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LinkClimate: An interoperable knowledge graph platform for climate data / Jiantao Wu in Computers & geosciences, vol 169 (December 2022)  

Public [article]  inComputers & geosciences > vol 169 (December 2022) . - n° 105215 Titre : LinkClimate: An interoperable knowledge graph platform for climate data Type de document : Article/Communication Auteurs : Jiantao Wu, Auteur ; Fabrizio Orlandi, Auteur ; Declan O'Sullivan, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 105215 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] changement climatique [Termes IGN] données météorologiques [Termes IGN] données multisources [Termes IGN] historique des données [Termes IGN] interopérabilité sémantique [Termes IGN] National oceanic and atmospheric administration [Termes IGN] ontologie [Termes IGN] OpenStreetMap [Termes IGN] réseau sémantique [Termes IGN] site wiki [Termes IGN] SPARQL [Termes IGN] web sémantique Résumé : (auteur) Climate science has become more ambitious in recent years as global awareness about the environment has grown. To better understand climate, historical climate(e.g. archived meteorological variables such as temperature, wind, water, etc.) and climate-related data (e.g. geographical features and human activities) are widely used by today’s climate research to derive models for an explainable climate change and its effects. However, such data sources are often dispersed across a multitude of disconnected data silos on the Web. Moreover, there is a lack of advanced climate data platforms to enable multi-source heterogeneous climate data analysis, therefore, researchers must face a stern challenge in collecting and analyzing multi-source data. In this paper, we address this problem by proposing a climate knowledge graph for the integration of multiple climate data and other data sources into one service, leveraging Web technologies (e.g. HTTP) for multi-source climate data analysis. The proposed knowledge graph is primarily composed of data from the National Oceanic and Atmospheric Administration’s daily climate summaries, OpenStreetMap, and Wikidata, and it supports joint data queries on these widely used databases. This paper shows, with a use case in Ireland and the United Kingdom, how climate researchers could benefit from this platform as it allows them to easily integrate datasets from different domains and geographical locations. Numéro de notice : A2022-789 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.cageo.2022.105215 Date de publication en ligne : 30/08/2022 En ligne : https://doi.org/10.1016/j.cageo.2022.105215 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101897 [article]

Performance benchmark on semantic web repositories for spatially explicit knowledge graph applications / Wenwen Li in Computers, Environment and Urban Systems, vol 98 (December 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 98 (December 2022) . - n° 101884 Titre : Performance benchmark on semantic web repositories for spatially explicit knowledge graph applications Type de document : Article/Communication Auteurs : Wenwen Li, Auteur ; Sizhe Wang, Auteur ; Sheng wu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101884 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] base de données relationnelles [Termes IGN] entrepôt de données [Termes IGN] ontologie [Termes IGN] RDF [Termes IGN] référentiel sémantique [Termes IGN] requête spatiale [Termes IGN] réseau sémantique [Termes IGN] SPARQL [Termes IGN] stockage de données [Termes IGN] test de performance [Termes IGN] web sémantique Résumé : (auteur) Knowledge graph has become a cutting-edge technology for linking and integrating heterogeneous, cross-domain datasets to address critical scientific questions. As big data has become prevalent in today's scientific analysis, semantic data repositories that can store and manage large knowledge graph data have become critical in successfully deploying spatially explicit knowledge graph applications. This paper provides a comprehensive evaluation of the popular semantic data repositories and their computational performance in managing and providing semantic support for spatial queries. There are three types of semantic data repositories: (1) triple store solutions (RDF4j, Fuseki, GraphDB, Virtuoso), (2) property graph databases (Neo4j), and (3) an Ontology-Based Data Access (OBDA) approach (Ontop). Experiments were conducted to compare each repository's efficiency (e.g., query response time) in handling geometric, topological, and spatial-semantic related queries. The results show that Virtuoso achieves the overall best performance in both non-spatial and spatial-semantic queries. The OBDA solution, Ontop, has the second-best query performance in spatial and complex queries and the best storage efficiency, requiring the least data-to-RDF conversion efforts. Other triple store solutions suffer from various issues that cause performance bottlenecks in handling spatial queries, such as inefficient memory management and lack of proper query optimization. Numéro de notice : A2022-720 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101884 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101884 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101654 [article]

Graph-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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 60 n° 11 (November 2022) . - n° 5705111 Titre : Graph-based leaf–wood separation method for individual trees using terrestrial lidar point clouds Type de document : Article/Communication Auteurs : Zhilin Tian, Auteur ; Shihua Li, Auteur Année de publication : 2022 Article en page(s) : n° 5705111 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] bois [Termes IGN] branche (arbre) [Termes IGN] chemin le plus court, algorithme du [Termes IGN] données lidar [Termes IGN] échantillonnage de données [Termes IGN] extraction de traits caractéristiques [Termes IGN] feuille (végétation) [Termes IGN] graphe [Termes IGN] Python (langage de programmation) [Termes IGN] segmentation [Termes IGN] semis de points Résumé : (auteur) Terrestrial light detection and ranging (lidar) is capable of resolving trees at the branch/leaf level with accurate and dense point clouds. The separation of leaf and wood components is a prerequisite for the estimation of branch/leaf-scale biophysical properties and realistic tree model reconstruction. Most existing methods have been tested on trees with similar structures; their robustness for trees of different species and sizes remains relatively unexplored. This study proposed a new graph-based leaf–wood separation (GBS) method for individual trees purely using the xyz -information of the point cloud. The GBS method fully utilized the shortest path-based features, as the shortest path can effectively reflect the structures for trees of different species and sizes. Ten types of tree data—covering tropical, temperate, and boreal species—with heights ranging from 5.4 to 43.7 m, were used to test the method performance. The mean accuracy and kappa coefficient at the point level were 94% and 0.78, respectively, and our method outperformed two other state-of-the-art methods. Through further analysis and testing, the GBS method exhibited a strong ability for detecting small and leaf-surrounded branches, and was also sufficiently robust in terms of data subsampling. Our research further demonstrated the potential of the shortest path-based features in leaf–wood separation. The entire framework was provided for use as an open-source Python package, along with our labeled validation data. Numéro de notice : A2022-853 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2022.3218603 Date de publication en ligne : 01/11/2022 En ligne : https://doi.org/10.1109/TGRS.2022.3218603 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102099 [article]

Habitats, agricultural practices, and population dynamics of a threatened species: The European turtle dove in France / Christophe Sauser in Biological Conservation, vol 274 (octobre 2022)  

Public [article]  inBiological Conservation > vol 274 (octobre 2022) . - n° 109730 Titre : Habitats, agricultural practices, and population dynamics of a threatened species: The European turtle dove in France Type de document : Article/Communication Auteurs : Christophe Sauser, Auteur ; Loïc Commagnac , Auteur ; Cyril Eraud, Auteur ; et al., Auteur Année de publication : 2022 Projets : 1-Pas de projet / Article en page(s) : n° 109730 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] agronomie [Termes IGN] analyse diachronique [Termes IGN] Aves [Termes IGN] habitat animal [Termes IGN] haie [Termes IGN] impact sur l'environnement [Termes IGN] jachère [Termes IGN] lisière [Termes IGN] modèle numérique [Termes IGN] politique de conservation (biodiversité) [Termes IGN] R (langage) Mots-clés libres : tourterelle des bois  Streptopelia turtur Résumé : (auteur) Agricultural changes in recent decades have led to a widespread loss of biodiversity, with habitat loss considered as the main factor in the decline. The European turtle dove is one of the farmland birds that has declined markedly in Europe, leading the IUCN to downgrade its status in 2015 from “Near Threatened” to “Vulnerable”. Knowledge of how habitat factors and agricultural practices influence the turtle dove population is crucial for the conservation of this species through the implementation of targeted measures. Here we investigate how foraging and nesting habitats influence the abundance of turtle doves at national and regional scales, using a 23-year dataset from point counts carried out throughout France, a stronghold country for this species during the breeding season. We found that turtle dove abondance was positively affected by fallow lands, both at national and regional scales. Turtle dove abundance was also negatively affected by fodder crop area at national scale, but the effect was detected in only four of the 13 French regions. We also showed that an increase in hedgerows length had a positive effect on turtle dove abundance. On the other hand, forest edges length showed a bell-shaped trend, suggesting that an increase in forest edges length may have a favourable effect on turtle dove abundance only up to a given threshold. We suggest that targeted conservation measures combining an increase in fallow lands and hedgerows length could allow the stabilisation or even an increase in turtle dove abundance in France, but also in European countries with similar landscapes. Numéro de notice : A2022-687 Affiliation des auteurs : IGN+Ext (2020- ) Thématique : BIODIVERSITE/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.biocon.2022.109730 Date de publication en ligne : 09/09/2022 En ligne : https://doi.org/10.1016/j.biocon.2022.109730 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101612 [article]

Novel algorithm based on geometric characteristics for tree branch skeleton extraction from LiDAR point cloud / Jie Yang in Forests, vol 13 n° 10 (October 2022)  

Public [article]  inForests > vol 13 n° 10 (October 2022) . - n° 1534 Titre : Novel algorithm based on geometric characteristics for tree branch skeleton extraction from LiDAR point cloud Type de document : Article/Communication Auteurs : Jie Yang, Auteur ; Xiaorong Wen, Auteur ; Qiulai Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1534 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse de groupement [Termes IGN] branche (arbre) [Termes IGN] C++ [Termes IGN] Chine [Termes IGN] données lidar [Termes IGN] extraction de traits caractéristiques [Termes IGN] itération [Termes IGN] modélisation de la forêt [Termes IGN] semis de points [Termes IGN] squelettisation Résumé : (auteur) More accurate tree models, such as branch skeleton, are needed to acquire forest inventory data. Currently available algorithms for constructing a branch skeleton from a LiDAR point cloud have low accuracy with problems such as irrational connection near trunk bifurcation, excessive central deviation and topological errors. Using the C++ and PCL library, a novel algorithm of the incomplete simulation of tree transmitting water and nutrients (ISTTWN), based on geometric characteristics for tree branch skeleton extraction, was developed in this research. The algorithm is an incomplete simulation of tree transmitting water and nutrients. Improvements were made to improve the time and memory consumption. The result show that the ISTTWN algorithm without any improvements is quite time consuming but has consecutive output. After improvement with iteration, the process is faster and has more detailed output. Breakpoint connection is added to recover continuity. The ISTTWN algorithm with improvements can produce a more accurate skeleton and cost less time than a previous algorithm. The superiority and effectiveness of the method are demonstrated, which provides a reference for the subsequent study of tree modeling and a prospect of application in other fields, such as virtual reality, computer games and movie scenes. Numéro de notice : A2022-835 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f13101534 Date de publication en ligne : 17/09/2022 En ligne : https://doi.org/10.3390/f13101534 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102032 [article]

Pyeo: A Python package for near-real-time forest cover change detection from Earth observation using machine learning / J.F. Roberts in Computers & geosciences, vol 167 (October 2022)  

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GNSSseg, a statistical method for the segmentation of daily GNSS IWV time series / Annarosa Quarello in Remote sensing, vol 14 n° 14 (July-2 2022)  

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A geospatial workflow for the assessment of public transit system performance using near real-time data / Anastassios Dardas in Transactions in GIS, vol 26 n° 4 (June 2022)  

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Narrative cartography with knowledge graphs / Gengchen Mai in Journal of Geovisualization and Spatial Analysis, vol 6 n° 1 (June 2022)  

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An algorithm to assist the robust filter for tightly coupled RTK/INS navigation system / Zun Niu in Remote sensing, vol 14 n° 10 (May-2 2022)  

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Automated inventory of broadleaf tree plantations with UAS imagery / Aishwarya Chandrasekaran in Remote sensing, vol 14 n° 8 (April-2 2022)  

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A survey on semantic question answering systems / Christina Antoniou in The Knowledge Engineering Review, vol 37 (2022)  

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Construction d’un plugin QGIS de détection d’îlots de chaleur urbains à partir d’images satellitaires de type optique / Houssayn Meriche (2022)   

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Création d’un indicateur de qualité de la desserte des transports pour des parcelles à une échelle locale / Nick Lin (2022) 

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Etude de la propagation de l’onde de crue du bassin versant de la Save / Emma Bonzom (2022) 

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