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Identification of enclaves and exclaves by computation based on point-set topology / Xiaonan Wang in International journal of geographical information science IJGIS, vol 37 n° 2 (February 2023)
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Titre : Identification of enclaves and exclaves by computation based on point-set topology Type de document : Article/Communication Auteurs : Xiaonan Wang, Auteur Année de publication : 2023 Article en page(s) : pp 307 - 338 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] frontière
[Termes IGN] géopolitique
[Termes IGN] intersection spatiale
[Termes IGN] partition de surface
[Termes IGN] polygone
[Termes IGN] relation topologique
[Termes IGN] territoire
[Termes IGN] topologieRésumé : (auteur) Enclaves and exclaves have special roles in geography and are of particular importance to fields such as (geo)politics and economy. However, enclaves and exclaves have not been defined with sufficient formality for automatic identification yet. To identify enclaves and exclaves more generally by computational means than current definitions existing in the literature, this article proposes expressive and generalized mathematical definitions of enclaves and exclaves based on point-set topology. A novel Boundary Extended 16-Intersection Model is developed in this article to identify enclaves, and 74 possible spatial configurations of enclaves are distinguished according to conditions of intersections for polygons in partitions and enclaves. The classic Dimensionally Extended 9-Intersection Model is employed to identify exclaves, and two possible spatial configurations of exclaves are distinguished according to conditions of intersections for polygons in partitions and exclaves. Applications of the proposed definitions are exemplified by the identification of enclaves and exclaves in prototypes and in the real world. Numéro de notice : A2023-102 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2120995 Date de publication en ligne : 21/09/2022 En ligne : https://doi.org/10.1080/13658816.2022.2120995 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102428
in International journal of geographical information science IJGIS > vol 37 n° 2 (February 2023) . - pp 307 - 338[article]A graph-based approach for representing addresses in geocoding / Chen Zhang in Computers, Environment and Urban Systems, vol 100 (March 2023)
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Titre : A graph-based approach for representing addresses in geocoding Type de document : Article/Communication Auteurs : Chen Zhang, Auteur ; Biao He, Auteur ; Renzhong Guo, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 101937 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] appariement d'adresses
[Termes IGN] base de données d'adresses
[Termes IGN] géocodage par adresse postale
[Termes IGN] graphe
[Termes IGN] stockage de données
[Termes IGN] toponymeRésumé : (auteur) Addresses, one of the most important geographical reference systems in natural languages, are usually used to search spatial objects in daily life. Geocoding concatenates text with georeferenced coordinates and is an essential middleware service in geographic information applications. Despite its importance, geocoding remains challenging with only text as input, hindering text matching in reference databases without the specific text. To optimize the storage and retrieval of addresses in databases, this work proposes a graph-based approach for representing addresses. The approach clarifies the characteristics of relative concepts, designs a graph structure and identifies modelling strategies. Furthermore, a schema is proposed to perform address matching and toponym disambiguation using an address graph. The model is implemented on a graph database, and experimental tasks are employed to demonstrate its effectiveness. The approach provides a new reference for developers when creating address databases. Numéro de notice : A2023-126 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101937 Date de publication en ligne : 04/01/2023 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101937 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102505
in Computers, Environment and Urban Systems > vol 100 (March 2023) . - n° 101937[article]Topology-based individual tree segmentation for automated processing of terrestrial laser scanning point clouds / Xin Xu in International journal of applied Earth observation and geoinformation, vol 116 (February 2023)
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Titre : Topology-based individual tree segmentation for automated processing of terrestrial laser scanning point clouds Type de document : Article/Communication Auteurs : Xin Xu, Auteur ; Federico Iuricich, Auteur ; Kim Calders, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 103145 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse de groupement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction d'arbres
[Termes IGN] houppier
[Termes IGN] segmentation d'image
[Termes IGN] semis de points
[Termes IGN] topologieRésumé : (auteur) Terrestrial laser scanning (TLS) is a ground-based approach to rapidly acquire 3D point clouds via Light Detection and Ranging (LiDAR) technologies. Quantifying tree-scale structure from TLS point clouds requires segmentation, yet there is a lack of automated methods available to the forest ecology community. In this work, we consider the problem of segmenting a forest TLS point cloud into individual tree point clouds. Different approaches have been investigated to identify and segment individual trees in a forest point cloud. Typically these methods require intensive parameter tuning and time-consuming user interactions, which has inhibited the application of TLS to large area research. Our goal is to define a new automated segmentation method that lifts these limitations. Our Topology-based Tree Segmentation (TTS) algorithm uses a new topological technique rooted in discrete Morse theory to segment input point clouds into single trees. TTS algorithm identifies distinctive tree structures (i.e., tree bottoms and tops) without user interactions. Tree tops and bottoms are then used to reconstruct single trees using the notion of relevant topological features. This mathematically well-established notion helps distinguish between noise and relevant tree features. To demonstrate the generality of our approach, we present an evaluation using multiple datasets, including different forest types and point densities. We also compare our TTS approach with open-source tree segmentation methods. The experiments show that we achieve a higher segmentation accuracy when performing point-by-point validation. Without expensive user interactions, TTS algorithm is promising for greater usage of TLS point clouds in the forest ecology community, such as fire risk and behavior modeling, estimating tree-level biodiversity structural traits, and above-ground biomass monitoring. Numéro de notice : A2023-129 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.103145 Date de publication en ligne : 12/12/2022 En ligne : https://doi.org/10.1016/j.jag.2022.103145 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102517
in International journal of applied Earth observation and geoinformation > vol 116 (February 2023) . - n° 103145[article]Estimation of lidar-based gridded DEM uncertainty with varying terrain roughness and point density / Luyen K. Bui in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 7 (January 2023)
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Titre : Estimation of lidar-based gridded DEM uncertainty with varying terrain roughness and point density Type de document : Article/Communication Auteurs : Luyen K. Bui, Auteur ; Craig L. Glennie, Auteur Année de publication : 2023 Article en page(s) : n° 100028 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] Alaska (Etats-Unis)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Hawaii (Etats-Unis)
[Termes IGN] incertitude des données
[Termes IGN] interpolation
[Termes IGN] modèle numérique de surface
[Termes IGN] semis de points
[Termes IGN] Triangulated Irregular NetworkRésumé : (auteur) Light detection and ranging (lidar) scanning systems can be used to provide a point cloud with high quality and point density. Gridded digital elevation models (DEMs) interpolated from laser scanning point clouds are widely used due to their convenience, however, DEM uncertainty is rarely provided. This paper proposes an end-to-end workflow to quantify the uncertainty (i.e., standard deviation) of a gridded lidar-derived DEM. A benefit of the proposed approach is that it does not require independent validation data measured by alternative means. The input point cloud requires per point uncertainty which is derived from lidar system observational uncertainty. The propagated uncertainty caused by interpolation is then derived by the general law of propagation of variances (GLOPOV) with simultaneous consideration of both horizontal and vertical point cloud uncertainties. Finally, the interpolated uncertainty is then scaled by point density and a measure of terrain roughness to arrive at the final gridded DEM uncertainty. The proposed approach is tested with two lidar datasets measured in Waikoloa, Hawaii, and Sitka, Alaska. Triangulated irregular network (TIN) interpolation is chosen as the representative gridding approach. The results indicate estimated terrain roughness/point density scale factors ranging between 1 (in flat areas) and 7.6 (in high roughness areas), with a mean value of 2.3 for the Waikoloa dataset and between 1 and 9.2 with a mean value of 1.2 for the Sitka dataset. As a result, the final gridded DEM uncertainties are estimated between 0.059 m and 0.677 m with a mean value of 0.164 m for the Waikoloa dataset and between 0.059 m and 1.723 m with a mean value of 0.097 m for the Sitka dataset. Numéro de notice : A2023-120 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.ophoto.2022.100028 Date de publication en ligne : 17/12/2023 En ligne : https://doi.org/10.1016/j.ophoto.2022.100028 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102494
in ISPRS Open Journal of Photogrammetry and Remote Sensing > vol 7 (January 2023) . - n° 100028[article]A geometry-aware attention network for semantic segmentation of MLS point clouds / Jie Wan in International journal of geographical information science IJGIS, vol 37 n° 1 (January 2023)
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Titre : A geometry-aware attention network for semantic segmentation of MLS point clouds Type de document : Article/Communication Auteurs : Jie Wan, Auteur ; Yongyang Xu, Auteur ; Qinjun Qiu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 138 - 161 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] attention (apprentissage automatique)
[Termes IGN] corrélation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] figure géométrique
[Termes IGN] fonction de perte
[Termes IGN] graphe
[Termes IGN] Perceptron multicouche
[Termes IGN] scène urbaine
[Termes IGN] segmentation sémantique
[Termes IGN] semis de pointsRésumé : (auteur) Semantic segmentation of mobile laser scanning (MLS) point clouds can provide meaningful 3 D semantic information of urban facilities for various applications. However, it still remains a challenge to extract accurate 3 D semantic information from MLS point cloud data due to its irregular 3 D geometric structure in a large-scale outdoor scene. To this end, this study develops a geometry-aware attention point network (GAANet) with geometric properties of the point cloud as a reference. Specifically, the proposed method first builds a graph-like region for each input point to establish the geometric correlation toward its neighbors for robustly descripting local geometry-aware features. Thereafter, the method introduces a novel multi-head attention mechanism to efficiently learn local discriminative features on the constructed graphs and a feature combination operation to capture both local and global geometric dependencies inside fused point features for significantly facilitating the segmentation of small or incomplete 3 D objects at point-level. Finally, an adaptive loss function is appended to handle class imbalance for the overall performance improvement. The validation experiments on two challenging benchmarks demonstrate the effectiveness and powerful generation ability of the proposed method, which achieves state-of-the-art performance with mean IoU of 65.09% and 95.20% in the Toronto-3D and Oakland 3-D MLS dataset, respectively. Numéro de notice : A2023-038 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658816.2022.2111572 Date de publication en ligne : 24/08/2022 En ligne : https://doi.org/10.1080/13658816.2022.2111572 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102309
in International journal of geographical information science IJGIS > vol 37 n° 1 (January 2023) . - pp 138 - 161[article]A hierarchical multiview registration framework of TLS point clouds based on loop constraint / Hao Wu in ISPRS Journal of photogrammetry and remote sensing, vol 195 (January 2023)
PermalinkMapping the anthropic occupation of the territory. Tracing dynamics of human settlement from archaeological records and historic cartographies / Marina López Sánchez in Journal of maps, vol 18 n° 1 (January 2023)
PermalinkProgressive collapse of dual-line rivers based on river segmentation considering cartographic generalization rules / Fubing Zhang in ISPRS International journal of geo-information, vol 11 n° 12 (December 2022)
PermalinkGraph-based leaf–wood separation method for individual trees using terrestrial lidar point clouds / Zhilin Tian in IEEE Transactions on geoscience and remote sensing, vol 60 n° 11 (November 2022)
PermalinkAnalysis of the spatial range of service and accessibility of hospitals designated for coronavirus disease 2019 in Yunnan Province, China / Liangting Zheng in Geocarto international, vol 37 n° 22 ([10/10/2022])
PermalinkRaster-based method for building selection in the multi-scale representation of two-dimensional maps / Yilang Shen in Geocarto international, vol 37 n° 22 ([10/10/2022])
PermalinkEstimating urban functional distributions with semantics preserved POI embedding / Weiming Huang in International journal of geographical information science IJGIS, vol 36 n° 10 (October 2022)
PermalinkA relation-augmented embedded graph attention network for remote sensing object detection / Shu Tian in IEEE Transactions on geoscience and remote sensing, vol 60 n° 10 (October 2022)
PermalinkSpatio-temporal graph convolutional networks for road network inundation status prediction during urban flooding / Faxi Yuan in Computers, Environment and Urban Systems, vol 97 (October 2022)
PermalinkSpherical harmonic synthesis of area-mean potential values on irregular surfaces / Blažej Bucha in Journal of geodesy, vol 96 n° 10 (October 2022)
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