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Improvement of a location-aware recommender system using volunteered geographic information / Sepehr Honarparvar in Geocarto international, vol 34 n° 13 ([15/10/2019])  

Public [article]  inGeocarto international > vol 34 n° 13 [15/10/2019] . - pp1496 - 1513 Titre : Improvement of a location-aware recommender system using volunteered geographic information Type de document : Article/Communication Auteurs : Sepehr Honarparvar, Auteur ; Rouzbeh Forouzandeh Jonaghani, Auteur ; Ali Asghar Alesheikh, Auteur ; Behnam Atazadeh, Auteur Année de publication : 2019 Article en page(s) : pp1496 - 1513 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] actualité des données [Termes descripteurs IGN] approche participative [Termes descripteurs IGN] base de données localisées [Termes descripteurs IGN] classement [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] prise en compte du contexte [Termes descripteurs IGN] qualité des données [Termes descripteurs IGN] système de recommandation [Termes descripteurs IGN] utilisateur Résumé : (auteur) Recommender systems (RS), as supportive tools, filter information from a massive amount of data based on the determined preferences. Most of the RS require information about the context of users such as their locations. In such cases, location-aware recommender systems (LARS) can be employed to suggest more personalized items to the users. The most current research projects on LARS focus on the development of algorithms, evaluation methods and applications. However, the role of up-to-date spatial databases in LARS is not a well-researched area. The up-to-date spatial information would potentially improve the accuracy of items which are recommended by LARS. Volunteered geographic information (VGI) could be a low-cost source of up-to-date spatial information for LARS. This article proposes an approach to enrich spatial databases of LARS by VGI. Since not all records of VGI are fitted for use in LARS, a mechanism is developed to identify useful information. Some VGI data sets refer to existing spatial data in the database while other VGI data sets are shared for the first time. Therefore, the proposed method assessed the quality of VGI with reference source (for VGI which is existed in the database) and VGI without reference source (for VGI which is shared for the first time). To demonstrate the feasibility of the proposed approach, a mobile application has been developed to recommend suitable restaurants to the users based on their geospatial locations. The evaluation of the method indicates that VGI can potentially enhance the functionality of the LARS in predicting the users’ interests. Numéro de notice : A2019-510 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1493155 date de publication en ligne : 10/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1493155 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93810 [article]

Pyramid scene parsing network in 3D: Improving semantic segmentation of point clouds with multi-scale contextual information / Hao Fang in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 154 (August 2019) . - pp 246 - 258 Titre : Pyramid scene parsing network in 3D: Improving semantic segmentation of point clouds with multi-scale contextual information Type de document : Article/Communication Auteurs : Hao Fang, Auteur ; Florent Lafarge, Auteur Année de publication : 2019 Article en page(s) : pp 246 - 258 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] compréhension de l'image [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] prise en compte du contexte [Termes descripteurs IGN] représentation multiple [Termes descripteurs IGN] scène [Termes descripteurs IGN] scène intérieure [Termes descripteurs IGN] segmentation sémantique [Termes descripteurs IGN] semis de points Résumé : (Auteur) Analyzing and extracting geometric features from 3D data is a fundamental step in 3D scene understanding. Recent works demonstrated that deep learning architectures can operate directly on raw point clouds, i.e. without the use of intermediate grid-like structures. These architectures are however not designed to encode contextual information in-between objects efficiently. Inspired by a global feature aggregation algorithm designed for images (Zhao et al., 2017), we propose a 3D pyramid module to enrich pointwise features with multi-scale contextual information. Our module can be easily coupled with 3D semantic segmentation methods operating on 3D point clouds. We evaluated our method on three large scale datasets with four baseline models. Experimental results show that the use of enriched features brings significant improvements to the semantic segmentation of indoor and outdoor scenes. Numéro de notice : A2019-271 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.06.010 date de publication en ligne : 01/07/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.06.010 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93089 [article]

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Detection of individual trees in urban alignment from airborne data and contextual information: A marked point process approach / Josselin Aval in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 146 (December 2018) . - pp 197 - 210 Titre : Detection of individual trees in urban alignment from airborne data and contextual information: A marked point process approach Type de document : Article/Communication Auteurs : Josselin Aval, Auteur ; Jean Demuynck, Auteur ; Emmanuel Zenou, Auteur ; Sophie Fabre, Auteur ; David Sheeren , Auteur ; Mathieu Fauvel, Auteur ; Karine R.M. Adeline, Auteur ; Xavier Briottet , Auteur Année de publication : 2018 Article en page(s) : pp 197 - 210 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] arbre urbain [Termes descripteurs IGN] canopée [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] houppier [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] prise en compte du contexte [Termes descripteurs IGN] processus ponctuel marqué [Termes descripteurs IGN] système d'information géographique [Termes descripteurs IGN] Toulouse [Termes descripteurs IGN] zone urbaine Résumé : (Auteur) With the current expansion of cities, urban trees have an important role for preserving the health of its inhabitants. With their evapotranspiration, they reduce the urban heat island phenomenon, by trapping CO2 emission, improve air quality. In particular, street trees or alignment trees, create shade on the road network, are structuring elements of the cities and decorate the roads. Street trees are also subject to specific conditions as they have little space for growth, are pruned and can be affected by the spread of diseases in single-species plantations. Thus, their detection, identification and monitoring are necessary. In this study, an approach is proposed for mapping these trees that are characteristic of the urban environment. Three areas of the city of Toulouse in the south of France are studied. Airborne hyperspectral data and a Digital Surface Model (DSM) for high vegetation detection are used. Then, contextual information is used to identify the street trees. Indeed, Geographic Information System (GIS) data are considered to detect the vegetation canopies close to the streets. Afterwards, individual street tree crown delineation is carried out by modeling the discriminative contextual features of individual street trees (hypotheses of small angle between the trees and similar heights) based on Marked Point Process (MPP). Compared to a baseline individual tree crown delineation method based on region growing, our method logically provides the best results with F-score values of 91%, 75% and 85% against 70%, 41% and 20% for the three studied areas respectively. Our approach mainly succeeds in identifying the street trees. In addition, the contribution of the angle, the height and the GIS data in the street tree mapping has been studied. The results encourage the use of the angle, the height and the GIS data together. However, with only the angle and the height, the results are similar to those obtained with the inclusion of the GIS data for the first and the second study cases with F-score values of 88%, 79% and 62% against 91%, 75% and 85% for the three study cases respectively. Finally, it is shown that the GIS data only is not sufficient. Numéro de notice : A2018-538 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.09.016 date de publication en ligne : 21/10/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.09.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91552 [article]

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A context-based geoprocessing framework for optimizing meetup location of multiple moving objects along road networks / Shaohua Wang in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 32 n° 7-8 (July - August 2018) . - pp 1368 - 1390 Titre : A context-based geoprocessing framework for optimizing meetup location of multiple moving objects along road networks Type de document : Article/Communication Auteurs : Shaohua Wang, Auteur ; Song Gao, Auteur ; Xin Feng, Auteur ; Alan T. Murray, Auteur ; Yuan Zeng Année de publication : 2018 Article en page(s) : pp 1368 - 1390 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] Arbre-R [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] chemin le plus court (algorithme) [Termes descripteurs IGN] démonstration de faisabilité [Termes descripteurs IGN] méthode heuristique [Termes descripteurs IGN] objet mobile [Termes descripteurs IGN] optimisation (mathématiques) [Termes descripteurs IGN] position [Termes descripteurs IGN] prise en compte du contexte [Termes descripteurs IGN] réseau routier Résumé : (Editeur) Given different types of constraints on human life, people must make decisions that satisfy social activity needs. Minimizing costs (i.e. distance, time, or money) associated with travel plays an important role in perceived and realized social quality of life. Identifying optimal interaction locations on road networks when there are multiple moving objects (MMO) with space–time constraints remains a challenge. In this research, we formalize the problem of finding dynamic ideal interaction locations for MMO as a spatial optimization model and introduce a context-based geoprocessing heuristic framework to address this problem. As a proof of concept, a case study involving identification of a meetup location for multiple people under traffic conditions is used to validate the proposed geoprocessing framework. Five heuristic methods with regard to efficient shortest-path search space have been tested. We find that the R* tree-based algorithm performs the best with high quality solutions and low computation time. This framework is implemented in a geographic information systems environment to facilitate integration with external geographic contextual information, e.g. temporary road barriers, points of interest, and real-time traffic information, when dynamically searching for ideal meetup sites. The proposed method can be applied in trip planning, carpooling services, collaborative interaction, and logistics management. Numéro de notice : A2018-278 Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2018.1431838 En ligne : https://doi.org/10.1080/13658816.2018.1431838 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90360 [article]

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TAGGS : grouping tweets to improve global geoparsing for disaster response / Jens A. de Bruijn in Journal of Geovisualization and Spatial Analysis, vol 2 n° 1 (June 2018)  

Public [article]  inJournal of Geovisualization and Spatial Analysis > vol 2 n° 1 (June 2018) Titre : TAGGS : grouping tweets to improve global geoparsing for disaster response Type de document : Article/Communication Auteurs : Jens A. de Bruijn, Auteur ; Hans de Moel, Auteur ; Brenden Jongman, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Linguistique [Termes descripteurs IGN] catastrophe naturelle [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] Geoparsing [Termes descripteurs IGN] inondation [Termes descripteurs IGN] prise en compte du contexte [Termes descripteurs IGN] risque naturel [Termes descripteurs IGN] Twitter Résumé : (Auteur) Timely and accurate information about ongoing events are crucial for relief organizations seeking to effectively respond to disasters. Recently, social media platforms, especially Twitter, have gained traction as a novel source of information on disaster events. Unfortunately, geographical information is rarely attached to tweets, which hinders the use of Twitter for geographical applications. As a solution, geoparsing algorithms extract and can locate geographical locations referenced in a tweet’s text. This paper describes TAGGS, a new algorithm that enhances location disambiguation by employing both metadata and the contextual spatial information of groups of tweets referencing the same location regarding a specific disaster type. Validation demonstrated that TAGGS approximately attains a recall of 0.82 and precision of 0.91. Without lowering precision, this roughly doubles the number of correctly found administrative subdivisions and cities, towns, and villages as compared to individual geoparsing. We applied TAGGS to 55.1 million flood-related tweets in 12 languages, collected over 3 years. We found 19.2 million tweets mentioning one or more flood locations, which can be towns (11.2 million), administrative subdivisions (5.1 million), or countries (4.6 million). In the future, TAGGS could form the basis for a global event detection system. Numéro de notice : A2018-588 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s41651-017-0010-6 date de publication en ligne : 26/12/2017 En ligne : https://doi.org/10.1007/s41651-017-0010-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92505 [article]

A voxel- and graph-based strategy for segmenting man-made infrastructures using perceptual grouping laws: comparison and evaluation / Yusheng Xu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 6 (juin 2018)  

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Context-aware automated interpretation of elaborate natural language descriptions of location through learning from empirical data / Kristin Stock in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)  

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Inference and analysis across spatial supports in the big data era : Uncertain point observations and geographic contexts / Colin Robertson in Transactions in GIS, vol 22 n° 2 (April 2018)  

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Quelle cohérence nationale des données géographiques des schémas régionaux de cohérence écologiques / Dominique Andrieu in Cartes & Géomatique, n° 235-236 (mars - juin 2018)

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Maps telling stories ? / Franz-Benjamin Mocnik in Cartographic journal (the), vol 55 n° 1 (February 2018)  

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Large-scale point cloud semantic segmentation with superpoint graphs / Loïc Landrieu (2018)    

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A higher order conditional random field model for simultaneous classification of land cover and land use / Lena Albert in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)  

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Designing across map use contexts : a research agenda / Amy L. Griffin in International journal of cartography, vol 3 suppl 1 (May 2017)  

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Experiments to distribute map generalization processes / Justin Berli (2017)  

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Context-dependent detection of non-linearly distributed points for vegetation classification in airborne LiDAR / Denis Horvat in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 2016)  

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