Centre dedocumentation
scientifique

Manual of Digital Earth / Huadong Guo (2020)  

Public Titre : Manual of Digital Earth Type de document : Monographie Auteurs : Huadong Guo, Auteur ; Michael F. Goodchild, Auteur ; Alessandro Annoni, Auteur Editeur : Springer International Publishing Année de publication : 2020 Importance : 852 p. ISBN/ISSN/EAN : 978-981-329-915-3 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Société de l'information [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] développement durable [Termes descripteurs IGN] données localisées numériques [Termes descripteurs IGN] données massives [Termes descripteurs IGN] données numériques [Termes descripteurs IGN] informatique en nuage [Termes descripteurs IGN] Infrastructure de données [Termes descripteurs IGN] intelligence artificielle [Termes descripteurs IGN] télédétection Résumé : (éditeur) This open access book offers a summary of the development of Digital Earth over the past twenty years. By reviewing the initial vision of Digital Earth, the evolution of that vision, the relevant key technologies, and the role of Digital Earth in helping people respond to global challenges, this publication reveals how and why Digital Earth is becoming vital for acquiring, processing, analysing and mining the rapidly growing volume of global data sets about the Earth. The main aspects of Digital Earth covered here include: Digital Earth platforms, remote sensing and navigation satellites, processing and visualizing geospatial information, geospatial information infrastructures, big data and cloud computing, transformation and zooming, artificial intelligence, Internet of Things, and social media. Moreover, the book covers in detail the multi-layered/multi-faceted roles of Digital Earth in response to sustainable development goals, climate changes, and mitigating disasters, the applications of Digital Earth (such as digital city and digital heritage), the citizen science in support of Digital Earth, the economic value of Digital Earth, and so on. This book also reviews the regional and national development of Digital Earth around the world, and discusses the role and effect of education and ethics. Lastly, it concludes with a summary of the challenges and forecasts the future trends of Digital Earth. By sharing case studies and a broad range of general and scientific insights into the science and technology of Digital Earth, this book offers an essential introduction for an ever-growing international audience. Note de contenu : Part I Digital Earth Technologies Part II Digital Earth for Multi-domain Applications Part III Digital Earth Regional & National Development Part IV Digital Earth Education and Ethics Numéro de notice : 25688 Thématique : SOCIETE NUMERIQUE Nature : Monographie En ligne : https://doi.org/10.1007/978-981-32-9915-3 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94727

Tile & merge: Distributed Delaunay triangulations for cloud computing / Laurent Caraffa (2019)  

Public Titre : Tile & merge: Distributed Delaunay triangulations for cloud computing Type de document : Article/Communication Auteurs : Laurent Caraffa , Auteur ; Pooran Memari, Auteur ; Murat Yirci, Auteur ; Mathieu Brédif , Auteur Congrès : Big Data 2019, IEEE International Conference on Big Data (9 - 12 décembre 2019; Los Angeles, Californie - Etats-Unis), Commanditaire Editeur : New-York : IEEE Computer society Année de publication : 2019 Importance : 7 p. Format : 21 x 30 cm Note générale : bibliographie preprint dans HAL https://hal.archives-ouvertes.fr/hal-02535021 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] géomètrie algorithmique [Termes descripteurs IGN] informatique en nuage [Termes descripteurs IGN] jeu de données [Termes descripteurs IGN] mémoire d'ordinateur [Termes descripteurs IGN] reconstruction d'objet [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] Spark [Termes descripteurs IGN] triangulation de Delaunay Résumé : (auteur) Motivated by the needs of a scalable out-of-core surface reconstruction algorithm available on the cloud, this paper addresses the computation of distributed Delaunay triangulations of massive point sets. The proposed algorithm takes as input a point cloud and first partitions it across multiple processing elements into tiles of relatively homogeneous point sizes. The distributed computation and communication between processing elements is orchestrated so that each one discovers the Delaunay neighbors of its input points within the theoretical overall Delaunay triangulation of all points and computes locally a partial view of this triangulation. This approach prevents memory limitations by never materializing the global triangulation. This efficiency is due to our proposed uncentralized model to represent, manage and locally construct the triangulation corresponding to each tile. The point set is first partitioned into non-overlapping tiles, then we construct within each tile the Delaunay triangulation of the local points and a minimal set of replicated foreign points in order to capture the simplices spanning multiple tiles. Inspired by the star splaying approach for Delaunay triangulation computation/repair, communication is limited to exchanging points of potential Delaunay neighbors across tiles. Therefore, our method is guaranteed to reconstruct, within each tile, a triangulation that contains the star of its local points, as though it were computed within the Delaunay triangulation of all points. The proposed algorithm is implemented with Spark for the scheduling and C++ for the geometric computations. This allows both an optimal scheduling on multiple machines and efficient low-level computation. The results show the efficiency of our algorithm in terms of speedup and strong scaling on a classical Spark configuration with both synthetic and real use case datasets. Numéro de notice : C2019-033 Thématique : IMAGERIE/INFORMATIQUE/MATHEMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/BigData47090.2019.9006534 date de publication en ligne : 24/02/2020 En ligne : https://doi.org/10.1109/BigData47090.2019.9006534 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95318

Automatic cloud resource management for interactive remote geovisualization / Tong Zhang in Transactions in GIS, vol 22 n° 6 (December 2018)  

Public [article]  inTransactions in GIS > vol 22 n° 6 (December 2018) . - pp 1437 - 1461 Titre : Automatic cloud resource management for interactive remote geovisualization Type de document : Article/Communication Auteurs : Tong Zhang, Auteur ; Jing Li, Auteur Année de publication : 2018 Article en page(s) : pp 1437 - 1461 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] automatisation [Termes descripteurs IGN] informatique en nuage [Termes descripteurs IGN] modèle dynamique [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) Remote geovisualization has gained momentum to support large‐scale geospatial data analysis and complex decision‐making over the last few years. Cloud computing, due to its capabilities to deliver on‐demand computing resources, has been embraced to develop and deploy interactive and scalable remote geovisualization applications. However, current cloud computing frameworks do not offer a versatile resource management scheme that is readily applicable for online remote visualization services, which usually require maintaining a satisfactory service level over time under dynamic workloads. To address this gap, we propose an automatic cloud resource management approach based on a bi‐level scheduling and horizontal scaling scheme to exploit cloud resources efficiently. At the lower level, a dynamic task‐scheduling scheme using collaborative filtering techniques is proposed to allocate virtual cloud resources to execute sub‐tasks. The scheduling scheme considers spatio‐temporal patterns presented in visualization views. At the upper level, reinforcement learning is adopted to perform resource auto‐scaling based on a reward function that integrates three different facets, namely: time cost, resource cost, and service stability. The original reinforcement learning algorithm is improved in two main aspects: (1) considering the delay of resource provisioning that is common in cloud environments; and (2) using online Gaussian estimation to estimate Q values. Task scheduling and auto‐scaling interact with each other and are integrated to deliver a comprehensive and responsive resource management solution. Experimental results demonstrate that our approach outperforms several existing cloud resource management methods. The proposed approach is also applicable for other interactive visualization applications, which have similar workload characteristics and performance requirements as interactive remote geovisualization. Numéro de notice : A2018-567 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12479 date de publication en ligne : 10/12/2018 En ligne : https://doi.org/10.1111/tgis.12479 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92286 [article]

Automated delineation of wildfire areas using Sentinel-2 satellite imagery / Mira Weirather in GI Forum, vol 2018 n° 1 ([01/01/2018])  

Public [article]  inGI Forum > vol 2018 n° 1 [01/01/2018] . - pp 251 - 262 Titre : Automated delineation of wildfire areas using Sentinel-2 satellite imagery Type de document : Article/Communication Auteurs : Mira Weirather, Auteur ; Gunter Zeug, Auteur ; Thomas Schneider, Auteur Année de publication : 2018 Article en page(s) : pp 251 - 262 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Copernicus (programme européen) [Termes descripteurs IGN] extraction automatique [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] incendie de forêt [Termes descripteurs IGN] informatique en nuage Résumé : (auteur) Climate change will bring many changes to the world. For example, the frequency and severity of natural hazards and related disasters are expected to increase globally. Wildfires already affect thousands of people every year and cause billions of Euros’ worth of damage. It is therefore paramount to develop measures that help deal with the consequences of wildfires. Forests being the largest terrestrial ecosystem in the European Union and providing many ecosystem services, their loss due to wildfires is of serious concern. In this study, an algorithm to extract the burned area of wildfire events is presented. It was developed on the basis of three fire events in 2017. The procedure is fully automated, from downloading suitable data to determining the burned area by applying the differenced Normalized Burn Ratio (dNBR) on open Sentinel-2 satellite imagery from the European Copernicus programme. First results show good performance and encourage its further development and application. It is planned that the output of our mapping will feed into and be used in calibrating wildfire simulations during longer fire events. Numéro de notice : A2018-302 Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1553/giscience2018_01_s251 En ligne : https://doi.org/10.1553/giscience2018_01_s251 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90400 [article]

A cloud-enabled automatic disaster analysis system of multi-sourced data streams: An example synthesizing social media, remote sensing and Wikipedia data / Qunying Huang in Computers, Environment and Urban Systems, vol 66 (November 2017)  

Public [article]  inComputers, Environment and Urban Systems > vol 66 (November 2017) . - pp 23 - 37 Titre : A cloud-enabled automatic disaster analysis system of multi-sourced data streams: An example synthesizing social media, remote sensing and Wikipedia data Type de document : Article/Communication Auteurs : Qunying Huang, Auteur ; Guido Cervone, Auteur ; Guiming Zhang, Auteur Année de publication : 2017 Article en page(s) : pp 23 - 37 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] caractérisation [Termes descripteurs IGN] catastrophe naturelle [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] exploration de données géographiques [Termes descripteurs IGN] exploration de texte [Termes descripteurs IGN] image numérique [Termes descripteurs IGN] informatique en nuage [Termes descripteurs IGN] inondation [Termes descripteurs IGN] intégration de données [Termes descripteurs IGN] interface web [Termes descripteurs IGN] prototype [Termes descripteurs IGN] tempête [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Social media streams and remote sensing data have emerged as new sources for tracking disaster events, and assessing their damages. Previous studies focus on a case-by-case approach, where a specific event was first chosen and filtering criteria (e.g., keywords, spatiotemporal information) are manually designed and used to retrieve relevant data for disaster analysis. This paper presents a framework that synthesizes multi-sourced data (e.g., social media, remote sensing, Wikipedia, and Web), spatial data mining and text mining technologies to build an architecturally resilient and elastic solution to support disaster analysis of historical and future events. Within the proposed framework, Wikipedia is used as a primary source of different historical disaster events, which are extracted to build an event database. Such a database characterizes the salient spatiotemporal patterns and characteristics of each type of disaster. Additionally, it can provide basic semantics, such as event name (e.g., Hurricane Sandy) and type (e.g., flooding) and spatiotemporal scopes, which are then tuned by the proposed procedures to extract additional information (e.g., hashtags for searching tweets), to query and retrieve relevant social media and remote sensing data for a specific disaster. Besides historical event analysis and pattern mining, the cloud-based framework can also support real-time event tracking and monitoring by providing on-demand and elastic computing power and storage capabilities. A prototype is implemented and tested with data relative to the 2011 Hurricane Sandy and the 2013 Colorado flooding. Numéro de notice : a2017-430 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : https://doi.org/10.1016/j.compenvurbsys.2017.06.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86330 [article]

VGI in surveying engineering : Introducing collaborative cloud land surveying / Ioannis Sofos in Journal of Spatial Information Science (JoSIS), n° 15 (September 2017)  

Permalink

A cyber-enabled spatial decision support system to inventory mangroves in Mozambique: coupling scientific workflows and cloud computing / Wenwu Tang in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

Permalink

Developing an integrated cloud-based spatial-temporal system for monitoring phenology / M. Cope in Ecological Informatics, vol 39 (May 2017)  

Permalink

Enabling point pattern analysis on spatial big data using cloud computing: optimizing and accelerating Ripley’s K function / Guiming Zhang in International journal of geographical information science IJGIS, vol 30 n° 11-12 (November - December 2016)  

Permalink

Service-oriented model-encapsulation strategy for sharing and integrating heterogeneous geo-analysis models in an open web environment / Songshan Yue in ISPRS Journal of photogrammetry and remote sensing, vol 114 (April 2016)  

Permalink

Maps and the meaning of the cloud / Michael P. Peterson in Cartographica, vol 50 n° 4 (Winter 2015)  

Permalink

Forming a global monitoring mechanism and a spatiotemporal performance model for geospatial services / Jizhe Xia in International journal of geographical information science IJGIS, vol 29 n° 3 (March 2015)  

Permalink

Architecture de l'information / Jean-Michel Salaün (2015)

Permalink

La gestion des identités numériques / Maryline Laurent (2015)

Permalink

Quand le Cloud favorise de nouveaux modes de commercialisation / Françoise de Blomac in DécryptaGéo le mag, n° 163 (janvier 2015)

Permalink