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Titre : Spationomy : Spatial exploration of economic data and methods of interdisciplinary analytics Type de document : Guide/Manuel Auteurs : Vit Pászto, Éditeur scientifique ; Carsten Jürgens, Éditeur scientifique ; Polona Tominc, Éditeur scientifique ; et al., Auteur Editeur : Springer Nature Année de publication : 2020 Importance : 333p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-030-26626-4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] acquisition de données
[Termes IGN] analyse multicritère
[Termes IGN] analyse spatiale
[Termes IGN] données socio-économiques
[Termes IGN] exploration de données géographiques
[Termes IGN] finance
[Termes IGN] géographie économique
[Termes IGN] microéconomie
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] recherche interdisciplinaire
[Termes IGN] régression logistique
[Termes IGN] système d'information géographique
[Termes IGN] veille économiqueRésumé : (éditeur) This open access book is based on 'Spationomy – Spatial Exploration of Economic Data', an interdisciplinary and international project in the frame of ERASMUS+ funded by the European Union. The project aims to exchange interdisciplinary knowledge in the fields of economics and geomatics. For the newly introduced courses, interdisciplinary learning materials have been developed by a team of lecturers from four different universities in three countries. In a first study block, students were taught methods from the two main research fields. Afterwards, the knowledge gained had to be applied in a project. For this international project, teams were formed, consisting of one student from each university participating in the project. The achieved results were presented in a summer school a few months later. At this event, more methodological knowledge was imparted to prepare students for a final simulation game about spatial and economic decision making. In a broader sense, the chapters will present the methodological background of the project, give case studies and show how visualisation and the simulation game works. Numéro de notice : 25973 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Manuel de cours DOI : 10.1007/978-3-030-26626-4 En ligne : https://doi.org/10.1007/978-3-030-26626-4 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96629
Titre : Sustainable land management in a European context : A co-design approach Type de document : Monographie Auteurs : Thomas Weith, Éditeur scientifique ; Tim Barkmann, Auteur ; Nadin Gaasch, Éditeur scientifique ; et al., Éditeur scientifique Editeur : Springer Nature Année de publication : 2020 Importance : 347 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-030-50841-8 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Ecologie
[Termes IGN] aménagement durable
[Termes IGN] aménagement rural
[Termes IGN] changement d'utilisation du sol
[Termes IGN] écosystème
[Termes IGN] Europe (géographie politique)
[Termes IGN] géosciences
[Termes IGN] gestion foncière
[Termes IGN] gestion forestière durable
[Termes IGN] paysage urbain
[Termes IGN] politique communautaire
[Termes IGN] recherche interdisciplinaire
[Termes IGN] sciences de l'environnement
[Termes IGN] surface cultivée
[Termes IGN] surveillance de l'urbanisationRésumé : (éditeur) This open access book presents and discusses current issues and innovative solution approaches for land management in a European context. Manifold sustainability issues are closely interconnected with land use practices. Throughout the world, we face increasing conflict over the use of land as well as competition for land. Drawing on experience in sustainable land management gained from seven years of the FONA programme (Research for Sustainable Development, conducted under the auspices of the German Federal Ministry of Education and Research), the book stresses and highlights co-design processes within the "co-creation of knowledge", involving collaboration in transdisciplinary research processes between academia and other stakeholders. The book begins with an overview of the current state of land use practices and the subsequent need to manage land resources more sustainably. New system solutions and governance approaches in sustainable land management are presented from a European perspective on land use. The volume also addresses how to use new modes of knowledge transfer between science and practice. New perspectives in sustainable land management and methods of combining knowledge and action are presented to a broad readership in land system sciences and environmental sciences, social sciences and geosciences. Note de contenu : 1- Land-use: State and drivers in Europe
2- Co-production of knowledge
3- Co-evolution: New system solutions and governance
4- OutlookNuméro de notice : 25987 Affiliation des auteurs : non IGN Thématique : FORET Nature : Recueil / ouvrage collectif DOI : 10.1007/978-3-030-50841-8 En ligne : https://doi.org/10.1007/978-3-030-50841-8 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96745 Torch-Points3D: A modular multi-task framework for reproducible deep learning on 3D point clouds / Thomas Chaton (2020)
Titre : Torch-Points3D: A modular multi-task framework for reproducible deep learning on 3D point clouds Type de document : Article/Communication Auteurs : Thomas Chaton, Auteur ; Nicolas Chaulet, Auteur ; Sofiane Horache, Auteur ; Loïc Landrieu , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2020 Projets : AI4GEO / Conférence : 3DV 2020, International Conference on 3D Vision 25/11/2020 27/11/2020 Fukuoka + en ligne Japon Proceedings IEEE Importance : 12 p. - n° 282 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Informatique
[Termes IGN] apprentissage profond
[Termes IGN] cadre conceptuel
[Termes IGN] code source libre
[Termes IGN] données localisées 3D
[Termes IGN] reproductibilité
[Termes IGN] réseau neuronal profond
[Termes IGN] semis de pointsRésumé : (auteur) We introduce Torch-Points3D, an open-source framework designed to facilitate the use of deep networks on 3D data. Its modular design, efficient implementation, and user-friendly interfaces make it a relevant tool for research and productization alike. Beyond multiple quality-of-life features, our goal is to standardize a higher level of transparency and reproducibility in 3D deep learning research, and to lower its barrier to entry. In this paper, we present the design principles of Torch-Points3D, as well as extensive benchmarks of multiple state-of-the-art algorithms and inference schemes across several datasets and tasks. The modularity of Torch-Points3D allows us to design fair and rigorous experimental protocols in which all methods are evaluated in the same conditions. The Torch-Points3D repository : https://github.com/nicolas-chaulet/torch-points3d. Numéro de notice : C2020-019 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/3DV50981.2020.00029 Date de publication en ligne : 19/01/2021 En ligne : https://doi.org/10.1109/3DV50981.2020.00029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96456 Towards interoperable research infrastructures for environmental and earth sciences / Zhiming Zhao (2020)
Titre : Towards interoperable research infrastructures for environmental and earth sciences : a reference model guided approach for common challenges Type de document : Monographie Auteurs : Zhiming Zhao, Éditeur scientifique ; Margareta Hellström, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2020 Collection : Lecture notes in Computer Science, ISSN 0302-9743 num. 12003 Importance : 373 p. ISBN/ISSN/EAN : 978-3-030-52829-4 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Société de l'information
[Termes IGN] données environnementales
[Termes IGN] géosciences
[Termes IGN] infrastructure
[Termes IGN] instrument de mesure
[Termes IGN] interopérabilité
[Termes IGN] monde virtuel
[Termes IGN] recherche scientifiqueRésumé : (Editeur) This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions. Note de contenu : 1--Data Management in Environmental and Earth Sciences
- Supporting Cross-Domain System-Level Environmental and Earth Science / Alex Vermeulen, Helen Glaves, Sylvie Pouliquen, and Alexandra Kokkinaki
- ICT Infrastructures for Environmental and Earth Sciences / Keith Jeffery, Antti Pursula, and Zhiming Zhao
- Common Challenges and Requirements / Barbara Magagna, Paul Martin, Abraham Nieva de la Hidalga, Malcolm Atkinson, and Zhiming Zhao
2--Reference Model Guided System Design and Development
- The ENVRI Reference Model / Abraham Nieva de la Hidalga, Alex Hardisty, Paul Martin, Barbara Magagna, and Zhiming Zhao
- Reference Model Guided Engineering / Zhiming Zhao and Keith Jeffery
- Semantic and Knowledge Engineering Using ENVRI RM / Paul Martin, Xiaofeng Liao, Barbara Magagna, Markus Stocker, and Zhiming Zhao
3--Common Data Management Services in Environmental RIs
- Data Curation and Preservation / Keith Jeffery
- Data Cataloguing / Erwann Quimbert, Keith Jeffery, Claudia Martens, Paul Martin, and Zhiming Zhao
- Identification and Citation of Digital Research Resources / Margareta Hellström, Maria Johnsson, and Alex Vermeulen
- Data Processing and Analytics for Data-Centric Sciences / Leonardo Candela, Gianpaolo Coro, Lucio Lelii, Giancarlo Panichi, and Pasquale Pagano
- Virtual Infrastructure Optimisation / Spiros Koulouzis, Paul Martin, and Zhiming Zhao
- Data Provenance / Barbara Magagna, Doron Goldfarb, Paul Martin, Malcolm Atkinson, Spiros Koulouzis, and Zhiming Zhao
- Semantic Linking of Research Infrastructure Metadata / Paul Martin, Barbara Magagna, Xiaofeng Liao, and Zhiming Zhao
- Authentication, Authorization, and Accounting / Alessandro Paolini, Diego Scardaci, Nicolas Liampotis, Vincenzo Spinoso, Baptiste Grenier, and Yin Chen
- Virtual Research Environments for Environmental and Earth Sciences : Approaches and Experiences / Keith Jeffery, Leonardo Candela, and Helen Glaves
4--Case Studies
- Case Study: Data Subscriptions Using Elastic Cloud Services / Spiros Koulouzis, Thierry Carval, Jani Heikkinen, Antti Pursula and Zhiming Zhao
- Case Study: ENVRI Science Demonstrators with D4Science / Leonardo Candela, Markus Stocker, Ingemar Häggström, Carl-Fredrik Enell, Domenico Vitale, Dario Papale, Baptiste Grenier, Yin Chen, and Matthias Obst
- Case Study: LifeWatch Italy Phytoplankton VRE / Elena Stanca, Nicola Fiore, Ilaria Rosati, Lucia Vaira, Francesco Cozzoli, and Alberto Basset
5--Sustainability and Future Challenges
- Towards Cooperative Sustainability / Wouter Los
- Towards Operational Research Infrastructures with FAIR : Data and Services / Zhiming Zhao, Keith Jeffery, Markus Stocker, Malcolm Atkinson, and Andreas PetzoldNuméro de notice : 26497 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Recueil / ouvrage collectif DOI : 10.1007/978-3-030-52829-4 En ligne : https://doi.org/10.1007/978-3-030-52829-4 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96989 A representativeness-directed approach to mitigate spatial bias in VGI for the predictive mapping of geographic phenomena / Guiming Zhang in International journal of geographical information science IJGIS, vol 33 n° 9 (September 2019)
[article]
Titre : A representativeness-directed approach to mitigate spatial bias in VGI for the predictive mapping of geographic phenomena Type de document : Article/Communication Auteurs : Guiming Zhang, Auteur ; A - Xing Zhu, Auteur Année de publication : 2019 Article en page(s) : pp 1873 - 1893 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Aves
[Termes IGN] carte thématique
[Termes IGN] distribution spatiale
[Termes IGN] données localisées des bénévoles
[Termes IGN] échantillon
[Termes IGN] erreur d'échantillon
[Termes IGN] erreur de positionnement
[Termes IGN] erreur systématique
[Termes IGN] habitat (nature)
[Termes IGN] modèle de simulation
[Termes IGN] phénomène géographique
[Termes IGN] pondération
[Termes IGN] précision de localisation
[Termes IGN] régression logistique
[Termes IGN] representativité
[Termes IGN] science citoyenne
[Termes IGN] Wisconsin (Etats-Unis)Résumé : (auteur) Volunteered geographic information (VGI) contains valuable field observations that represent the spatial distribution of geographic phenomena. As such, it has the potential to provide regularly updated low-cost field samples for predictively mapping the spatial variations of geographic phenomena. The predictive mapping of geographic phenomena often requires representative samples for high mapping accuracy, but samples consisting of VGI observations are often not representative as they concentrate on specific geographic areas (i.e. spatial bias) due to the opportunistic nature of voluntary observation efforts. In this article, we propose a representativeness-directed approach to mitigate spatial bias in VGI for predictive mapping. The proposed approach defines and quantifies sample representativeness by comparing the probability distributions of sample locations and the mapping area in the environmental covariate space. Spatial bias is mitigated by weighting the sample locations to maximize their representativeness. The approach is evaluated using species habit suitability mapping as a case study. The results show that the accuracy of predictive mapping using weighted sample locations is higher than using unweighted sample locations. A positive relationship between sample representativeness and mapping accuracy is also observed, suggesting that sample representativeness is a valid indicator of predictive mapping accuracy. This approach mitigates spatial bias in VGI to improve predictive mapping accuracy. Numéro de notice : A2019-392 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1615071 Date de publication en ligne : 10/05/2019 En ligne : https://doi.org/10.1080/13658816.2019.1615071 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93490
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