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Low-cost warning system for the monitoring of the Corinth Canal / George Hloupis in Applied geomatics, vol 9 n° 4 (December 2017)  

Public [article]  inApplied geomatics > vol 9 n° 4 (December 2017) . - pp 263 - 277 Titre : Low-cost warning system for the monitoring of the Corinth Canal Type de document : Article/Communication Auteurs : George Hloupis, Auteur ; Vassilis Pagounis, Auteur ; Maria Tsakiri-Strati, Auteur ; George Doxastakis, Auteur ; Vangelis Zacharis, Auteur Année de publication : 2017 Article en page(s) : pp 263 - 277 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie [Termes IGN] accéléromètre [Termes IGN] canal [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Grèce [Termes IGN] gyroscope [Termes IGN] microsystème électromécanique [Termes IGN] réseau de capteurs [Termes IGN] télémétrie laser terrestre Résumé : (auteur) This paper presents an in-house developed low-cost triggering design using wireless sensor network (WSN) nodes. A set of corresponding microelectromechanical system (MEMS) sensors (accelerometer and gyroscope) are used along with a radio transmission unit and a microprocessor. In conjunction with the WSN, terrestrial laser scanning (TLS) measurements are used. Specifically, the aim of this work is to introduce a low-cost WSN node with verified repeatability that will raise an initial signal for possible slope change which will be further verified by TLS measurements. The paper demonstrates the deployment of the developed design for a 3-month period in the Corinth Canal in Greece and presents indicative results. Numéro de notice : A2017-728 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s12518-017-0196-9 Date de publication en ligne : 17/11/2017 En ligne : https://doi.org/10.1007/s12518-017-0196-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88401 [article]

VGI in surveying engineering : Introducing collaborative cloud land surveying / Ioannis Sofos in Journal of Spatial Information Science, JoSIS, n° 15 (September 2017)  

Public [article]  inJournal of Spatial Information Science, JoSIS > n° 15 (September 2017) . - pp 35 - 64 Titre : VGI in surveying engineering : Introducing collaborative cloud land surveying Type de document : Article/Communication Auteurs : Ioannis Sofos, Auteur ; Vassilios Vescoukis, Auteur ; Maria Tsakiri-Strati, Auteur Année de publication : 2017 Article en page(s) : pp 35 - 64 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] Athènes [Termes IGN] données localisées des bénévoles [Termes IGN] entrepôt de données localisées [Termes IGN] géomètre [Termes IGN] informatique en nuage [Termes IGN] partage de données localisées [Termes IGN] topographe Résumé : (Auteur) Volunteered geographic information (VGI) has enabled many innovative applications in various scientific fields. This paper introduces a new framework called “collaborative cloud-based land surveying” (CCLS) that uses VGI principles for data sharing among surveyor engineers to boost the productivity and improve the quality of their applications. A cloud-based spatio-temporal data repository is presented, aiming to facilitate the sharing of VGI among surveyor engineers. A fully-functional distributed software application has been developed and used to apply CCLS in a large-scale land surveying project run by the Greek Ministry of Culture, which involves the mapping of the historic center of Athens. Results from the data analysis of hundreds of measurements indicate a substantial (30% to 60%) error reduction and also a significant productivity raise (22%). The collected measurements are shared in an online database, accessible by professional surveyors who can in turn contribute their own data to further enhance the CCLS system. Numéro de notice : A2017-821 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5311/JOSIS.2017.15.320 En ligne : https://doi.org/10.5311/JOSIS.2017.15.320 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89306 [article]

Object-based building change detection from a single multispectral image and pre-existing geospatial information / Georgia Doxani in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 6 (June 2015) . - pp 481 - 489 Titre : Object-based building change detection from a single multispectral image and pre-existing geospatial information Type de document : Article/Communication Auteurs : Georgia Doxani, Auteur ; Konstantinos Karantzalos, Auteur ; Maria Tsakiri-Strati, Auteur Année de publication : 2015 Article en page(s) : pp 481 - 489 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] analyse de l'existant [Termes IGN] analyse diachronique [Termes IGN] base de données localisées [Termes IGN] bâtiment [Termes IGN] classification à base de connaissances [Termes IGN] détection de changement [Termes IGN] Grèce [Termes IGN] image isolée [Termes IGN] image multibande [Termes IGN] milieu urbain Résumé : (auteur) Multispectral images of very high spatial resolution and vector data from geospatial databases, such as cadastral maps, are among the cost-effective and broadly available geodata in urban environments. Therefore, we aim to address building change detection based on pre-existing building footprint information and a single very high resolution multispectral image. An object-based classification methodology was developed that employs advanced scalespace filtering, unsupervised clustering, and knowledge-based classification. The developed framework effectively integrates prior vector data and multispectral observations, through incorporating the prior knowledge into the training process and defining the proper object-based classification rules. The methodology successfully identified important building changes, which were validated by employing the vector information of a building geodatabase and a QuickBird image acquired in 2003 and 2007, respectively, over urban regions in the city of Thessaloniki, Greece. The performed quantitative and qualitative evaluation indicated that the proposed analysis framework can detect the new buildings with high accuracy rates and, to a lesser degree, their exact shape and size. Numéro de notice : A2015-978 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.81.6.481 En ligne : https://doi.org/10.14358/PERS.81.6.481 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80061 [article]