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IQmulus

financed

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A High volume Fusion and Analysis Platform nfor Geospatial Point Clouds Covera...

A High volume Fusion and Analysis Platform nfor Geospatial Point Clouds Coverages and Volumetric Data Sets For geospatial applications, huge amounts of heterogeneous data sets of different topology are collected nowadays with different data acquisition techniques. Especially airborne and mobile platform LIDAR data are becoming ubiquito... see more

31/10/2016

SINTEF

11M€

Project Budget: 11M€

Project leader

SINTEF AS No se ha especificado una descripción o un objeto social para esta compañía.

PARTICIPATION DEPralty Sin fecha límite de participación.

Ver 14 Participantes

Financing granted El organismo FP7 notifico la concesión del proyecto The day 2016-10-31 We do not have the information of the call

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characteristics of the participant

Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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14 Participantes

SINTEF

0.00€ | Leader

TU Delft

N.D. | participant

IGN

N.D. | participant

INSTITUT FRANCAIS DE RECHERC...

N.D. | participant

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Project leader

SINTEF AS No se ha especificado una descripción o un objeto social para esta compañía.

Project Budget 11M€

participation deadline Sin fecha límite de participación.

Project description For geospatial applications, huge amounts of heterogeneous data sets of different topology are collected nowadays with different data acquisition techniques. Especially airborne and mobile platform LIDAR data are becoming ubiquitous, but SAR and stereophotogrammetry also contribute to the rapid growth of geotopographical data sets to sizes of tens to hundreds of TBs. Due to the problems of handling such large data volumes and the difficulty of fusing point clouds of heterogeneous provenance, rasters, volumetric data and 2D vector data, many of those new data sets are not used appropriately or not at all.Therefore, IQmulus is targeting to enable optimized use of large, heterogeneous geo-spatial data sets for better decision making through a high-volume fusion and analysis information management platform. This platform will transpose approaches and IT standards from distributed computing to enable distributed, service-oriented geospatial processing. We will determine optimal execution and distribution parameters for different geospatial processing tasks and to ensure that the IQmulus system can transparently execute processing on different architectures like GPGPU clusters or clouds. Methods will be developed to connect processing and visualization into a tight loop, ensuring high interactivity in the process to enable users to better understand correlations between heterogeneous data sets.Two testbeds will be implemented in IQmulus (Maritime Spatial Planning & Land Applications for Rapid Response and Territorial Management) to show the benefits of the approach for decision makers such as European industries interested in exploiting sea-borne resources such as renewable energy from wind parks, and citizens affected by emergency cases that require quick response. Result dissemination and evaluation of the IQmulus approach will be handled via a managed user group of relevant stakeholders such as political decision makers, geospatial processing developers and industry

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