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Titre : Martin Waldseemüller’s carta marina of 1516 : Study and transcription of the long legends Type de document : Monographie Auteurs : Chet Van Duzer, Auteur Editeur : Springer Nature Année de publication : 2020 Importance : 150 p. ISBN/ISSN/EAN : 978-3-030-22703-6 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie ancienne
[Termes descripteurs IGN] carte ancienne
[Termes descripteurs IGN] carte marine
[Termes descripteurs IGN] histoire de la cartographie
[Termes descripteurs IGN] Renaissance
[Termes descripteurs IGN] seizième siècleRésumé : (éditeur) This open access book presents the first detailed study of one of the most important masterpieces of Renaissance cartography, Martin Waldseemüller’s Carta marina of 1516. By transcribing, translating into English, and detailing the sources of all of the descriptive texts on the map, as well as the sources of many of the images, the book makes the map available to scholars in a wholly unprecedented way. In addition, the book provides revealing insights into how Waldseemüller went about making the map (information that can’t be found in any other source). The Carta marina is the result of Waldseemüller’s radical re-evaluation of what a world map should be; he essentially started from scratch when he created it, rejecting the Ptolemaic model and other sources he had used in creating his 1507 map, and added more descriptive texts and a wealth of illustrations. Given its content, the book offers an essential reference work not only on this map, but also for anyone working in sixteenth-century European cartography. Note de contenu : 1- Introduction to the Carta Marina
2- The Long Legends: Transcription, Translation, and CommentaryNuméro de notice : 25981 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Monographie DOI : 10.1007/978-3-030-22703-6 En ligne : https://doi.org/10.1007/978-3-030-22703-6 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96714 Nonparametric Bayesian learning for collaborative robot multimodal introspection / Xuefeng Zhou · (2020)
Titre : Nonparametric Bayesian learning for collaborative robot multimodal introspection Type de document : Monographie Auteurs : Xuefeng Zhou ·, Auteur ; Hongmin Wu, Auteur ; Juan Rojas, Auteur ; et al., Auteur Editeur : Springer Nature Année de publication : 2020 Importance : 137 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-981-1562631-- Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes descripteurs IGN] apprentissage automatique
[Termes descripteurs IGN] classification bayesienne
[Termes descripteurs IGN] Hidden Markov Model (HMM)
[Termes descripteurs IGN] inférence
[Termes descripteurs IGN] interface homme-machine
[Termes descripteurs IGN] modèle mathématique
[Termes descripteurs IGN] problème de Dirichlet
[Termes descripteurs IGN] robotiqueRésumé : (éditeur) This open access book focuses on robot introspection, which has a direct impact on physical human–robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies. In robotics, the ability to reason, solve their own anomalies and proactively enrich owned knowledge is a direct way to improve autonomous behaviors. To this end, the authors start by considering the underlying pattern of multimodal observation during robot manipulation, which can effectively be modeled as a parametric hidden Markov model (HMM). They then adopt a nonparametric Bayesian approach in defining a prior using the hierarchical Dirichlet process (HDP) on the standard HMM parameters, known as the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). The HDP-HMM can examine an HMM with an unbounded number of possible states and allows flexibility in the complexity of the learned model and the development of reliable and scalable variational inference methods. This book is a valuable reference resource for researchers and designers in the field of robot learning and multimodal perception, as well as for senior undergraduate and graduate university students. Note de contenu : 1- Introduction to robot introspection
2- Nonparametric Bayesian modeling of multimodal time series
3- Incremental learning robot task representation and identification
4- Nonparametric Bayesian method for robot anomaly monitoring
5- Nonparametric Bayesian method for robot anomaly diagnose
6- Learning policy for robot anomaly recovery based on robot introspectionNuméro de notice : 25965 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Monographie DOI : 10.1007%2F978-981-15-6263-1 En ligne : https://link.springer.com/book/10.1007%2F978-981-15-6263-1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96557
Titre : Remote sensing of plant biodiversity Type de document : Monographie Auteurs : Jeannine Cavender-Bares, Editeur scientifique ; John A. Gamon, Editeur scientifique ; Philip A. Townsend, Editeur scientifique Editeur : Springer Nature Année de publication : 2020 Importance : 581 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-030-33157-3 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] biodiversité
[Termes descripteurs IGN] données lidar
[Termes descripteurs IGN] écosystème
[Termes descripteurs IGN] espèce exotique envahissante
[Termes descripteurs IGN] hybridation naturelle (végétation)
[Termes descripteurs IGN] image hyperspectrale
[Termes descripteurs IGN] protection du paysage
[Termes descripteurs IGN] surveillance de la végétationRésumé : (éditeur) This Open Access volume aims to methodologically improve our understanding of biodiversity by linking disciplines that incorporate remote sensing, and uniting data and perspectives in the fields of biology, landscape ecology, and geography. The book provides a framework for how biodiversity can be detected and evaluated—focusing particularly on plants—using proximal and remotely sensed hyperspectral data and other tools such as LiDAR. The volume, whose chapters bring together a large cross-section of the biodiversity community engaged in these methods, attempts to establish a common language across disciplines for understanding and implementing remote sensing of biodiversity across scales. The first part of the book offers a potential basis for remote detection of biodiversity. An overview of the nature of biodiversity is described, along with ways for determining traits of plant biodiversity through spectral analyses across spatial scales and linking spectral data to the tree of life. The second part details what can be detected spectrally and remotely. Specific instrumentation and technologies are described, as well as the technical challenges of detection and data synthesis, collection and processing. The third part discusses spatial resolution and integration across scales and ends with a vision for developing a global biodiversity monitoring system. Topics include spectral and functional variation across habitats and biomes, biodiversity variables for global scale assessment, and the prospects and pitfalls in remote sensing of biodiversity at the global scale. Note de contenu : 1- The use of remote sensing to enhance biodiversity monitoring and detection: A critical challenge for the twenty-first century
2- Applying remote sensing to biodiversity science
3- Scaling functional traits from leaves to canopies
4- The Laegeren site: An augmented forest laboratory
5- Lessons learned from spectranomics: Wet tropical forests
6- Remote sensing for early, detailed, and accurate detection of forest disturbance and decline for protection of biodiversity
7- Linking leaf spectra to the plant tree of life
8- Linking foliar traits to belowground processes
9- Using remote sensing for modeling and monitoring species distributions
10- Remote sensing of geodiversity as a link to biodiversity
11- Predicting patterns of plant diversity and endemism in the tropics using remote sensing data: A study case from the Brazilian Atlantic Forest
12- Remote detection of invasive alien species
13- A range of earth observation techniques for assessing plant diversity
14- How the optical properties of leaves modify the absorption and scattering of energy and enhance leaf functionality
15- Spectral field campaigns: Planning and data collection
16- Consideration of scale in remote sensing of biodiversity
17- Integrating biodiversity, remote sensing, and auxiliary information for the study of ecosystem functioning and conservation at large spatial scales
18- Essential biodiversity variables: Integrating in-situ observations and remote sensing through modelingNuméro de notice : 25919 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/IMAGERIE Nature : Monographie En ligne : https://link.springer.com/book/10.1007%2F978-3-030-33157-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96126
Titre : Spationomy : Spatial exploration of economic data and methods of interdisciplinary analytics Type de document : Guide/Manuel Auteurs : Vit Pászto, Editeur scientifique ; Carsten Jürgens, Editeur scientifique ; Polona Tominc, Editeur 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 descripteurs IGN] acquisition de données
[Termes descripteurs IGN] analyse multicritère
[Termes descripteurs IGN] analyse spatiale
[Termes descripteurs IGN] données socio-économiques
[Termes descripteurs IGN] exploration de données géographiques
[Termes descripteurs IGN] finance
[Termes descripteurs IGN] géographie économique
[Termes descripteurs IGN] microéconomie
[Termes descripteurs IGN] modèle conceptuel de données localisées
[Termes descripteurs IGN] recherche interdisciplinaire
[Termes descripteurs IGN] régression logistique
[Termes descripteurs IGN] système d'information géographique
[Termes descripteurs 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, Editeur scientifique ; Tim Barkmann, Auteur ; Nadin Gaasch, Editeur scientifique ; et al., Editeur 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 descripteurs IGN] aménagement durable
[Termes descripteurs IGN] aménagement rural
[Termes descripteurs IGN] changement d'utilisation du sol
[Termes descripteurs IGN] écosystème
[Termes descripteurs IGN] Europe (géographie politique)
[Termes descripteurs IGN] géosciences
[Termes descripteurs IGN] gestion foncière
[Termes descripteurs IGN] gestion forestière durable
[Termes descripteurs IGN] paysage urbain
[Termes descripteurs IGN] politique communautaire
[Termes descripteurs IGN] recherche interdisciplinaire
[Termes descripteurs IGN] sciences de l'environnement
[Termes descripteurs IGN] surface cultivée
[Termes descripteurs 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
