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A general model for creating robust choropleth maps / Wangshu Mu in Computers, Environment and Urban Systems, vol 96 (September 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 96 (September 2022) . - n° 101850 Titre : A general model for creating robust choropleth maps Type de document : Article/Communication Auteurs : Wangshu Mu, Auteur ; Daoqin Tong, Auteur Année de publication : 2022 Article en page(s) : n° 101850 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie [Termes IGN] carte choroplèthe [Termes IGN] incertitude des données [Termes IGN] méthode du maximum de vraisemblance (estimation) [Termes IGN] méthode robuste [Termes IGN] optimisation par essaim de particules [Termes IGN] programmation dynamique Résumé : (auteur) Choropleth maps visualize areal geographical data by grouping data into a few map classes and assigning different colors, shades, or patterns. Recent studies show that data uncertainty, commonly observed in real-life applications, should also be accounted for when determining the best classification scheme. Due to data uncertainty, a few studies note that map units might be placed in a wrong class, and the concept of map robustness has been introduced to minimize such misplacement. Recently, an algorithm has been developed to integrate robustness into the design of the optimal map classification scheme. However, the existing algorithm has two limitations: first, it is only suitable for certain robustness metrics. Second, when identifying the optimal class breaks, the existing algorithm requires predefined candidate class break values, which might lead to sub-optimal solutions. This paper resolves these issues by proposing a new model, namely, the Continuous Robust Map Classification Problem (CRMCP), and the associated solution approach. The CRMCP allows mapmakers to customize robustness metrics according to their data and applications. In addition, a particle swarm optimization algorithm is developed to solve the CRMCP. The model and algorithm are tested using American Community Survey data. Test results suggest that the new approach can find better solutions than the existing algorithm. The study improves the usability of choropleth maps when uncertain geographical attributes are involved and allows spatial analysts and decision-makers to incorporate robustness into the mapmaking process more flexibly. Numéro de notice : A2022-514 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101850 Date de publication en ligne : 28/06/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101850 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101055 [article]

Outliers and uncertainties in GNSS ZTD estimates from double-difference processing and precise point positioning / Katarzyna Stępniak in GPS solutions, vol 26 n° 3 (July 2022)  

Public [article]  inGPS solutions > vol 26 n° 3 (July 2022) . - n° 74 Titre : Outliers and uncertainties in GNSS ZTD estimates from double-difference processing and precise point positioning Type de document : Article/Communication Auteurs : Katarzyna Stępniak, Auteur ; Olivier Bock , Auteur ; Pierre Bosser , Auteur ; Pawel Wielgosz, Auteur Année de publication : 2022 Projets : VEGAN / Bock, Olivier Article en page(s) : n° 74 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] données GNSS [Termes IGN] double différence [Termes IGN] ERA5 [Termes IGN] incertitude des données [Termes IGN] positionnement ponctuel précis [Termes IGN] retard troposphérique zénithal [Termes IGN] valeur aberrante [Vedettes matières IGN] Traitement de données GNSS Résumé : (auteur) Double-difference (DD) analysis and precise point positioning (PPP) are two widely used processing approaches to analyze ground-based GNSS measurements. We investigate the quality of the zenith tropospheric delay (ZTD) estimates produced from both processing approaches for a regional network over 1 year and show that DD solutions contain more numerous and larger ZTD outliers. The accuracy of both DD and PPP solutions strongly depends on the data processing procedure and models. We analyze the impact of mapping functions, satellite orbit and clock products and ambiguity resolution (fixed vs. float) on ZTD estimates. The results are assessed from station position repeatability and ZTD differences with respect to the ERA5 reanalysis. As expected, mapping functions have the strongest impact, with VMF1 being more accurate than GMF. Surprisingly, the impact of the ambiguity resolution and satellite products is rather weak in the PPP solution. We speculate that this results from the fact that final satellite products have reached a high level of accuracy and that other error sources now dominate static PPP solutions. A time and frequency analysis reveal unprecedented spurious sub-daily signals in the ZTD time series, which occur at the frequency of the GPS satellite repeat period and its harmonics. This suggests that sub-daily GPS ZTD estimates contain a significant part of the residual modeling errors due to satellite orbits, tidal models, mapping functions and multipath, which still need to be improved. Numéro de notice : A2022-359 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-022-01261-z Date de publication en ligne : 29/04/2022 En ligne : https://doi.org/10.1007/s10291-022-01261-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100578 [article]

On the consistency of coastal sea-level measurements in the Mediterranean Sea from tide gauges and satellite radar altimetry / Sara Bruni in Journal of geodesy, vol 96 n° 6 (June 2022)  

Public [article]  inJournal of geodesy > vol 96 n° 6 (June 2022) . - n° 41 Titre : On the consistency of coastal sea-level measurements in the Mediterranean Sea from tide gauges and satellite radar altimetry Type de document : Article/Communication Auteurs : Sara Bruni, Auteur ; Luciana Fenoglio, Auteur ; Fabio Raicich, Auteur ; Susanna Zerbini, Auteur Année de publication : 2022 Article en page(s) : n° 41 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] analyse comparative [Termes IGN] cohérence des données [Termes IGN] déformation verticale de la croute terrestre [Termes IGN] données altimétriques [Termes IGN] données marégraphiques [Termes IGN] Méditerranée, mer [Termes IGN] niveau de la mer Résumé : (auteur) We assess the consistency of sea-level variability derived from tide-gauge (TG) and satellite radar altimeter (ALT) data acquired along the coasts of the Mediterranean Sea. For a coherent comparison between these techniques, we use GNSS observations to characterize the local vertical land movement embedded in TG records, but not affecting ALT data. We first investigate the performance of CMEMS, a gridded altimeter product covering the period 1993–2019. TG and GNSS series are not required to cover the whole altimeter period. The inter-technique comparison reveals good agreement at annual and semi-annual scales, but also the occasional occurrence of nonlinear discrepancies impacting trend estimation. Large-scale patterns of variability are observed in the Ionian region and along the continental shores from the Alboran to the Adriatic Sea. The estimates of linear trends based on TG + GNSS or CMEMS observations are found consistent within 1σ at 27/45 sites, with the best agreement in the Western Mediterranean and Adriatic Seas. We also consider the X-TRACK/ALES altimeter dataset, provided along the tracks of the Jason missions (2002–2018) and optimized for coastal applications. In this case, we identify only 12 sites suitable for the comparison. The results show that inter-technique consistency is impacted by the length of the series used in the comparison. Optimum agreement between X-TRACK/ALES and TG + GNSS trends is reached at the two sites closer to a satellite track. However, we find sites where X-TRACK/ALES-derived sea-level trends present suspicious along-track variations at  Numéro de notice : A2022-452 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s00190-022-01626-9 En ligne : http://dx.doi.org/10.1007/s00190-022-01626-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100976 [article]

Constraint-based evaluation of map images generalized by deep learning / Azelle Courtial in Journal of Geovisualization and Spatial Analysis, vol 6 n° 1 (June 2022)  

Public [article]  inJournal of Geovisualization and Spatial Analysis > vol 6 n° 1 (June 2022) . - n° 13 Titre : Constraint-based evaluation of map images generalized by deep learning Type de document : Article/Communication Auteurs : Azelle Courtial , Auteur ; Guillaume Touya , Auteur ; Xiang Zhang, Auteur Année de publication : 2022 Projets : 2-Pas d'info accessible - article non ouvert / Bock, Olivier Article en page(s) : n° 13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond [Termes IGN] connexité (graphes) [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] montagne [Termes IGN] programmation par contraintes [Termes IGN] qualité des données [Termes IGN] rendu réaliste [Termes IGN] route [Vedettes matières IGN] Généralisation Résumé : (auteur) Deep learning techniques have recently been experimented for map generalization. Although promising, these experiments raise new problems regarding the evaluation of the output images. Traditional map generalization evaluation cannot directly be applied to the results in a raster format. Additionally, the internal evaluation used by deep learning models is mostly based on the realism of images and the accuracy of pixels, and none of these criteria is sufficient to evaluate a generalization process. Finally, deep learning processes tend to hide the causal mechanisms and do not always guarantee a result that follows cartographic principles. In this article, we propose a method to adapt constraint-based evaluation to the images generated by deep learning models. We focus on the use case of mountain road generalization, and detail seven raster-based constraints, namely, clutter, coalescence reduction, smoothness, position preservation, road connectivity preservation, noise absence, and color realism constraints. These constraints can contribute to current studies on deep learning-based map generalization, as they can help guide the learning process, compare different models, validate these models, and identify remaining problems in the output images. They can also be used to assess the quality of training examples. Numéro de notice : A2022-449 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s41651-022-00104-2 Date de publication en ligne : 07/05/2022 En ligne : http://dx.doi.org/10.1007/s41651-022-00104-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100646 [article]

Multipurpose temporal GIS model for cadastral data management / Joseph Mango in International journal of geographical information science IJGIS, vol 36 n° 6 (June 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 6 (June 2022) . - pp 1205 - 1230 Titre : Multipurpose temporal GIS model for cadastral data management Type de document : Article/Communication Auteurs : Joseph Mango, Auteur ; Christophe Claramunt, Auteur ; Jamila Ngondo, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1205 - 1230 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] données cadastrales [Termes IGN] historique des données [Termes IGN] outil d'aide à la décision [Termes IGN] parcelle cadastrale [Termes IGN] SIG temporel [Termes IGN] système d'information foncière [Termes IGN] Tanzanie [Termes IGN] Zambie Résumé : (auteur) Past and current cadastral records are among the most valuable information that different countries need to solve land management and planning problems. However, many countries still face critical challenges in adopting modern temporal cadastral systems, including a sound integration of time constructs, efficient data integration and representation methods in the designed models. This research developed a new temporal GIS model to manage spatial and non-spatial temporal cadastral data, namely cadastral parcels, land-use and land-ownerships. Three-time dimensions defined by decision and valid and transaction times were formulated to qualify parcels data. A hybrid approach fusing on the Base State with Amendment and Space-Time Composite models is used to store significant parcel changes and their relationships in two interdependent sub-databases. We used administrative plot identifiers to associate with land use and ownership records, experiencing distinct temporal variations in the third sub-database within the same main repository. We experimented our model with data from Tanzania, and the results from queries demonstrate that the designed model can store all three temporal cadastral data and track their variations semantically and effectively. This model is very useful for storing cadastral parcels, reasons, events, and the transformed parcels’ values to improve decision-making processes. Numéro de notice : A2022-406 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.2009483 Date de publication en ligne : 15/12/2022 En ligne : https://doi.org/10.1080/13658816.2021.2009483 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100719 [article]

Analysis of massive imports of open data in Openstreetmap database: a study case for France / Arnaud Le Guilcher in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-4-2022 (2022 edition)  

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Completeness assessment and improvement in mobile crowd-sensing environments / Souheir Mehanna in SN Computer Science, vol 3 n° 3 (May 2022)  

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Accuracy issues for spatial update of digital cadastral maps / David Pullar in ISPRS International journal of geo-information, vol 11 n° 4 (April 2022)  

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Identification and classification of routine locations using anonymized mobile communication data / Gonçalo Ferreira in ISPRS International journal of geo-information, vol 11 n° 4 (April 2022)  

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Automated 3D reconstruction of LoD2 and LoD1 models for All 10 million buildings of the Netherlands / Ravi Peters in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 3 (March 2022)  

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Évaluation des apports de l’apprentissage profond au sein d’un service dédié à la numérisation du patrimoine / Maxime Mérizette in XYZ, n° 170 (mars 2022)

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Mise à jour du registre de l’EPSG suite aux évolutions du RGF93 / Thierry Gattacceca in XYZ, n° 170 (mars 2022)

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Observational constraint on the climate sensitivity to atmospheric CO2 concentrations changes derived from the 1971-2017 global energy budget / Jonathan Chenal in Journal of climate, vol 2022 ([01/03/2022])  

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Analysis of factors affecting adoption of volunteered geographic information in the context of national spatial data infrastructure / Munir Ahmad in ISPRS International journal of geo-information, vol 11 n° 2 (February 2022)  

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Attention-based vandalism detection in OpenStreetMap / Nicolas Tempelmeier (2022)  

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