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SNN_flow: a shared nearest-neighbor-based clustering method for inhomogeneous origin-destination flows / Qiliang Liu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)
[article]
Titre : SNN_flow: a shared nearest-neighbor-based clustering method for inhomogeneous origin-destination flows Type de document : Article/Communication Auteurs : Qiliang Liu, Auteur ; Jie Yang, Auteur ; Min Deng, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 253 - 279 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] classification barycentrique
[Termes IGN] flux
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] mobilité urbaine
[Termes IGN] noeud
[Termes IGN] origine - destination
[Termes IGN] Pékin (Chine)
[Termes IGN] réseau routier
[Termes IGN] taxi
[Termes IGN] trajet (mobilité)Résumé : (auteur) Identifying clusters from individual origin–destination (OD) flows is vital for investigating spatial interactions and flow mapping. However, detecting arbitrarily-shaped and non-uniform flow clusters from network-constrained OD flows continues to be a challenge. This study proposes a shared nearest-neighbor-based clustering method (SNN_flow) for inhomogeneous OD flows constrained by a road network. To reveal clusters of varying shapes and densities, a normalized density for each OD flow is defined based on the concept of shared nearest-neighbor, and flow clusters are constructed using the density-connectivity mechanism. To handle large amounts of disaggregated OD flows, an efficient method for searching the network-constrained k-nearest flows is developed based on a local road node distance matrix. The parameters of SNN_flow are statistically determined: the density threshold is modeled as a significance level of a significance test, and the number of nearest neighbors is estimated based on the variance of the kth nearest distance. SNN_flow is compared with three state-of-the-art methods using taxicab trip data in Beijing. The results show that SNN_flow outperforms existing methods in identifying flow clusters with irregular shapes and inhomogeneous distributions. The clusters identified by SNN_flow can reveal human mobility patterns in Beijing. Numéro de notice : A2022-163 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1899184 Date de publication en ligne : 16/03/2021 En ligne : https://doi.org/10.1080/13658816.2021.1899184 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99786
in International journal of geographical information science IJGIS > vol 36 n° 2 (February 2022) . - pp 253 - 279[article]Synergistic use of particle swarm optimization, artificial neural network, and extreme gradient boosting algorithms for urban LULC mapping from WorldView-3 images / Alireza Hamedianfar in Geocarto international, vol 37 n° 3 ([01/02/2022])
[article]
Titre : Synergistic use of particle swarm optimization, artificial neural network, and extreme gradient boosting algorithms for urban LULC mapping from WorldView-3 images Type de document : Article/Communication Auteurs : Alireza Hamedianfar, Auteur ; Mohamed Barakat A. Gibril, Auteur ; Mohammadjavad Hosseinpoor, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 773 - 791 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] carte d'occupation du sol
[Termes IGN] Extreme Gradient Machine
[Termes IGN] image à très haute résolution
[Termes IGN] image Worldview
[Termes IGN] itération
[Termes IGN] optimisation (mathématiques)
[Termes IGN] optimisation par essaim de particules
[Termes IGN] réseau neuronal artificiel
[Termes IGN] segmentation d'image
[Termes IGN] zone urbaineRésumé : (auteur) Geographic object-based image analysis (GEOBIA) has emerged as an effective and evolving paradigm for analyzing very high resolution (VHR) images as it demonstrates preeminence over the traditional pixel-wise methods and enables the utilization of diverse spectral, geometrical, and textural information to for image classification. Among feature selection (FS) methods, metaheuristic FS techniques have recently demonstrated effective performance in the dimensionality reduction of GEOBIA features. In this study, an artificial neural network (ANN) was integrated with particle swarm optimization (PSO) to enhance the learning process and more effectively determine the most significant features and their importance using WorldView-3 (WV-3) satellite data. First, multi-resolution image segmentation parameters were tuned using Taguchi optimization technique and unsupervised segmentation quality measure. Second, the proposed ANN–PSO was compared with PSO under 100 iterations. The ANN–PSO integration achieved lower root mean square error (RMSE) in all the iterations. Third, state-of-the-art extreme gradient boosting (Xgboost) image classifier was used to derive the land use/land cover (LULC) map of the first study area and assess the transferability of the selected features on the second and third regions. The Xgboost classifier obtained 91.68%, 89.54%, and 89.33% overall accuracies for the first, second, and third sites, respectively. ANN contributed to an intelligent approach for identifying which features are more likely to be relevant and discriminate the land cover types. The proposed integrated FS is a promising approach and an efficient tool for determining significant features and enhancing the detection of urban LULC classes from WV-3 data. Numéro de notice : A2022-344 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1737974 Date de publication en ligne : 12/03/2020 En ligne : https://doi.org/10.1080/10106049.2020.1737974 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100525
in Geocarto international > vol 37 n° 3 [01/02/2022] . - pp 773 - 791[article]3D modeling of urban area based on oblique UAS images - An end-to-end pipeline / Valeria-Ersilia Oniga in Remote sensing, vol 14 n° 2 (January-2 2022)
[article]
Titre : 3D modeling of urban area based on oblique UAS images - An end-to-end pipeline Type de document : Article/Communication Auteurs : Valeria-Ersilia Oniga, Auteur ; Ana-Ioana Breaban, Auteur ; Norbert Pfeifer, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 422 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage automatique
[Termes IGN] Bâti-3D
[Termes IGN] CityGML
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] image aérienne oblique
[Termes IGN] image captée par drone
[Termes IGN] indice de végétation
[Termes IGN] lasergrammétrie
[Termes IGN] modèle numérique de surface
[Termes IGN] modélisation 3D
[Termes IGN] point d'appui
[Termes IGN] Roumanie
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] zone urbaineRésumé : (auteur) 3D modelling of urban areas is an attractive and active research topic, as 3D digital models of cities are becoming increasingly common for urban management as a consequence of the constantly growing number of people living in cities. Viewed as a digital representation of the Earth’s surface, an urban area modeled in 3D includes objects such as buildings, trees, vegetation and other anthropogenic structures, highlighting the buildings as the most prominent category. A city’s 3D model can be created based on different data sources, especially LiDAR or photogrammetric point clouds. This paper’s aim is to provide an end-to-end pipeline for 3D building modeling based on oblique UAS images only, the result being a parametrized 3D model with the Open Geospatial Consortium (OGC) CityGML standard, Level of Detail 2 (LOD2). For this purpose, a flight over an urban area of about 20.6 ha has been taken with a low-cost UAS, i.e., a DJI Phantom 4 Pro Professional (P4P), at 100 m height. The resulting UAS point cloud with the best scenario, i.e., 45 Ground Control Points (GCP), has been processed as follows: filtering to extract the ground points using two algorithms, CSF and terrain-mark; classification, using two methods, based on attributes only and a random forest machine learning algorithm; segmentation using local homogeneity implemented into Opals software; plane creation based on a region-growing algorithm; and plane editing and 3D model reconstruction based on piece-wise intersection of planar faces. The classification performed with ~35% training data and 31 attributes showed that the Visible-band difference vegetation index (VDVI) is a key attribute and 77% of the data was classified using only five attributes. The global accuracy for each modeled building through the workflow proposed in this study was around 0.15 m, so it can be concluded that the proposed pipeline is reliable. Numéro de notice : A2022-101 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.3390/rs14020422 Date de publication en ligne : 17/01/2022 En ligne : https://doi.org/10.3390/rs14020422 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99566
in Remote sensing > vol 14 n° 2 (January-2 2022) . - n° 422[article]Increasing territorial planning activities through viewshed analysis / Gheorghe-Gavrilă Hognogi in Geocarto international, vol 37 n° 2 ([15/01/2022])
[article]
Titre : Increasing territorial planning activities through viewshed analysis Type de document : Article/Communication Auteurs : Gheorghe-Gavrilă Hognogi, Auteur ; Ana-Maria Pop, Auteur ; Simona Mălăescu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 627 - 637 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] aménagement du territoire
[Termes IGN] analyse géovisuelle
[Termes IGN] Carpates
[Termes IGN] carte topographique
[Termes IGN] logique floue
[Termes IGN] point de visibilité
[Termes IGN] Roumanie
[Termes IGN] vision
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Visibility analyses are employed in various fields, from landscape to archeology or territorial planning. Two case studies, of different elevation, from Romania were selected to be considered for setting up some observation points as lookout points. Fuzzy viewshed analysis was performed to evaluate the degree of visibility of certain landscape components and was also used as a tool for territorial planning. The main results of the research were some particular viewshed analysis area according to the dominant visibility directions. This methodology may be useful to local authorities, which are the only responsible bodies for authorizing, creating and setting up lookout points in a given space or for organizing certain planning activities. Numéro de notice : A2022-051 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1730450 Date de publication en ligne : 27/02/2020 En ligne : https://doi.org/10.1080/10106049.2020.1730450 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99444
in Geocarto international > vol 37 n° 2 [15/01/2022] . - pp 627 - 637[article]3D geovisualization for visual analysis of urban climate / Sidonie Christophe in Cybergeo, European journal of geography, vol 2022 ([01/01/2022])
[article]
Titre : 3D geovisualization for visual analysis of urban climate Titre original : Géovisualisation en 3D pour l'analyse visuelle du climat urbain Type de document : Article/Communication Auteurs : Sidonie Christophe , Auteur ; Jacques Gautier , Auteur ; Paul Chapron , Auteur ; Luke Riley, Auteur ; Valéry Masson, Auteur Année de publication : 2022 Projets : URCLIM / Masson, Valéry Article en page(s) : n° 1008 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse visuelle
[Termes IGN] climat urbain
[Termes IGN] données météorologiques
[Termes IGN] données topographiques
[Termes IGN] ilot thermique urbain
[Termes IGN] morphologie urbaine
[Termes IGN] visualisation 3D
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) This paper is about the relevance of proposing geovisualization methods to visually integrate, co-visualize and interact with urban and meteorological data into a 3D environment, in order to support the visual analysis of the urban climate. Meteorological experts and researchers already face meteorological data and climate models analysis issues, at larger scales into the city: yet even if they have existing practices and tools to address these issues, they could take benefit from the knowledge and the methods from the Geovisualization domain, to complement these analyses by a visuospatial reasoning approach. In this paper, based on the knowledge of the expectations of the meteorological experts we are working with, we brought climate analysis into the city and visuospatial reasoning closer, on both heterogeneous urban and air temperature data(1). We reviewed the existing works regarding geovisualization of spatio-temporal phenomena and visualization of meteorological data (2). We then presented the different approaches we fulfilled to provide a 3D geovisualization environment and graphic representations, visually integrating both meteorological and spatial data. One provides style and interaction capacities on those data, enabling the interactive 3D exploration of their spatial and value distributions, throughout the city. Another geovisualization-design experiment is presented as a co-visualization of meteorological data and morphological indicators on 2.5D maps (3). These complementary approaches are presented and discussed with the meteorological experts, based on their relevance to tackle climate analysis at a larger scale and on the refinements required to extend their exploration capacities (4). Numéro de notice : A2022-270 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE/IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.4000/cybergeo.38518 Date de publication en ligne : 17/03/2022 En ligne : https://doi.org/10.4000/cybergeo.38518 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100206
in Cybergeo, European journal of geography > vol 2022 [01/01/2022] . - n° 1008[article]An approach for multi-scale urban building data integration and enrichment through geometric matching and semantic web / Abdulkadir Memduhoglu in Cartography and Geographic Information Science, vol 49 n° 1 (January 2022)PermalinkAn extended patch-based cellular automaton to simulate horizontal and vertical urban growth under the shared socioeconomic pathways / Yimin Chen in Computers, Environment and Urban Systems, vol 91 (January 2022)PermalinkPermalinkAnalyse contrastive de la perception de la ville entre fictions climatiques et débats publics / Alexandra Li–Combeau-Longuet (2022)PermalinkAttributing pedestrian networks with semantic information based on multi-source spatial data / Xue Yang in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)PermalinkPermalinkPermalinkA comprehensive assessment of four-satellite QZSS constellation: navigation signals, broadcast ephemeris, availability, SPP, interoperability with GPS, and ISB against GPS / Xuanping Li in Survey review, vol 54 n° 382 (January 2022)PermalinkA constraint-based approach for identifying the urban–rural fringe of polycentric cities using multi-sourced data / Jing Yang in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)PermalinkContribution to object extraction in cartography : A novel deep learning-based solution to recognise, segment and post-process the road transport network as a continuous geospatial element in high-resolution aerial orthoimagery / Calimanut-Ionut Cira (2022)Permalink