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Generic rule-sets for automated detection of urban tree species from very high-resolution satellite data / Razieh Shojanoori in Geocarto international, vol 33 n° 4 (April 2018)
[article]
Titre : Generic rule-sets for automated detection of urban tree species from very high-resolution satellite data Type de document : Article/Communication Auteurs : Razieh Shojanoori, Auteur ; Helmi Zulhaidi Mohd Shafri, Auteur ; Shattri Bin Mansor, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 357 - 374 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse d'image orientée objet
[Termes IGN] arbre (flore)
[Termes IGN] arbre urbain
[Termes IGN] base de règles
[Termes IGN] détection d'arbres
[Termes IGN] image Worldview
[Termes IGN] Malaisie
[Termes IGN] traitement d'image
[Termes IGN] zone urbaineRésumé : (Auteur) The sustainable management and monitoring of urban forests is an important activity in the urbanized world, and operational approaches require information about the status of urban trees to determine the best strategy. One limitation in urban forest studies is the detection and discrimination of tree species using limited training data. Thus, this study focuses on developing generic rule sets from high-resolution WorldView-2 imagery in conjunction with spectral, spatial, colour and textural information for automated urban tree species detection. The object-based image analysis and its combination with statistical analysis of object features is utilized for this purpose. Results of attribute selection indicated that from 55 attributes, only 26 were useful to discriminate urban tree species, namely Messua ferrea L., Samanea saman and Casuarina sumatrana. Finally, the high overall accuracy, approximately 86.87% with kappa of 0.75 confirmed the transferability of the generic model. Numéro de notice : A2018-046 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1265593 En ligne : https://doi.org/10.1080/10106049.2016.1265593 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89268
in Geocarto international > vol 33 n° 4 (April 2018) . - pp 357 - 374[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2018021 RAB Revue Centre de documentation En réserve L003 Disponible A spatio-temporal index for aerial full waveform laser scanning data / Debra F. Laefer in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)
[article]
Titre : A spatio-temporal index for aerial full waveform laser scanning data Type de document : Article/Communication Auteurs : Debra F. Laefer, Auteur ; Anh-Vu Vo, Auteur ; Michela Bertolotto, Auteur Année de publication : 2018 Article en page(s) : pp 232 - 251 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre-R
[Termes IGN] base de données localisées
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forme d'onde pleine
[Termes IGN] index spatiotemporel
[Termes IGN] indexation spatiale
[Termes IGN] octreeRésumé : (Auteur) Aerial laser scanning is increasingly available in the full waveform version of the raw signal, which can provide greater insight into and control over the data and, thus, richer information about the scanned scenes. However, when compared to conventional discrete point storage, preserving raw waveforms leads to vastly larger and more complex data volumes. To begin addressing these challenges, this paper introduces a novel bi-level approach for storing and indexing full waveform (FWF) laser scanning data in a relational database environment, while considering both the spatial and the temporal dimensions of that data. In the storage scheme's upper level, the full waveform datasets are partitioned into spatial and temporal coherent groups that are indexed by a two-dimensional R∗-tree. To further accelerate intra-block data retrieval, at the lower level a three-dimensional local octree is created for each pulse block. The local octrees are implemented in-memory and can be efficiently written to a database for reuse. The indexing solution enables scalable and efficient three-dimensional (3D) spatial and spatio-temporal queries on the actual pulse data - functionalities not available in other systems. The proposed FWF laser scanning data solution is capable of managing multiple FWF datasets derived from large flight missions. The flight structure is embedded into the data storage model and can be used for querying predicates. Such functionality is important to FWF data exploration since aircraft locations and orientations are frequently required for FWF data analyses. Empirical tests on real datasets of up to 1 billion pulses from Dublin, Ireland prove the almost perfect scalability of the system. The use of the local 3D octree in the indexing structure accelerated pulse clipping by 1.2–3.5 times for non-axis-aligned (NAA) polyhedron shaped clipping windows, while axis-aligned (AA) polyhedron clipping was better served using only the top indexing layer. The distinct behaviours of the hybrid indexing for AA and NAA clipping windows are attributable to the different proportion of the local-index-related overheads with respect to the total querying costs. When temporal constraints were added, generally the number of costly spatial checks were reduced, thereby shortening the querying times. Numéro de notice : A2018-125 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89587
in ISPRS Journal of photogrammetry and remote sensing > vol 138 (April 2018) . - pp 232 - 251[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018041 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018043 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018042 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Video event recognition and anomaly detection by combining gaussian process and hierarchical dirichlet process models / Michael Ying Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 4 (April 2018)
[article]
Titre : Video event recognition and anomaly detection by combining gaussian process and hierarchical dirichlet process models Type de document : Article/Communication Auteurs : Michael Ying Yang, Auteur ; Wentong Liao, Auteur ; Yanpeng Cao, Auteur ; Bodo Rosenhahn, Auteur Année de publication : 2018 Article en page(s) : pp 203 - 214 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] agent (intelligence artificielle)
[Termes IGN] apprentissage non-dirigé
[Termes IGN] approche hiérarchique
[Termes IGN] image vidéo
[Termes IGN] modèle de Markov
[Termes IGN] modèle orienté agent
[Termes IGN] séquence d'imagesRésumé : (Auteur) In this paper, we present an unsupervised learning framework for analyzing activities and interactions in surveillance videos. In our framework, three levels of video events are connected by Hierarchical Dirichlet Process (HDP) model: low-level visual features, simple atomic activities, and multi-agent interactions. Atomic activities are represented as distribution of low-level features, while complicated interactions are represented as distribution of atomic activities. This learning process is unsupervised. Given a training video sequence, low-level visual features are extracted based on optic flow and then clustered into different atomic activities and video clips are clustered into different interactions. The HDP model automatically decides the number of clusters, i.e., the categories of atomic activities and interactions. Based on the learned atomic activities and interactions, a training dataset is generated to train the Gaussian Process (GP) classifier. Then, the trained GP models work in newly captured video to classify interactions and detect abnormal events in real time. Furthermore, the temporal dependencies between video events learned by HDP-Hidden Markov Models (HMM) are effectively integrated into GP classifier to enhance the accuracy of the classification in newly captured videos. Our framework couples the benefits of the generative model (HDP) with the discriminant model (GP). We provide detailed experiments showing that our framework enjoys favorable performance in video event classification in real-time in a crowded traffic scene. Numéro de notice : A2018-139 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.4.203 Date de publication en ligne : 01/04/2018 En ligne : https://doi.org/10.14358/PERS.84.4.203 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89689
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 4 (April 2018) . - pp 203 - 214[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2018041 RAB Revue Centre de documentation En réserve L003 Disponible An approach to measuring semantic relatedness of geographic terminologies using a thesaurus and lexical database sources / Zugang Chen in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)
[article]
Titre : An approach to measuring semantic relatedness of geographic terminologies using a thesaurus and lexical database sources Type de document : Article/Communication Auteurs : Zugang Chen, Auteur ; Jia Song, Auteur ; Yaping Yang, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] recherche d'information géographique
[Termes IGN] relation sémantique
[Termes IGN] représentation des connaissances
[Termes IGN] terminologie
[Termes IGN] thesaurusRésumé : (Auteur) In geographic information science, semantic relatedness is important for Geographic Information Retrieval (GIR), Linked Geospatial Data, geoparsing, and geo-semantics. But computing the semantic similarity/relatedness of geographic terminology is still an urgent issue to tackle. The thesaurus is a ubiquitous and sophisticated knowledge representation tool existing in various domains. In this article, we combined the generic lexical database (WordNet or HowNet) with the Thesaurus for Geographic Science and proposed a thesaurus–lexical relatedness measure (TLRM) to compute the semantic relatedness of geographic terminology. This measure quantified the relationship between terminologies, interlinked the discrete term trees by using the generic lexical database, and realized the semantic relatedness computation of any two terminologies in the thesaurus. The TLRM was evaluated on a new relatedness baseline, namely, the Geo-Terminology Relatedness Dataset (GTRD) which was built by us, and the TLRM obtained a relatively high cognitive plausibility. Finally, we applied the TLRM on a geospatial data sharing portal to support data retrieval. The application results of the 30 most frequently used queries of the portal demonstrated that using TLRM could improve the recall of geospatial data retrieval in most situations and rank the retrieval results by the matching scores between the query of users and the geospatial dataset. Numéro de notice : A2018-100 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : doi:10.3390/ijgi7030098 En ligne : https://doi.org/10.3390/ijgi7030098 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89515
in ISPRS International journal of geo-information > vol 7 n° 3 (March 2018)[article]A comparative approach to modelling multiple urban land use changes using tree-based methods and cellular automata: the case of Greater Tokyo Area / Guodong Du in International journal of geographical information science IJGIS, vol 32 n° 3-4 (March - April 2018)
[article]
Titre : A comparative approach to modelling multiple urban land use changes using tree-based methods and cellular automata: the case of Greater Tokyo Area Type de document : Article/Communication Auteurs : Guodong Du, Auteur ; Kong Joo Shin, Auteur ; Liang Yuan, Auteur ; Shunsuke Managi, Auteur Année de publication : 2018 Article en page(s) : pp 757 - 782 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse comparative
[Termes IGN] automate cellulaire
[Termes IGN] changement d'utilisation du sol
[Termes IGN] Tokyo (Japon)
[Termes IGN] utilisation du sol
[Termes IGN] zone urbaineRésumé : (Auteur) Urban multiple land use change (LUC) modelling enables the realistic simulation of LUC processes in complex urban systems; however, such modelling suffers from technical challenges posed by complicated transition rules and high spatial heterogeneity when predicting the LUC of a highly developed area. Tree-based methods are powerful tools for addressing this task, but their predictive capabilities need further examination. This study integrates tree-based methods and cellular automata to simulate multiple LUC processes in the Greater Tokyo Area. We examine the predictive capability of 4 tree-based models – bagged trees, random forests, extremely randomised trees (ERT) and bagged gradient boosting decision trees (bagged GBDT) – on transition probability prediction for 18 land use transitions derived from 8 land use types. We compare the predictive power of a tree-based model with multi-layer perceptron (MLP) and among themselves. The results show that tree-based models generally perform better than MLP, and ERT significantly outperforms the three other tree-based models. The outstanding predictive performance of ERT demonstrates the advantages of introducing bagging ensemble and a high degree of randomisation into transition probability modelling. In addition, through variable importance evaluation, we found the strongest explanatory powers of neighbourhood characteristics for all land use transitions; however, the size of the impacts depends on the neighbourhood land use type and the neighbourhood size. Furthermore, socio-economic and policy factors play important roles in transitions ending with high-rise buildings and transitions related to industrial areas. Numéro de notice : A2018-044 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1410550 En ligne : https://doi.org/10.1080/13658816.2017.1410550 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89266
in International journal of geographical information science IJGIS > vol 32 n° 3-4 (March - April 2018) . - pp 757 - 782[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018022 RAB Revue Centre de documentation En réserve L003 Disponible 079-2018021 RAB Revue Centre de documentation En réserve L003 Disponible European Forest Types: toward an automated classification / Francesca Giannetti in Annals of Forest Science, vol 75 n° 1 (March 2018)PermalinkGenerating vague neighbourhoods through data mining of passive web data / Paul Brindley in International journal of geographical information science IJGIS, vol 32 n° 3-4 (March - April 2018)PermalinkGenerative street addresses from satellite imagery / İlke Demir in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkOpen data, big data : quel renouveau du raisonnement cartographique ? / Emilie Lerond in Cartes & Géomatique, n° 235-236 (mars - juin 2018)PermalinkSimilarity measurement of metadata of geospatial data : an artificial neural network approach / Zugang Chen in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkAnalyse de l'incertitude et de la précision thématique de classifications GEOBIA d'une image WorldView-2 / François Messner in Revue Française de Photogrammétrie et de Télédétection, n° 216 (février 2018)PermalinkExtraction of pluvial flood relevant volunteered geographic information (VGI) by deep learning from user generated texts and photos / Yu Feng in ISPRS International journal of geo-information, vol 7 n° 2 (February 2018)PermalinkFine-grained object recognition and zero-shot learning in remote sensing imagery / Gencer Sumbul in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)PermalinkLarge-scale remote sensing image retrieval by deep hashing neural networks / Yansheng Li in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)PermalinkLRAGE : learning latent relationships with adaptive graph embedding for aerial scene classification / Yuebin Wang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)Permalink