A scalable parallel minimum spanning tree algorithm for catchment basin delimitation in large digital elevation models
SUMMARY This paper describes a new fast and scalable parallel algorithm to automatically determine catchment basin of rivers in large digital elevation models (DEMs). This algorithm is based on the construction of a minimal spanning tree, via a hierarchy of graphs, modeling the water route on the DE...
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| Veröffentlicht in: | Concurrency and computation 2013-07, Vol.25 (10), p.1394-1409 |
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| container_title | Concurrency and computation |
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| creator | Do, Hiep-Thuan Limet, Sébastien Melin, Emmanuel |
| description | SUMMARY
This paper describes a new fast and scalable parallel algorithm to automatically determine catchment basin of rivers in large digital elevation models (DEMs). This algorithm is based on the construction of a minimal spanning tree, via a hierarchy of graphs, modeling the water route on the DEM. It combines different techniques used in hydrogeology, image processing and graph theory to obtain the most accurate results in terms of geomorphology without any preprocessing. The method tends to exploit the most of the DEMs, avoiding misleading inconsistencies DEMs contain. It has been designed to be entirely parallel and scalable for architectures such as PC clusters. Some experiments are presented to show accuracy, efficiency and scalability on huge DEMs. Copyright © 2012 John Wiley & Sons, Ltd. |
| doi_str_mv | 10.1002/cpe.2950 |
| format | Article |
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This paper describes a new fast and scalable parallel algorithm to automatically determine catchment basin of rivers in large digital elevation models (DEMs). This algorithm is based on the construction of a minimal spanning tree, via a hierarchy of graphs, modeling the water route on the DEM. It combines different techniques used in hydrogeology, image processing and graph theory to obtain the most accurate results in terms of geomorphology without any preprocessing. The method tends to exploit the most of the DEMs, avoiding misleading inconsistencies DEMs contain. It has been designed to be entirely parallel and scalable for architectures such as PC clusters. Some experiments are presented to show accuracy, efficiency and scalability on huge DEMs. Copyright © 2012 John Wiley & Sons, Ltd.</description><identifier>ISSN: 1532-0626</identifier><identifier>EISSN: 1532-0634</identifier><identifier>DOI: 10.1002/cpe.2950</identifier><language>eng</language><publisher>Blackwell Publishing Ltd</publisher><subject>Algorithms ; Basins ; catchment basin ; Catchments ; Computer Science ; digital elevation model ; Digital Elevation Models ; Distributed, Parallel, and Cluster Computing ; geographic information system ; Geomorphology ; Graph theory ; image segmentation ; Mathematical models ; minimum spanning tree ; Reproduction</subject><ispartof>Concurrency and computation, 2013-07, Vol.25 (10), p.1394-1409</ispartof><rights>Copyright © 2012 John Wiley & Sons, Ltd.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4040-e274474afee6f6442b675b58d4832926c4ce39905c4bb65b50596e315ef7e4f93</citedby><cites>FETCH-LOGICAL-c4040-e274474afee6f6442b675b58d4832926c4ce39905c4bb65b50596e315ef7e4f93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fcpe.2950$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fcpe.2950$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,1416,27922,27923,45572,45573</link.rule.ids><backlink>$$Uhttps://hal.science/hal-00785859$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Do, Hiep-Thuan</creatorcontrib><creatorcontrib>Limet, Sébastien</creatorcontrib><creatorcontrib>Melin, Emmanuel</creatorcontrib><title>A scalable parallel minimum spanning tree algorithm for catchment basin delimitation in large digital elevation models</title><title>Concurrency and computation</title><addtitle>Concurrency Computat.: Pract. Exper</addtitle><description>SUMMARY
This paper describes a new fast and scalable parallel algorithm to automatically determine catchment basin of rivers in large digital elevation models (DEMs). This algorithm is based on the construction of a minimal spanning tree, via a hierarchy of graphs, modeling the water route on the DEM. It combines different techniques used in hydrogeology, image processing and graph theory to obtain the most accurate results in terms of geomorphology without any preprocessing. The method tends to exploit the most of the DEMs, avoiding misleading inconsistencies DEMs contain. It has been designed to be entirely parallel and scalable for architectures such as PC clusters. Some experiments are presented to show accuracy, efficiency and scalability on huge DEMs. Copyright © 2012 John Wiley & Sons, Ltd.</description><subject>Algorithms</subject><subject>Basins</subject><subject>catchment basin</subject><subject>Catchments</subject><subject>Computer Science</subject><subject>digital elevation model</subject><subject>Digital Elevation Models</subject><subject>Distributed, Parallel, and Cluster Computing</subject><subject>geographic information system</subject><subject>Geomorphology</subject><subject>Graph theory</subject><subject>image segmentation</subject><subject>Mathematical models</subject><subject>minimum spanning tree</subject><subject>Reproduction</subject><issn>1532-0626</issn><issn>1532-0634</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNp10ctOGzEUBuARKhKUIvURvITFUN-dWUYRBKSIogJC6sY645xJDPbM1J6k5e07UapUXXR1bp_O5i-Kz4xeMUr5F9fjFa8UPSpOmRK8pFrID4ee65PiY86vlDJGBTsttlOSHQSoA5IeEoSAgUTf-riJJPfQtr5dkSEhEgirLvlhHUnTJeJgcOuI7UBqyL4lSww--gEG37VknAOkFZKlX427QDDgdn-K3Sjzp-K4gZDx_E89K55vrp9mt-Xi6_xuNl2UTlJJS-RGSiOhQdSNlpLX2qhaTZZyInjFtZMORVVR5WRd6_FCVaVRMIWNQdlU4qy43P9dQ7B98hHSu-3A29vpwu52lJqJmqhqy0Z7sbd96n5sMA82-uwwBGix22TLpKiMkpzrv9SlLueEzeE3o3YXgx1jsLsYRlru6U8f8P2_zs4erv_1Pg_46-AhvVlthFH25X5uv5v7h5tvj3MrxW8UmZh1</recordid><startdate>201307</startdate><enddate>201307</enddate><creator>Do, Hiep-Thuan</creator><creator>Limet, Sébastien</creator><creator>Melin, Emmanuel</creator><general>Blackwell Publishing Ltd</general><general>Wiley</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>1XC</scope></search><sort><creationdate>201307</creationdate><title>A scalable parallel minimum spanning tree algorithm for catchment basin delimitation in large digital elevation models</title><author>Do, Hiep-Thuan ; Limet, Sébastien ; Melin, Emmanuel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4040-e274474afee6f6442b675b58d4832926c4ce39905c4bb65b50596e315ef7e4f93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Algorithms</topic><topic>Basins</topic><topic>catchment basin</topic><topic>Catchments</topic><topic>Computer Science</topic><topic>digital elevation model</topic><topic>Digital Elevation Models</topic><topic>Distributed, Parallel, and Cluster Computing</topic><topic>geographic information system</topic><topic>Geomorphology</topic><topic>Graph theory</topic><topic>image segmentation</topic><topic>Mathematical models</topic><topic>minimum spanning tree</topic><topic>Reproduction</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Do, Hiep-Thuan</creatorcontrib><creatorcontrib>Limet, Sébastien</creatorcontrib><creatorcontrib>Melin, Emmanuel</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Concurrency and computation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Do, Hiep-Thuan</au><au>Limet, Sébastien</au><au>Melin, Emmanuel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A scalable parallel minimum spanning tree algorithm for catchment basin delimitation in large digital elevation models</atitle><jtitle>Concurrency and computation</jtitle><addtitle>Concurrency Computat.: Pract. Exper</addtitle><date>2013-07</date><risdate>2013</risdate><volume>25</volume><issue>10</issue><spage>1394</spage><epage>1409</epage><pages>1394-1409</pages><issn>1532-0626</issn><eissn>1532-0634</eissn><abstract>SUMMARY
This paper describes a new fast and scalable parallel algorithm to automatically determine catchment basin of rivers in large digital elevation models (DEMs). This algorithm is based on the construction of a minimal spanning tree, via a hierarchy of graphs, modeling the water route on the DEM. It combines different techniques used in hydrogeology, image processing and graph theory to obtain the most accurate results in terms of geomorphology without any preprocessing. The method tends to exploit the most of the DEMs, avoiding misleading inconsistencies DEMs contain. It has been designed to be entirely parallel and scalable for architectures such as PC clusters. Some experiments are presented to show accuracy, efficiency and scalability on huge DEMs. Copyright © 2012 John Wiley & Sons, Ltd.</abstract><pub>Blackwell Publishing Ltd</pub><doi>10.1002/cpe.2950</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
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| source | Wiley Online Library All Journals |
| subjects | Algorithms Basins catchment basin Catchments Computer Science digital elevation model Digital Elevation Models Distributed, Parallel, and Cluster Computing geographic information system Geomorphology Graph theory image segmentation Mathematical models minimum spanning tree Reproduction |
| title | A scalable parallel minimum spanning tree algorithm for catchment basin delimitation in large digital elevation models |
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