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Detecting spatiotemporal traffic events using geosocial media data / Shishuo Xu in Computers, Environment and Urban Systems, vol 94 (June 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 94 (June 2022) . - n° 101797 Titre : Detecting spatiotemporal traffic events using geosocial media data Type de document : Article/Communication Auteurs : Shishuo Xu, Auteur ; Songnian Li, Auteur ; Wei Huang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101797 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse de groupement [Termes IGN] base de données d'objets mobiles [Termes IGN] base de données spatiotemporelles [Termes IGN] détection d'événement [Termes IGN] données issues des réseaux sociaux [Termes IGN] données spatiotemporelles [Termes IGN] planification urbaine [Termes IGN] sécurité routière [Termes IGN] Toronto [Termes IGN] trafic routier [Termes IGN] Twitter Résumé : (auteur) Social media platforms enable efficient traffic event detection by allowing users to produce geo-tagged content (e.g., tweets) known as geosocial media data. Geosocial media data improve road safety by providing timely updates for traffic flow and traffic control. Recent studies on traffic event detection with geosocial media data have been focused around keyword-based query approaches, where the event content was inferred by predetermined categories, to retrieve relevant traffic events. Spatiotemporal features associated with traffic-related posts have not been fully investigated. In this study, we filtered irrelevant posts with association rules. A spatiotemporal clustering-based method was then used to retrieve traffic events from these filtered posts, where the content of detected events was automatically inferred with a set of representative terms. For comparison, a typical text classification-based method was also used by classifying the posts filtered from association rules into different categories. By validating the detection results with vehicle travel speed data, we demonstrate that the former outperforms the latter in terms of the number of correctly detected traffic events from one-year of Twitter data in Toronto, Canada. Our proposed approach helps organizations and governments to be aware of when and where traffic events occur by identifying event hotspots and peak periods, which improves both traffic management and urban planning. Numéro de notice : A2022-264 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101797 Date de publication en ligne : 26/03/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101797 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100261 [article]

Combining spatiotemporal fusion and object-based image analysis for improving wetland mapping in complex and heterogeneous urban landscapes / Meng Zhang in Geocarto international, vol 34 n° 10 ([15/07/2019])  

Public [article]  inGeocarto international > vol 34 n° 10 [15/07/2019] . - pp 1144 - 1161 Titre : Combining spatiotemporal fusion and object-based image analysis for improving wetland mapping in complex and heterogeneous urban landscapes Type de document : Article/Communication Auteurs : Meng Zhang, Auteur ; Yongnian Zeng, Auteur ; Wei Huang, Auteur ; Songnian Li, Auteur Année de publication : 2019 Article en page(s) : pp 1144 - 1161 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] Chine [Termes IGN] données spatiotemporelles [Termes IGN] fusion d'images [Termes IGN] hétérogénéité [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-OLI [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] paysage urbain [Termes IGN] zone humide Résumé : (auteur) Remote sensing has been proven promising in wetland mapping. However, conventional methods in a complex and heterogeneous urban landscape usually use mono temporal Landsat TM/ETM + images, which have great uncertainty due to the spectral similarity of different land covers, and pixel-based classifications may not meet the accuracy requirement. This paper proposes an approach that combines spatiotemporal fusion and object-based image analysis, using the spatial and temporal adaptive reflectance fusion model to generate a time series of Landsat 8 OLI images on critical dates of sedge swamp and paddy rice, and the time series of MODIS NDVI to calculate phenological parameters for identifying wetlands with an object-based method. The results of a case study indicate that different types of wetlands can be successfully identified, with 92.38%. The overall accuracy and 0.85 Kappa coefficient, and 85% and 90% for the user’s accuracies of sedge swamp and paddy respectively. Numéro de notice : A2019-302 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1474275 Date de publication en ligne : 17/05/2018 En ligne : https://doi.org/10.1080/10106049.2018.1474275 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93222 [article]

Geospatial big data handling theory and methods: A review and research challenges / Songnian Li in ISPRS Journal of photogrammetry and remote sensing, vol 115 (May 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 115 (May 2016) . - pp 119 – 133 Titre : Geospatial big data handling theory and methods: A review and research challenges Type de document : Article/Communication Auteurs : Songnian Li, Auteur ; Suzana Dragićević, Auteur ; Francesc Antón Castro, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 119 – 133 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] données massives [Termes IGN] traitement automatique de données [Termes IGN] traitement de données localisées Résumé : (auteur) Big data has now become a strong focus of global interest that is increasingly attracting the attention of academia, industry, government and other organizations. Big data can be situated in the disciplinary area of traditional geospatial data handling theory and methods. The increasing volume and varying format of collected geospatial big data presents challenges in storing, managing, processing, analyzing, visualizing and verifying the quality of data. This has implications for the quality of decisions made with big data. Consequently, this position paper of the International Society for Photogrammetry and Remote Sensing (ISPRS) Technical Commission II (TC II) revisits the existing geospatial data handling methods and theories to determine if they are still capable of handling emerging geospatial big data. Further, the paper synthesises problems, major issues and challenges with current developments as well as recommending what needs to be developed further in the near future. Numéro de notice : A2016-547 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.10.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.10.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81699 [article]

Information from imagery: ISPRS scientific vision and research agenda / Jun Chen in ISPRS Journal of photogrammetry and remote sensing, vol 115 (May 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 115 (May 2016) . - pp 3 – 21 Titre : Information from imagery: ISPRS scientific vision and research agenda Type de document : Article/Communication Auteurs : Jun Chen, Auteur ; Ian J. Dowman, Auteur ; Songnian Li, Auteur ; Zhilin li, Auteur ; Marguerite Madden, Auteur ; Jon Mills, Auteur ; Nicolas Paparoditis , Auteur ; Franz Rottensteiner, Auteur ; Monika Sester, Auteur ; Charles K. Toth, Auteur ; John C. Trinder, Auteur ; Christian Heipke, Auteur Année de publication : 2016 Article en page(s) : pp 3 – 21 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] image à haute résolution [Termes IGN] information géographique [Termes IGN] informatique ubiquitaire [Termes IGN] recherche et développement [Termes IGN] technologies de l'information et de la communication [Termes IGN] télédétection spatiale Mots-clés libres : Research agenda  Photogrammetry  Remote sensing  Spatial information science Résumé : (auteur) With the increased availability of very high-resolution satellite imagery, terrain based imaging and participatory sensing, inexpensive platforms, and advanced information and communication technologies, the application of imagery is now ubiquitous, playing an important role in many aspects of life and work today. As a leading organisation in this field, the International Society for Photogrammetry and Remote Sensing (ISPRS) has been devoted to effectively and efficiently obtaining and utilising information from imagery since its foundation in the year 1910. This paper examines the significant challenges currently facing ISPRS and its communities, such as providing high-quality information, enabling advanced geospatial computing, and supporting collaborative problem solving. The state-of-the-art in ISPRS related research and development is reviewed and the trends and topics for future work are identified. By providing an overarching scientific vision and research agenda, we hope to call on and mobilise all ISPRS scientists, practitioners and other stakeholders to continue improving our understanding and capacity on information from imagery and to deliver advanced geospatial knowledge that enables humankind to better deal with the challenges ahead, posed for example by global change, ubiquitous sensing, and a demand for real-time information generation. Numéro de notice : A2016-541 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.09.008 Date de publication en ligne : 09/10/2015 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.09.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81686 [article]

vol 69 n° 3 - september 2015 - Advances in Geospatial Statistical Modelling Analysis and Data Mining (Bulletin de Geomatica) / Emmanuel Stefanakis  

Public [n° ou bulletin]  est un bulletin de Geomatica / Canadian institute of geomatics = Association canadienne des sciences géomatiques (Canada) (1993 -)   Titre : vol 69 n° 3 - september 2015 - Advances in Geospatial Statistical Modelling Analysis and Data Mining Titre original : Les avancées dans les domaines de la modélisation, de l’analyse et du forage des données statistiques géospatiales Type de document : Périodique Auteurs : Emmanuel Stefanakis, Éditeur scientifique ; Songnian Li, Éditeur scientifique ; Suzana Dragićević, Éditeur scientifique Année de publication : 2015 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique Numéro de notice : 035-201503 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Numéro de périodique En ligne : http://pubs.cig-acsg.ca/toc/cig/69/3 Format de la ressource électronique : URL sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=26001 [n° ou bulletin]

Contient

• 3D model construction in an urban environment from sparse LiDAR points and aerial photos : a statistical approach / Xuebin Wei in Geomatica, vol 69 n° 3 (september 2015)  
• An intelligent spatial proximity system using neurofuzzy classifiers and contextual information / F. Barouni in Geomatica, vol 69 n° 3 (september 2015)  
• Prediction of traffic counts using statistical and neural network models / Abul Kalam Azad in Geomatica, vol 69 n° 3 (september 2015)  
• Exploring the decision tree method for modelling urban land use change / Mileva Samardžić-Petrović in Geomatica, vol 69 n° 3 (september 2015)  
• Contextual Douglas-Peucker Simplification / Titus Tienaah in Geomatica, vol 69 n° 3 (september 2015)  

An analysis of urban expansion and its associated thermal characteristics using Landsat imagery / Wei Huang in Geocarto international, vol 30 n° 1 - 2 (January - February 2015)  

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An across-country comparison of the hierarchical spatial structures of cities / Xintao Liu in Geomatica, vol 68 n° 3 (September 2014)  

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vol 83 - September 2013 - Special section : Towards intelligent geoprocessing on the web (Bulletin de ISPRS Journal of photogrammetry and remote sensing) / International society for photogrammetry and remote sensing (1980 -)  

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Temporal logic and operation relations based knowledge representation for land cover change web services / Jun Chen in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)  

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Geo-social model: A conceptual framework for real-time geocollaboration / Zheng Chang in Transactions in GIS, vol 17 n° 2 (April 2013)  

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