes IGN] structure hiérarchique de données [Termes IGN] surveillance géologique [Termes IGN] urbanisme [Termes IGN] zone urbaine dense Résumé : (auteur) The urban geological environment risk assessment is based on the research and analysis of the main geological environmental problems of the city, comprehensively assessing the risk of urban geological environment problems and the possible losses, and studying the degree of matching between the natural and social attributes of the geological environment. According to the urban planning of Zhengzhou City, the different types of functional areas of the city were used as evaluation objects, and the analytic hierarchy-composite index model was used to evaluate the geological environment risk and social economic vulnerability. The risk assessment model was used to evaluate the geological environment risk of Zhengzhou City. The evaluation results show that the area of high-risk area in Zhengzhou accounts for 4.05%; the area of medium-high risk area accounts for 12.89%; the area of medium-low and low-risk area accounts for 83.06%. According to the assessment results, suggestions are put forward to provide service for the urban planning, development and risk management. Highlights: * An urban geo-environment risk assessment technique system combining with the AHP - composite index assessment model is proposed. * Different types of functional zones in Zhengzhou City are taken as assessment units. * Geo-environment risk in Zhengzhou City is qualitatively and quantitatively evaluated. Numéro de notice : A2020-565 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475705.2019.1701571 date de publication en ligne : 27/12/2019 En ligne : https://doi.org/10.1080/19475705.2019.1701571 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95890 [article]

Micro-tasking as a method for human assessment and quality control in a geospatial data import / Atle Frenvik Sveen in Cartography and Geographic Information Science, vol 47 n° 2 (February 2020)  

Public [article]  inCartography and Geographic Information Science > vol 47 n° 2 (February 2020) . - pp 141 - 152 Titre : Micro-tasking as a method for human assessment and quality control in a geospatial data import Type de document : Article/Communication Auteurs : Atle Frenvik Sveen, Auteur ; Anne Sofie Strom Erichsen, Auteur ; Terje Midtbo, Auteur Année de publication : 2020 Article en page(s) : pp 141 - 152 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] algorithme de filtrage [Termes IGN] chevauchement [Termes IGN] contrôle qualité [Termes IGN] données localisées [Termes IGN] données localisées des bénévoles [Termes IGN] évaluation des données [Termes IGN] import de données [Termes IGN] OpenStreetMap [Termes IGN] précision des données [Termes IGN] production participative Résumé : (auteur) Crowd-sourced geospatial data can often be enriched by importing open governmental datasets as long as they are up-to date and of good quality. Unfortunately, merging datasets is not straight forward. In the context of geospatial data, spatial overlaps pose a particular problem, as existing data may be overwritten when a naïve, automated import strategy is employed. For example: OpenStreetMap has imported over 100 open geospatial datasets, but the requirement for human assessment makes this a time-consuming process which requires experienced volunteers or training. In this paper, we propose a hybrid import workflow that combines algorithmic filtering with human assessment using the micro-tasking method. This enables human assessment without the need for complex tools or prior experience. Using an online experiment, we investigated how import speed and accuracy is affected by volunteer experience and partitioning of the micro-task. We conclude that micro-tasking is a viable method for massive quality assessment that does not require volunteers to have prior experience working with geospatial data. Numéro de notice : A2020-058 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2019.1659187 date de publication en ligne : 16/09/2020 En ligne : https://doi.org/10.1080/15230406.2019.1659187 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94575 [article]

Geometric comparison and quality evaluation of 3D models of indoor environments / H. Tran in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 149 (March 2019) . - pp 29 - 39 Titre : Geometric comparison and quality evaluation of 3D models of indoor environments Type de document : Article/Communication Auteurs : H. Tran, Auteur ; Kourosh Khoshelham, Auteur ; Allison Kealy, Auteur Année de publication : 2019 Article en page(s) : pp 29 - 39 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] analyse comparative [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] erreur géométrique [Termes IGN] espace intérieur [Termes IGN] évaluation des données [Termes IGN] modèle 3D du site [Termes IGN] positionnement en intérieur [Termes IGN] qualité des données [Termes IGN] reconstruction 3D du bâti [Termes IGN] semis de points [Termes IGN] test de performance Résumé : (Auteur) The increasing demand for automated, cost-effective and time-efficient indoor modelling methods leads to a need for performance evaluation of these methods by assessing the quality of the reconstructed models. In this paper, we introduce a method for geometric comparison of a 3D indoor model with a reference, which is useful not only for evaluating the geometric quality of the model, but also for change detection and temporal analysis of the building. The method provides suitable criteria for the quantitative evaluation of the geometric quality in terms of completeness, correctness, and accuracy. Experimental evaluation on a synthetic dataset and the ISPRS benchmark dataset shows the potential of the proposed method for quantitative evaluation and localization of geometric errors in 3D models of indoor environments. Numéro de notice : A2019-126 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.012 date de publication en ligne : 19/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.012 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92436 [article]

Réservation

Réserver ce document

Exemplaires (3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2019031	RAB	Revue	Centre de documentation	En réserve 3L	Disponible
081-2019033	DEP-RECP	Revue	LaSTIG	Dépôt en unité	Exclu du prêt
081-2019032	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Accuracy assessment of the global TanDEM-X Digital Elevation Model with GPS data / Birgit Wessel in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 139 (May 2018) . - pp 171 - 182 Titre : Accuracy assessment of the global TanDEM-X Digital Elevation Model with GPS data Type de document : Article/Communication Auteurs : Birgit Wessel, Auteur ; Martin Huber, Auteur ; Christian Wohlfart, Auteur ; Ursula Marschalk, Auteur ; Detlev Kosmann, Auteur ; Achim Roth, Auteur Année de publication : 2018 Article en page(s) : pp 171 - 182 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] erreur en altitude [Termes IGN] évaluation des données [Termes IGN] MNS TerraSAR & TanDEM-X [Termes IGN] modèle numérique de surface [Termes IGN] précision de localisation Résumé : (Auteur) The primary goal of the German TanDEM-X mission is the generation of a highly accurate and global Digital Elevation Model (DEM) with global accuracies of at least 10 m absolute height error (linear 90% error). The global TanDEM-X DEM acquired with single-pass SAR interferometry was finished in September 2016. This paper provides a unique accuracy assessment of the final TanDEM-X global DEM using two different GPS point reference data sets, which are distributed across all continents, to fully characterize the absolute height error. Firstly, the absolute vertical accuracy is examined by about three million globally distributed kinematic GPS (KGPS) points derived from 19 KGPS tracks covering a total length of about 66,000 km. Secondly, a comparison is performed with more than 23,000 “GPS on Bench Marks” (GPS-on-BM) points provided by the US National Geodetic Survey (NGS) scattered across 14 different land cover types of the US National Land Cover Data base (NLCD). Both GPS comparisons prove an absolute vertical mean error of TanDEM-X DEM smaller than ±0.20 m, a Root Means Square Error (RMSE) smaller than 1.4 m and an excellent absolute 90% linear height error below 2 m. The RMSE values are sensitive to land cover types. For low vegetation the RMSE is ±1.1 m, whereas it is slightly higher for developed areas (±1.4 m) and for forests (±1.8 m). This validation confirms an outstanding absolute height error at 90% confidence level of the global TanDEM-X DEM outperforming the requirement by a factor of five. Due to its extensive and globally distributed reference data sets, this study is of considerable interests for scientific and commercial applications. Numéro de notice : A2018-611 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.02.017 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.02.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89551 [article]

Réservation

Réserver ce document

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018051	RAB	Revue	Centre de documentation	En réserve 3L	Disponible

A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information / Lívia Castro Degrossi in Transactions in GIS, vol 22 n° 2 (April 2018)  

Public [article]  inTransactions in GIS > vol 22 n° 2 (April 2018) . - pp 542 - 560 Titre : A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information Type de document : Article/Communication Auteurs : Lívia Castro Degrossi, Auteur ; João Porto de Albuquerque, Auteur ; Roberto dos Santos Rocha, Auteur ; Alexander Zipf, Auteur Année de publication : 2018 Article en page(s) : pp 542 - 560 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] cartographie collaborative [Termes IGN] données localisées des bénévoles [Termes IGN] évaluation des données [Termes IGN] production participative [Termes IGN] qualité des données [Termes IGN] taxinomie Résumé : (Auteur) The growing use of crowdsourced geographic information (CGI) has prompted the employment of several methods for assessing information quality, which are aimed at addressing concerns on the lack of quality of the information provided by non‐experts. In this work, we propose a taxonomy of methods for assessing the quality of CGI when no reference data are available, which is likely to be the most common situation in practice. Our taxonomy includes 11 quality assessment methods that were identified by means of a systematic literature review. These methods are described in detail, including their main characteristics and limitations. This taxonomy not only provides a systematic and comprehensive account of the existing set of methods for CGI quality assessment, but also enables researchers working on the quality of CGI in various sources (e.g., social media, crowd sensing, collaborative mapping) to learn from each other, thus opening up avenues for future work that combines and extends existing methods into new application areas and domains. Numéro de notice : A2018-217 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12329 date de publication en ligne : 19/04/2018 En ligne : https://doi.org/10.1111/tgis.12329 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90008 [article]

3D micro-mapping : Towards assessing the quality of crowdsourcing to support 3D point cloud analysis / Benjamin Herfort in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)  

Permalink

Improvements in precise orbits of altimetry satellites and their impact on mean sea level monitoring / Sergei Rudenko in IEEE Transactions on geoscience and remote sensing, vol 55 n° 6 (June 2017)  

Permalink

Evaluation of the range accuracy and the radiometric calibration of multiple terrestrial laser scanning instruments for data interoperability / Kim Calders in IEEE Transactions on geoscience and remote sensing, vol 55 n° 5 (May 2017)  

Permalink

Assessing crowdsourced POI quality: combining methods based on reference data, history, and spatial relations / Guillaume Touya in ISPRS International journal of geo-information, vol 6 n° 3 (March 2017)  

Permalink

Crowd and community sourced data quality assessment / Laurence Jolivet (2017)  

Permalink

Évaluation de la qualité des sources du Web de Données pour la résolution d'entités nommées / Carmen Brando in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 21 n° 5 - 6 (septembre - décembre 2016)  

Permalink

Stem quality assessment in European National Forest Inventories: an opportunity for harmonised reporting? / Michal Bosela in Annals of Forest Science [en ligne], vol 73 n° 3 (September 2016)  

Permalink

Radiometric correction of airborne radar images over forested terrain with topography / Marc Simard in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)  

Permalink

Pan-sharpening quality investigation of PLÉIADES-1A images / Mustafa Ozendi in Geocarto international, vol 31 n° 7 - 8 (July - August 2016)  

Permalink

Rethinking big data: A review on the data quality and usage issues / Jianzheng Liu in ISPRS Journal of photogrammetry and remote sensing, vol 115 (May 2016)  

Permalink