Database Design for High-Resolution LIDAR Topography Data
Identifieur interne : 000212 ( Istex/Curation ); précédent : 000211; suivant : 000213Database Design for High-Resolution LIDAR Topography Data
Auteurs : Viswanath Nandigam ; Chaitan Baru ; Christopher CrosbySource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2010.
Abstract
Abstract: The advent of high-resolution mapping technologies such as airborne Light Detection and Ranging (LIDAR) has revolutionized the study of processes acting on the earth’s surface. However, the massive volumes of data produced by LIDAR technology pose significant technical challenges in terms of the management and web-based distribution of these datasets. This paper provides a case study in the use of relational database technology for serving large airborne LIDAR “point cloud” datasets, as part of the National Science Foundation funded OpenTopography facility. We have experimented with the use of spatial extensions in the database as well as implementation solutions from a single partition database on a supercomputer resource to a multi-partition implementation on a shared-nothing commodity cluster for management of these terabyte scale datasets. We also describe future directions being pursued to support binary data formats and for scaling to larger system configurations.
Url:
DOI: 10.1007/978-3-642-13818-8_12
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Viswanath Nandigam<affiliation><mods:affiliation>San Diego Supercomputer Center, University of California San Diego</mods:affiliation><wicri:noCountry code="subField">Diego</wicri:noCountry></affiliation><affiliation><mods:affiliation>San Diego Supercomputer Center, University of California San Diego</mods:affiliation><wicri:noCountry code="subField">Diego</wicri:noCountry></affiliation><affiliation><mods:affiliation>San Diego Supercomputer Center, University of California San Diego</mods:affiliation><wicri:noCountry code="subField">Diego</wicri:noCountry></affiliation>Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Database Design for High-Resolution LIDAR Topography Data</title><author><name sortKey="Nandigam, Viswanath" sort="Nandigam, Viswanath" uniqKey="Nandigam V" first="Viswanath" last="Nandigam">Viswanath Nandigam</name><affiliation><mods:affiliation>San Diego Supercomputer Center, University of California San Diego</mods:affiliation><wicri:noCountry code="subField">Diego</wicri:noCountry></affiliation></author><author><name sortKey="Baru, Chaitan" sort="Baru, Chaitan" uniqKey="Baru C" first="Chaitan" last="Baru">Chaitan Baru</name><affiliation><mods:affiliation>San Diego Supercomputer Center, University of California San Diego</mods:affiliation><wicri:noCountry code="subField">Diego</wicri:noCountry></affiliation></author><author><name sortKey="Crosby, Christopher" sort="Crosby, Christopher" uniqKey="Crosby C" first="Christopher" last="Crosby">Christopher Crosby</name><affiliation><mods:affiliation>San Diego Supercomputer Center, University of California San Diego</mods:affiliation><wicri:noCountry code="subField">Diego</wicri:noCountry></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:108E86F2EE230EB3B2E070B4AFC26099BEFF8189</idno><date when="2010" year="2010">2010</date><idno type="doi">10.1007/978-3-642-13818-8_12</idno><idno type="url">https://api.istex.fr/document/108E86F2EE230EB3B2E070B4AFC26099BEFF8189/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000212</idno><idno type="wicri:Area/Istex/Curation">000212</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Database Design for High-Resolution LIDAR Topography Data</title><author><name sortKey="Nandigam, Viswanath" sort="Nandigam, Viswanath" uniqKey="Nandigam V" first="Viswanath" last="Nandigam">Viswanath Nandigam</name><affiliation><mods:affiliation>San Diego Supercomputer Center, University of California San Diego</mods:affiliation><wicri:noCountry code="subField">Diego</wicri:noCountry></affiliation></author><author><name sortKey="Baru, Chaitan" sort="Baru, Chaitan" uniqKey="Baru C" first="Chaitan" last="Baru">Chaitan Baru</name><affiliation><mods:affiliation>San Diego Supercomputer Center, University of California San Diego</mods:affiliation><wicri:noCountry code="subField">Diego</wicri:noCountry></affiliation></author><author><name sortKey="Crosby, Christopher" sort="Crosby, Christopher" uniqKey="Crosby C" first="Christopher" last="Crosby">Christopher Crosby</name><affiliation><mods:affiliation>San Diego Supercomputer Center, University of California San Diego</mods:affiliation><wicri:noCountry code="subField">Diego</wicri:noCountry></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2010</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">108E86F2EE230EB3B2E070B4AFC26099BEFF8189</idno><idno type="DOI">10.1007/978-3-642-13818-8_12</idno><idno type="ChapterID">12</idno><idno type="ChapterID">Chap12</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: The advent of high-resolution mapping technologies such as airborne Light Detection and Ranging (LIDAR) has revolutionized the study of processes acting on the earth’s surface. However, the massive volumes of data produced by LIDAR technology pose significant technical challenges in terms of the management and web-based distribution of these datasets. This paper provides a case study in the use of relational database technology for serving large airborne LIDAR “point cloud” datasets, as part of the National Science Foundation funded OpenTopography facility. We have experimented with the use of spatial extensions in the database as well as implementation solutions from a single partition database on a supercomputer resource to a multi-partition implementation on a shared-nothing commodity cluster for management of these terabyte scale datasets. We also describe future directions being pursued to support binary data formats and for scaling to larger system configurations.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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