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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m16c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP8W/3GTJ84E
Repositorysid.inpe.br/mtc-m18/2014/08.27.13.23
Last Update2014:08.27.13.23.04 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m18/2014/08.27.13.23.04
Metadata Last Update2023:01.30.13.13.10 (UTC) administrator
ISBN85-88442-43-4
ISSN2179-4847
Citation KeyBaumannGlocHofnScha:2002:CaSt
TitleQuerying large geo image databases: a case study
FormatImpresso, On-line.
Year2002
Access Date2024, Apr. 16
Secondary TypePRE CN
Number of Files1
Size730 KiB
2. Context
Author1 Baumann, Peter
2 Glock, Clemens
3 Hofner, Maximilian
4 Schatz, Walter
Affiliation1 Active Knowledge GmbH
2 Active Knowledge GmbH
3 Active Knowledge GmbH
4 Active Knowledge GmbH
EditorDavis Júnior, Clodoveu Augusto
Borges, Karla Albuquerque de Vasconcelos
e-Mail Addressgeoinfo@dpi.inpe.br
Conference NameSimpósio Brasileiro de Geoinformática, 4 (GEOINFO).
Conference LocationCaxambu
Date5-6 dez. 2002
PublisherSociedade Brasileira de Computação (SBC)
Publisher CityBelo Horizonte
Pages91-98
Book TitleAnais
History (UTC)2014-08-27 13:23:04 :: geoinfo@dpi.inpe.br -> administrator ::
2020-05-18 14:43:51 :: administrator -> simone :: 2002
2020-05-18 15:02:15 :: simone -> administrator :: 2002
2023-01-30 13:13:10 :: administrator -> simone :: 2002
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
AbstractOnline services based on extremely large volumes of aerial and satellite imagery are becoming more and more important, being established both by public authorities and private providers.Technically, the requirement is to store raster arrays of multi-Terabyte sizes and to offer flexible, efficient support for extracting rectangular cutouts and performing raster operations such as zooming, overlaying, channel extraction, and derivation of value-added information like vegetation index. Usually such image servers today are implemented file based, because standard DBMSs currently do not give adequate query support for the functionality sketched. Providing maps and aerial imagery of Bavaria is the task of the Bavarian Land Survey Authority. The state of Bavaria covers 20% of the area of Germany; its aerial photo coverage consists of 13,500 images. As the first German state, Bavaria has set up a database server for web-bases raster image access recently, based on a combination of the array database middleware RasDaMan and Oracle. Tea seamless aerial image, which has been compressed losslessly, occupies about 700 GB on disk. In this contribution we present design rationales, server architecture, and first experience.
AreaSRE
Arrangement 1urlib.net > BDMCI > Fonds > GEOINFO > IV GEOINFO > Querying large geo...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > IV GEOINFO > Querying large geo...
Arrangement 3urlib.net > BDMCI > Fonds > GEOINFO > Coleção GEOINFO > Querying large geo...
Arrangement 4Local Collection Index... > Querying large geo...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGP8W/3GTJ84E
zipped data URLhttp://urlib.net/zip/8JMKD3MGP8W/3GTJ84E
Languageen
Target Filepaper12.pdf
User Groupgeoinfo@dpi.inpe.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorydpi.inpe.br/banon-pc2@80/2006/07.04.20.21
Next Higher Units-
1
2018:06.04.04.22.53
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8JMKD3MGPDW34P/48F29JE
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6. Notes
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