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A GIS representation framework for location-based social media activities / Xuebin Wei in Transactions in GIS, vol 26 n° 3 (May 2022)
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Titre : A GIS representation framework for location-based social media activities Type de document : Article/Communication Auteurs : Xuebin Wei, Auteur ; Xiaobai Yao, Auteur Année de publication : 2022 Article en page(s) : pp 1444 - 1464 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] cadre conceptuel
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] environnement géographique virtuel
[Termes IGN] Facebook
[Termes IGN] modèle conceptuel de données spatio-temporelles
[Termes IGN] ontologie
[Termes IGN] relations sociales
[Termes IGN] représentation des données
[Termes IGN] réseau social géodépendant
[Termes IGN] système d'information géographique
[Termes IGN] Time-geographyRésumé : (auteur) The past couple of decades have witnessed tremendous growth of location-based social media activities (LBSMA) data in virtual spaces, including virtual geographic environments. Such data become innovative resources for the analysis of human activities. Meanwhile, a shift of human interactions from geographical spaces to virtual spaces has been observed. Although this is an exciting research opportunity, it also imposes significant challenges on GIScience, as current GIS representation models are no longer sufficient to handle the increased sophistication of human activities data. This research formalizes an ontology for LBSMA data and a conceptual framework for representing such data in GIS. The framework contributes to GIScience as it enables interconnections of human activities in both the physical and virtual worlds to be represented, organized, retrieved, analyzed, and visualized. The proposed GIS representation model integrates a social dimension into the existing spatial–temporal representation models and allows data analysis in the spatial–temporal–social (STS) dimensions. The research tested this conceptual framework with a prototype and a case study using Facebook data. The prototype and the case study prove that the proposed framework can significantly enhance GIS capabilities for data organization, retrieval, and analysis of LBSMA data in STS dimensions. Numéro de notice : A2022-477 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article DOI : 10.1111/tgis.12929 Date de publication en ligne : 02/05/2022 En ligne : https://doi.org/10.1111/tgis.12929 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100825
in Transactions in GIS > vol 26 n° 3 (May 2022) . - pp 1444 - 1464[article]HiPerMovelets: high-performance movelet extraction for trajectory classification / Tarlis Tortelli Portela in International journal of geographical information science IJGIS, vol 36 n° 5 (May 2022)
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Titre : HiPerMovelets: high-performance movelet extraction for trajectory classification Type de document : Article/Communication Auteurs : Tarlis Tortelli Portela, Auteur ; Jonata Tyska Carvalho, Auteur ; Vania Bogorny, Auteur Année de publication : 2022 Article en page(s) : pp 1012 - 1036 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] classification
[Termes IGN] exploration de données géographiques
[Termes IGN] jeu de données localisées
[Termes IGN] trace numérique
[Termes IGN] trajet (mobilité)Résumé : (auteur) In the last decade, trajectory classification has received significant attention. The vast amount of data generated on social media, the use of sensor networks, IOT devices and other Internet-enabled sources allowed the semantic enrichment of mobility data, making the classification task more challenging. Existing trajectory classification methods have mainly considered space, time and numerical data, ignoring the semantic dimensions. Only recently proposed methods as Movelets and MASTERMovelets can handle all types of dimensions. MASTERMovelets is the only method that automatically discovers the best dimension combination and subtrajectory size for trajectory classification. However, although it outperformed the state-of-the-art in terms of accuracy, MASTERMovelets is computationally expensive and results in a high dimensionality problem, which makes it unfeasible for most real trajectory datasets that contain a big volume of data. To overcome this problem and enable the application of the movelets approach on large datasets, in this paper we propose a new high-performance method for extracting movelets and classifying trajectories, called HiPerMovelets (High-performance Movelets). Experimental results show that HiPerMovelets is 10 times faster than MASTERMovelets, reduces the high-dimensionality problem, is more scalable, and presents a high classification accuracy in all evaluated datasets with both raw and semantic trajectories. Numéro de notice : A2022-332 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2021.2018593 Date de publication en ligne : 03/01/2022 En ligne : https://doi.org/10.1080/13658816.2021.2018593 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100608
in International journal of geographical information science IJGIS > vol 36 n° 5 (May 2022) . - pp 1012 - 1036[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2022051 SL Revue Centre de documentation Revues en salle Disponible How do voice-assisted digital maps influence human wayfinding in pedestrian navigation? / Yawei Xu in Cartography and Geographic Information Science, vol 49 n° 3 (May 2022)
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Titre : How do voice-assisted digital maps influence human wayfinding in pedestrian navigation? Type de document : Article/Communication Auteurs : Yawei Xu, Auteur ; Tong Qin, Auteur ; Yulin Wu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 271 - 287 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie numérique
[Termes IGN] acquisition de connaissances
[Termes IGN] cognition
[Termes IGN] comportement
[Termes IGN] itinéraire piétionnier
[Termes IGN] navigation pédestre
[Termes IGN] oculométrie
[Termes IGN] orientation
[Termes IGN] Pékin (Chine)
[Termes IGN] questionnaireRésumé : (auteur) Voice-assisted digital maps have become mainstream navigation aids for pedestrian navigation. Although these maps are widely studied and applied, it is still unclear how they affect human behavior and spatial knowledge acquisition. In this study, we recruited thirty-three college students to carry out an outdoor wayfinding experiment. We compared the effects of voice-assisted digital maps with those of digital maps without voice instructions and paper maps by using eye tracking, sketch maps, questionnaires and interviews. The results show that, compared to the other map types, voice-assisted digital maps can help users reach their destinations more quickly and pay more attention to moving objects, thereby increasing the comfort levels of participants. However, the efficiency of voice-assisted maps on route memory tasks does not rival that of paper maps. Overall, the use of voice-assisted digital maps saves time but may reduce pedestrians’ spatial knowledge acquisition. The results of this study reveal the influence of voice on pedestrian wayfinding and deepen the scientific understanding of the multimedia navigation mode in shaping human spatial ability. Numéro de notice : A2022-295 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2021.2017798 Date de publication en ligne : 13/01/2022 En ligne : https://doi.org/10.1080/15230406.2021.2017798 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100347
in Cartography and Geographic Information Science > vol 49 n° 3 (May 2022) . - pp 271 - 287[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2022031 RAB Revue Centre de documentation En réserve L003 Disponible Impacts of spatiotemporal resolution and tiling on SLEUTH model calibration and forecasting for urban areas with unregulated growth patterns / Damilola Eyelade in International journal of geographical information science IJGIS, vol 36 n° 5 (May 2022)
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Titre : Impacts of spatiotemporal resolution and tiling on SLEUTH model calibration and forecasting for urban areas with unregulated growth patterns Type de document : Article/Communication Auteurs : Damilola Eyelade, Auteur ; Keith C. Clarke, Auteur ; Ighodalo Ijagbone, Auteur Année de publication : 2022 Article en page(s) : pp 1037 - 1058 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] changement d'utilisation du sol
[Termes IGN] croissance urbaine
[Termes IGN] dalle
[Termes IGN] données spatiotemporelles
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle de simulation
[Termes IGN] modélisation spatiale
[Termes IGN] Nigéria
[Termes IGN] OpenStreetMapRésumé : (auteur) The SLEUTH model provides a framework for understanding land use evolution around urban areas. Calibration of SLEUTH’s behavioral coefficients can be impacted by scale and nonlinear transitions due to the SLEUTH land use deltatron module’s assumption of linear Markov change probabilities. This study attempted to establish what spatial resolution and temporal scale produces the most accurate forecasts given the linear change assumption. The impact of tiling the input data was also examined. To determine these, SLEUTH was calibrated at four spatial and three temporal scales for Ibadan, Nigeria using both untiled and tiled data. Calibration results were evaluated using accuracy metrics including Figure of Merit (FOM) and mean uncertainty. The best mix of calibration metrics (FOM 0.26) and mean uncertainty (11.64) was achieved at 30 m resolution and an intermediate temporal interval. Tiling input data led to overfitting, allowing good model fit within individual tiles but a reduction in trend recognition across land use types. Subsequently, a 2040 projection that is as accurate as possible, and scientifically justifiable given the available data, was produced. The findings provide a framework for understanding the effect of spatiotemporal scale on SLEUTH inputs that require tiling particularly for urban areas in the global south. Numéro de notice : A2022-347 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.2011292 Date de publication en ligne : 16/12/2021 En ligne : https://doi.org/10.1080/13658816.2021.2011292 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100531
in International journal of geographical information science IJGIS > vol 36 n° 5 (May 2022) . - pp 1037 - 1058[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2022051 SL Revue Centre de documentation Revues en salle Disponible Mapping and prediction of soil organic carbon by an advanced geostatistical technique using remote sensing and terrain data / Santanu Malik in Geocarto international, vol 37 n° 8 ([01/05/2022])
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Titre : Mapping and prediction of soil organic carbon by an advanced geostatistical technique using remote sensing and terrain data Type de document : Article/Communication Auteurs : Santanu Malik, Auteur ; Tridip Bhowmik, Auteur ; Umesh Mishra, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2198 - 2214 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte d'occupation du sol
[Termes IGN] estimation bayesienne
[Termes IGN] géostatistique
[Termes IGN] gestion durable
[Termes IGN] Inde
[Termes IGN] krigeage
[Termes IGN] modèle de simulation
[Termes IGN] puits de carbone
[Termes IGN] régression
[Termes IGN] réseau neuronal artificiel
[Termes IGN] sol arableRésumé : (auteur) Prediction and accurate digital soil mapping (DSM) of soil organic carbon (SOC) at a local scale is a key factor for any agro-ecological modelling. This study aims to use remote sensing and terrain derivatives to provide a reliable method for SOC prediction. An advanced geostatistical-based empirical Bayesian Kriging regression (EBKR) method was used and performance was compared with the artificial neural network (ANN) and hybrid ANN, i.e. ANN-OK (ordinary kriging) and ANN-CK (cokriging). The result showed that the hybrid ANN model performs better than ANN, whereas the EBKR method outperforms all other methods with the highest R2 of 0.936. The DSM map shows that the highest SOC concentration was found in easternmost part of the study area with grass and agricultural land. This work shows the robustness of the EBKR prediction method over other techniques. The study will also aid the policymakers in adopting sustainable land use management. Numéro de notice : A2022-505 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1815864 Date de publication en ligne : 24/09/2020 En ligne : https://doi.org/10.1080/10106049.2020.1815864 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101026
in Geocarto international > vol 37 n° 8 [01/05/2022] . - pp 2198 - 2214[article]Multi-modal temporal attention models for crop mapping from satellite time series / Vivien Sainte Fare Garnot in ISPRS Journal of photogrammetry and remote sensing, vol 187 (May 2022)
PermalinkPerformance analysis of low-cost GNSS stations for structural health monitoring of civil engineering structures / Nicolas Manzini in Structure and Infrastructure Engineering, vol 18 n° 5 ([01/05/2022])
PermalinkProduction of optimum forest roads and comparison of these routes with current forest roads: a case study in Maçka, Turkey / Faruk Yildirim in Geocarto international, vol 37 n° 8 ([01/05/2022])
PermalinkProxemic maps for immersive visualization / Zeinab Ghaemi in Cartography and Geographic Information Science, vol 49 n° 3 (May 2022)
PermalinkA review of maps in PhDs: Is your map worth a thousand words? / Serena Coetzee in Cartographic journal (the), vol 59 n° 2 (May 2022)
PermalinkRevising cadastral data on land boundaries using deep learning in image-based mapping / Bujar Fetai in ISPRS International journal of geo-information, vol 11 n° 5 (May 2022)
PermalinkSwipe versus multiple view: a comprehensive analysis using eye-tracking to evaluate user interaction with web maps / Stanislav Popelka in Cartography and Geographic Information Science, vol 49 n° 3 (May 2022)
PermalinkUnsupervised multi-view CNN for salient view selection and 3D interest point detection / Ran Song in International journal of computer vision, vol 130 n° 5 (May 2022)
PermalinkPermalinkWeakly supervised semantic segmentation of airborne laser scanning point clouds / Yaping Lin in ISPRS Journal of photogrammetry and remote sensing, vol 187 (May 2022)
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