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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)  

Public [article]  inJournal of Spatial Information Science (JoSIS) > n° 15 (September 2017) . - pp 35 - 64 Titre : VGI in surveying engineering : Introducing collaborative cloud land surveying Type de document : Article/Communication Auteurs : Ioannis Sofos, Auteur ; Vassilios Vescoukis, Auteur ; Maria Tsakiri-Strati, Auteur Année de publication : 2017 Article en page(s) : pp 35 - 64 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] Athènes [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] entrepôt de données localisées [Termes descripteurs IGN] géomètre [Termes descripteurs IGN] informatique en nuage [Termes descripteurs IGN] partage de données localisées [Termes descripteurs IGN] topographe Résumé : (Auteur) Volunteered geographic information (VGI) has enabled many innovative applications in various scientific fields. This paper introduces a new framework called “collaborative cloud-based land surveying” (CCLS) that uses VGI principles for data sharing among surveyor engineers to boost the productivity and improve the quality of their applications. A cloud-based spatio-temporal data repository is presented, aiming to facilitate the sharing of VGI among surveyor engineers. A fully-functional distributed software application has been developed and used to apply CCLS in a large-scale land surveying project run by the Greek Ministry of Culture, which involves the mapping of the historic center of Athens. Results from the data analysis of hundreds of measurements indicate a substantial (30% to 60%) error reduction and also a significant productivity raise (22%). The collected measurements are shared in an online database, accessible by professional surveyors who can in turn contribute their own data to further enhance the CCLS system. Numéro de notice : A2017-821 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5311/JOSIS.2017.15.320 En ligne : https://doi.org/10.5311/JOSIS.2017.15.320 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89306 [article]

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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) . - pp 907 - 938 Titre : A cyber-enabled spatial decision support system to inventory mangroves in Mozambique: coupling scientific workflows and cloud computing Type de document : Article/Communication Auteurs : Wenwu Tang, Auteur ; Wenpeng Feng, Auteur ; Meijuan Jia, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 907 - 938 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] informatique en nuage [Termes descripteurs IGN] inventaire de la végétation [Termes descripteurs IGN] lever des détails [Termes descripteurs IGN] mangrove [Termes descripteurs IGN] modélisation [Termes descripteurs IGN] Mozambique [Termes descripteurs IGN] synergiciel [Termes descripteurs IGN] système d'aide à la décision [Termes descripteurs IGN] Zambèze (fleuve) [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Mangroves are an important terrestrial carbon reservoir with numerous ecosystem services. Yet, it is difficult to inventory mangroves because of their low accessibility. A sampling approach that produces accurate assessment while maximizing logistical integrity of inventory operation is often required. Spatial decision support systems (SDSSs) provide support for integrating such a sampling design of fieldwork with operational considerations and evaluation of alternative scenarios. However, this fieldwork design driven by SDSS is often computationally intensive and repetitive. In this study, we develop a cyber-enabled SDSS framework to facilitate the computationally challenging fieldwork design that requires the efficacious selection of base camps and plots for the inventory of mangroves. Our study area is the Zambezi River Delta, Mozambique. Cyber-enabled capabilities, including scientific workflows and cloud computing, are integrated with the SDSS. Scientific workflows enable the automation of data and modeling tasks in the SDSS. Cloud computing offers on-demand computational support for interoperation among stakeholders for collaborative scenario evaluation for the fieldwork design of mangrove inventory. Further, this framework allows for harnessing high-performance computing capabilities for accelerating the fieldwork design. The cyber-enabled framework provides significant merits in terms of effective coordination among science and logistical teams, assurance of meeting inventory objectives, and an objective basis to collectively and efficaciously evaluate alternative scenarios. Numéro de notice : A2017-237 Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1250900 En ligne : http://dx.doi.org/10.1080/13658816.2016.1250900 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85171 [article]

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