INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACH

Remote sensing satellites, together with aerial and terrestrial platforms (mobile and fixed), produce nowadays huge amounts of data coming from a wide variety of sensors. These datasets serve as main data sources for the extraction of Geospatial Reference Information (GRI), constituting the “skeleto...

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Main Authors: A. Arozarena, G. Villa, N. Valcárcel, B. Pérez
Format: Article
Language:English
Published: Copernicus Publications 2016-06-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B4/721/2016/isprs-archives-XLI-B4-721-2016.pdf
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spelling doaj-a6795077f1a4441a94f4f5030a6970b92020-11-25T01:06:06ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342016-06-01XLI-B472172510.5194/isprs-archives-XLI-B4-721-2016INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACHA. Arozarena0G. Villa1N. Valcárcel2B. Pérez3Spanish National Geographic Institute, Land Observation Unit, 3 General Ibáñez de Ibero, 28003 Madrid, SpainSpanish National Geographic Institute, Land Observation Unit, 3 General Ibáñez de Ibero, 28003 Madrid, SpainSpanish National Geographic Institute, Land Observation Unit, 3 General Ibáñez de Ibero, 28003 Madrid, SpainSpanish National Geographic Institute, Land Observation Unit, 3 General Ibáñez de Ibero, 28003 Madrid, SpainRemote sensing satellites, together with aerial and terrestrial platforms (mobile and fixed), produce nowadays huge amounts of data coming from a wide variety of sensors. These datasets serve as main data sources for the extraction of Geospatial Reference Information (GRI), constituting the “skeleton” of any Spatial Data Infrastructure (SDI). <br><br> Since very different situations can be found around the world in terms of geographic information production and management, the generation of global GRI datasets seems extremely challenging. Remotely sensed data, due to its wide availability nowadays, is able to provide fundamental sources for any production or management system present in different countries. After several automatic and semiautomatic processes including ancillary data, the extracted geospatial information is ready to become part of the GRI databases. <br><br> In order to optimize these data flows for the production of high quality geospatial information and to promote its use to address global challenges several initiatives at national, continental and global levels have been put in place, such as European INSPIRE initiative and Copernicus Programme, and global initiatives such as the Group on Earth Observation/Global Earth Observation System of Systems (GEO/GEOSS) and United Nations Global Geospatial Information Management (UN-GGIM). These workflows are established mainly by public organizations, with the adequate institutional arrangements at national, regional or global levels. Other initiatives, such as Volunteered Geographic Information (VGI), on the other hand may contribute to maintain the GRI databases updated. <br><br> Remotely sensed data hence becomes one of the main pillars underpinning the establishment of a global SDI, as those datasets will be used by public agencies or institutions as well as by volunteers to extract the required spatial information that in turn will feed the GRI databases. <br><br> This paper intends to provide an example of how institutional arrangements and cooperative production systems can be set up at any territorial level in order to exploit remotely sensed data in the most intensive manner, taking advantage of all its potential.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B4/721/2016/isprs-archives-XLI-B4-721-2016.pdf
collection DOAJ
language English
format Article
sources DOAJ
author A. Arozarena
G. Villa
N. Valcárcel
B. Pérez
spellingShingle A. Arozarena
G. Villa
N. Valcárcel
B. Pérez
INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACH
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet A. Arozarena
G. Villa
N. Valcárcel
B. Pérez
author_sort A. Arozarena
title INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACH
title_short INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACH
title_full INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACH
title_fullStr INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACH
title_full_unstemmed INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACH
title_sort integration of remotely sensed data into geospatial reference information databases. un-ggim national approach
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2016-06-01
description Remote sensing satellites, together with aerial and terrestrial platforms (mobile and fixed), produce nowadays huge amounts of data coming from a wide variety of sensors. These datasets serve as main data sources for the extraction of Geospatial Reference Information (GRI), constituting the “skeleton” of any Spatial Data Infrastructure (SDI). <br><br> Since very different situations can be found around the world in terms of geographic information production and management, the generation of global GRI datasets seems extremely challenging. Remotely sensed data, due to its wide availability nowadays, is able to provide fundamental sources for any production or management system present in different countries. After several automatic and semiautomatic processes including ancillary data, the extracted geospatial information is ready to become part of the GRI databases. <br><br> In order to optimize these data flows for the production of high quality geospatial information and to promote its use to address global challenges several initiatives at national, continental and global levels have been put in place, such as European INSPIRE initiative and Copernicus Programme, and global initiatives such as the Group on Earth Observation/Global Earth Observation System of Systems (GEO/GEOSS) and United Nations Global Geospatial Information Management (UN-GGIM). These workflows are established mainly by public organizations, with the adequate institutional arrangements at national, regional or global levels. Other initiatives, such as Volunteered Geographic Information (VGI), on the other hand may contribute to maintain the GRI databases updated. <br><br> Remotely sensed data hence becomes one of the main pillars underpinning the establishment of a global SDI, as those datasets will be used by public agencies or institutions as well as by volunteers to extract the required spatial information that in turn will feed the GRI databases. <br><br> This paper intends to provide an example of how institutional arrangements and cooperative production systems can be set up at any territorial level in order to exploit remotely sensed data in the most intensive manner, taking advantage of all its potential.
url http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B4/721/2016/isprs-archives-XLI-B4-721-2016.pdf
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